Non-orthogonal multiple access (NOMA) and massive multiple-input multiple-output (MIMO) systems are highly efficient. Massive MIMO systems are inherently resistant to passive attackers (eavesdroppers), thanks to transmissions directed to the users. However, active attackers can transmit a combination of legitimate user pilot signals during the channel estimation phase. This way, they can mislead the base station (BS) to rotate the transmission in their direction and allow them to eavesdrop during the downlink data transmission phase. In this paper, we analyze this vulnerability with two-user pairing strategies and investigate how physical layer security can mitigate such attacks and ensure secure (confidential) communication. We derive the secrecy outage probability (SOP) and a lower bound on the ergodic secrecy capacity using stochastic geometry tools when the number of antennas in the BSs tends to infinity (i.e., massive MIMO BS). The numerical and simulation results show that one of the strategies performs better and has a higher ergodic secrecy rate (ESR) and lower SOP. Moreover, we show that using NOMA instead of orthogonal multiple access (OMA) improves system performance significantly.

The deployment of Internet of Things (IoT) devices requires efficient security mechanisms. However, cryptographic solutions often prove resource-intensive. Radio Frequency Fingerprinting (RFF) enables device authentication through the intrinsic characteristics of RF signals at the Physical (PHY)-layer. Deploying RFF presents two challenges: ensuring operational efficiency and scalability in resource-constrained environments. This paper presents a lightweight Edge AI-based RFF model for device authentication using PHY-layer characteristics. Our approach implements a Deep Learning (DL) model to extract device-specific features from IQ samples, converted using TensorFlow Lite for edge deployment. Evaluation on Raspberry Pi demonstrates high accuracy (> 0.95) and Receiver Operating Characteristic-Area Under the Curve (ROC-AUC) scores (> 0.90), while maintaining a compact model size suitable for resource-constrained environments.

Vehicular Communication Systems (VCSs) enhance safety by enabling communication among vehicles and road-side infrastructure. To provide secure communication and privacy, a Vehicular Public-Key Infrastructure (VPKI) distributes long-term and temporary credentials (pseudonyms) to validate Cooperative Awareness Messages (CAMs) and other communication by registered vehicles. However, improperly designed pseudonym-based privacy techniques are still vulnerable to pseudonym linking based on their issuer, i.e., a specific Pseudonymous Certification Authority (PCA) that signed the pseudonyms in one batch, in the presence of PCAs. As each PCA digitally signs pseudonyms, the presence of distinct PCAs makes linking pseudonyms easier. We propose two strategies, Interleaved Pseudonym Distribution (IPD) and Random Interleaved Pseudonym Distribution (RIPD), to mitigate linking. Multi-PCA collaboration allows distributing interleaved pseudonyms (issued by different PCAs), reducing linkability. To assess our scheme privacy enhancement, a PCAid-based pseudonym linking algorithm is developed utilizing a Kalman filter and road information to track vehicles. Simulation results show that IPD provides a moderate improvement in pseudonym confusion, while RIPD significantly disrupts PCAid-based linking, enhancing vehicle privacy. The proof-of-concept implementation of our scheme shows the efficiency of our scheme, compared to the baseline that a single PCA issues all pseudonyms within one request.

We propose Privacy-Enhanced Secure Neighbor Discovery (PE-SND), a lightweight protocol that addresses the security and privacy needs of existing and emerging wireless networks. Traditional Secure Neighbor Discovery (SND) protocols effectively mitigate relay attacks but expose device identities and locations. Our protocol preserves SND security guarantees while enhancing privacy through pseudonymous authentication and encrypted location exchange. Formal verification confirms pseudonym unlinkability and location confidentiality against both external adversaries and honest-but-curious participants. Performance evaluation across security levels (96 to 256 bits) demonstrates feasibility with processing latencies of$\mathbf{1 4}$to$\mathbf{7 5} \text{ms}$. Deployment of PE-SND using Ultra-Wide-Band (UWB) technology confirms sub-meter accuracy ($\mathbf{1 5} \text{cm}$) in indoor Line-of-Sight (LoS) and 0.953 m in Non-Line-of-Sight (NLoS) environments, with execution times up to 90 ms. PE-SND provides a lightweight solution for privacy-demanding applications in the Internet of Things (IoT), Internet of Vehicles (IoV), and other emerging wireless ecosystems.

Standardized Vehicular Communication (VC), mainly Cooperative Awareness Messages (CAMs) and Decentralized Environmental Notification Messages (DENMs), is paramount to vehicle safety, carrying vehicle status information and reports of traffic/road-related events respectively. Broadcasted CAMs and DENMs are pseudonymously authenticated for security and privacy protection, with each node needing to have all incoming messages validated within an expiration deadline. This creates an asymmetry that can be easily exploited by external adversaries to launch a clogging Denial of Service (DoS) attack: each forged VC message forces all neighboring nodes to cryptographically validate it; at increasing rates, easy to generate forged messages gradually exhaust processing resources and severely degrade or deny timely validation of benign CAMs/DENMs. The result can be catastrophic when awareness of neighbor vehicle positions or critical reports are missed. We address this problem making the standardized VC pseudonymous authentication DoS-resilient . We propose efficient cryptographic constructs, which we term message verification facilitators , to prioritize processing resources for verification of potentially valid messages among bogus messages and verify multiple messages based on one signature verification. Any message acceptance is strictly based on public-key based message authentication/verification for accountability , i.e., non-repudiation is not sacrificed, unlike symmetric key based approaches. This further enables drastic misbehavior detection , also exploiting the newly introduced facilitators, based on probabilistic signature verification and cross-checking over multiple facilitators verifying the same message; while maintaining verification latency low even when under attack, trading off modest communication overhead. Our facilitators can also be used for efficient discovery and verification of DENM or any event-driven message , including misbehavior evidence used for our scheme. Even when vehicles are saturated by adversaries mounting a clogging DoS attack, transmitting high-rate bogus CAMs/DENMs, our scheme achieves an average 50 m s verification delay with message expiration ratio less than 1% - a huge improvement over the current standard that verifies every message signature in a First-Come First-Served (FCFS) manner and suffers from having 50% to nearly 100% of the received benign messages expiring.

The limited or no protection for civilian Global Navigation Satellite System (GNSS) signals makes spoofing attacks relatively easy. With modern mobile devices often featuring network interfaces, state-of-the-art signals of opportunity (SOP) schemes can provide accurate network positions in replacement of GNSS. The use of onboard inertial sensors can also assist in the absence of GNSS, possibly in the presence of jammers. The combination of SOP and inertial sensors has received limited attention, yet it shows strong results on fully custom-built platforms. We do not seek to improve such special-purpose schemes. Rather, we focus on countering GNSS attacks, notably detecting them, with emphasis on deployment with consumer-grade platforms, notably smartphones, that provide off-the-shelf opportunistic information (i.e., network position and inertial sensor data). Our Position-based Attack Detection Scheme (PADS) is a probabilistic framework that uses regression and uncertainty analysis for positions. The regression optimization problem is a weighted mean square error of polynomial fitting, with constraints that the fitted positions satisfy the device velocity and acceleration. Then, uncertainty is modeled by a Gaussian process, which provides more flexibility to analyze how sure or unsure we are about position estimations. In the detection process, we combine all uncertainty information with the position estimations into a fused test statistic, which is the input utilized by an anomaly detector based on outlier ensembles. The evaluation shows that the PADS outperforms a set of baseline methods that rely on SOP or inertial sensor-based or statistical tests, achieving up to 3 times the true positive rate at a low false positive rate.

Global Navigation Satellite Systems (GNSS) are fundamental in ubiquitously providing position and time to a wide gamut of systems. Jamming remains a realistic threat in many deployment settings, civilian and tactical. Specifically, in drones sustained denial raises safety critical concerns. This work presents a strategy that allows detection, localization, and classification both in the frequency and time domain of interference signals harmful to navigation. A high-performance Vertical Take Off and Landing (VTOL) drone with a single antenna and a commercial GNSS receiver is used to geolocate and characterize RF emitters at long range, to infer the navigation impairment. Raw IQ baseband snapshots from the GNSS receiver make the application of spectral correlation methods possible without extra software-defined radio payload, paving the way to spectrum identification and monitoring in airborne platforms, aiming at RF situational awareness. Live testing at Jammertest, in Norway, with portable, commercially available GNSS multi-band jammers demonstrates the ability to detect, localize, and characterize harmful interference. Our system pinpointed the position with an error of a few meters of the transmitter and the extent of the affected area at long range, without entering the denied zone. Additionally, further spectral content extraction is used to accurately identify the jammer frequency, bandwidth, and modulation scheme based on spectral correlation techniques.

Clogging Denial of Service (DoS) attacks have disrupted or disabled various networks, in spite of security mechanisms. External adversaries can severely harm networks, especially when high-overhead security mechanisms are deployed in resource-constrained systems. This can be especially true in the emerging standardized secure Vehicular Communication (VC) systems: mandatory message signature verification can be exploited to exhaust resources and prevent validating incoming messages sent by neighboring vehicles, information that is critical, often, for transportation safety. Efficient message verification schemes and better provisioned devices could serve as potential remedies, but existing solutions have limitations. We point out those and identify, challenges to address for scalable and resilient secure Vehicular Communication (VC) systems, and, most notably, the need for integrating defense mechanisms against clogging Denial of Service (DoS) attacks. We take the position that existing secure Vehicular Communication (VC) protocols are vulnerable to clogging Denial of Service (DoS) attacks and recommend symmetric key chain based pre-validation with mandatory signature verification to thwart clogging Denial of Service (DoS) attacks, while maintaining all key security properties, including non-repudiation to enable accountability.

Cyber-Physical Systems (CPSs) complexity has been continuously increasing to support new life-impacting applications, such as Internet of Things (IoT) devices or Industrial Control Systems (ICSs). These characteristics introduce new critical security challenges to both industrial practitioners and academics. This work investigates how Model-Based System Engineering (MBSE) and attack graph approaches could be leveraged to model secure Cyber-Physical System solutions and identify high-impact attacks early in the system development life cycle. To achieve this, we propose a new framework that comprises (1) an easily adoptable modeling paradigm for Cyber-Physical System representation, (2) an attack-graph-based solution for Cyber-Physical System automatic quantitative security analysis, based on the MulVAL security tool, (3) a set of Model-To-Text (MTT) transformation rules to bridge the gap between SysML and MulVAL. We illustrated the validity of our proposed framework through an autonomous ventilation system example. A Denial of Service (DoS) attack targeting an industrial communication protocol was identified and displayed as attack graphs. In future work, we intend to connect the approach to dynamic security databases for automatic countermeasure selection.

Radio Frequency Fingerprinting (RFF) techniques promise to authenticate wireless devices at the physical layer based on inherent hardware imperfections introduced during manufacturing. Such RF transmitter imperfections are reflected into over-the-air signals, allowing receivers to accurately identify the RF transmitting source. Recent advances in Machine Learning, particularly in Deep Learning (DL), have improved the ability of RFF systems to extract and learn complex features that make up the device-specific fingerprint. However, integrating DL techniques with RFF and operating the system in real-world scenarios presents numerous challenges, originating from the embedded systems and the DL research domains. This paper systematically identifies and analyzes the essential considerations and challenges encountered in the creation of DL-based RFF systems across their typical development life-cycle, which include (i) data collection and preprocessing, (ii) training, and finally, (iii) deployment. Our investigation provides a comprehensive overview of the current open problems that prevent real deployment of DL-based RFF systems while also discussing promising research opportunities to enhance the overall accuracy, robustness, and privacy of these systems.

Traditional Neighbor Discovery (ND) and Secure Neighbor Discovery (SND) are key elements for network functionality. SND is a hard problem, satisfying not only typical security properties (authentication, integrity) but also verification of direct communication, which involves distance estimation based on time measurements and device coordinates. Defeating relay attacks, also known as "wormholes", leading to stealthy Byzantine links and significant degradation of communication and adversarial control, is key in many wireless networked systems. However, SND is not concerned with privacy; it necessitates revealing the identity and location of the device(s) participating in the protocol execution. This can be a deterrent for deployment, especially involving user-held devices in the emerging Internet of Things (IoT) enabled smart environments. To address this challenge, we present a novel Privacy-Preserving Secure Neighbor Discovery (PP-SND) protocol, enabling devices to perform SND without revealing their actual identities and locations, effectively decoupling discovery from the exposure of sensitive information. We use Homomorphic Encryption (HE) for computing device distances without revealing their actual coordinates, as well as employing a pseudonymous device authentication to hide identities while preserving communication integrity. PP-SND provides SND [1] along with pseudonymity, confidentiality, and unlinkability. Our presentation here is not specific to one wireless technology, and we assess the performance of the protocols (cryptographic overhead) on a Raspberry Pi 4 and provide a security and privacy analysis.

Platooning has shown promising results in improving transportation safety and decreasing fuel consumption. Vehicles enter these formations, to form convoys, while traveling to similar destinations. However, this implies trust in the information received by the other platoon members. Insider attackers performing falsification attacks can destabilize the platoon or cause catastrophic vehicle collisions. Detecting this type of misbehavior is not without shortcomings: benign mobility deviations can be, erroneously, flagged as misbehavior. Further, even when an attack is detected, the vehicles remain affected until the attacker is excluded from the formation. Thus, in this work, we address the need for a reliable mitigation approach. We propose a platoon restructuring scheme aiming to mitigate attacks and reduce the attacker's potential for further misbehavior. Our results, and analysis, show the feasibility of our approach, which manages to restore the formation's stability even when an attack is ongoing.

Medium Access Control (MAC) address randomization is a key component for privacy protection in Wi-Fi networks. Current proposals periodically change the mobile device MAC addresses when it disconnects from the Access Point (AP). This way frames cannot be linked across changes, but the mobile device presence is exposed as long as it remains connected: all its communication is trivially linkable by observing the randomized yet same MAC address throughout the connection. Our runtime MAC re-randomization scheme addresses this issue, reducing or eliminating Wi-Fi frames linkability without awaiting for or requiring a disconnection. Our MAC re-randomization is practically 'over-the-air': MAC addresses are re-randomized just before transmission, while the protocol stacks (at the mobile and the AP) maintain locally the original connection MAC addresses - making our MAC layer scheme transparent to upper layers. With an implementation and a set of small-scale experiments with off-the-shelf devices, we show the feasibility of our scheme and the potential towards future deployment.

These proceedings contain the papers selected for inclusion in the technical program for the 22st ACM Workshop on Privacy in the Electronic Society (ACM WPES 2023), held in conjunction with the 30th ACM Conference on Computer and Communication Security (ACM CCS 2023) at the Tivoli Congress Center in Copenhagen, Denmark, on November 26, 2023. In response to the workshop's call for papers, 31 valid submissions were received, including 21 full paper submissions and 10 short paper submissions. They were evaluated by a technical program committee consisting of 54 researchers whose backgrounds include a diverse set of topics related to privacy. Each paper was reviewed by at least 3 members of the program committee. Papers were evaluated based on their importance, novelty, and technical quality. After the rigorous review process, 9 submissions were accepted as full papers (acceptance rate: 29.0%) and an additional 8 submissions were accepted as short papers.

Side-channel attacks impose a serious threat to cryptographic algorithms, including widely employed ones, such as AES and RSA. These attacks take advantage of the algorithm implementation in hardware or software to extract secret information via side channels. Software masking is a mitigation approach against power side-channel attacks aiming at hiding the secret-revealing dependencies from the power footprint of a vulnerable implementation. However, this type of software mitigation often depends on general-purpose compilers, which do not preserve non-functional properties. Moreover, microarchitectural features, such as the memory bus and register reuse, may also leak secret information. These abstractions are not visible at the high-level implementation of the program. Instead, they are decided at compile time. To remedy these problems, security engineers often sacrifice code efficiency by turning off compiler optimization and/or performing local, post-compilation transformations. This paper proposes Secure by Construction Code Generation (SecCG), a constraint-based compiler approach that generates optimized yet protected against power side channels code. SecCG controls the quality of the mitigated program by efficiently searching the best possible low-level implementation according to a processor cost model. In our experiments with twelve masked cryptographic functions up to 100 lines of code on Mips32 and ARM Thumb, SecCG speeds up the generated code from 77% to 6.6 times compared to non-optimized secure code with an overhead of up to 13% compared to non-secure optimized code at the expense of a high compilation cost. For security and compiler researchers, this paper proposes a formal model to generate power side channel free low-level code. For software engineers, SecCG provides a practical approach to optimize performance critical and vulnerable cryptographic implementations that preserve security properties against power side channels.

Embedded devices are increasingly present in our everyday life. They often process critical information, and hence, rely on cryptographic protocols to achieve security. However, embedded devices remain particularly vulnerable to attackers seeking to hijack their operation and extract sensitive information by exploiting side channels and code reuse. Code-Reuse Attack (CRA) can steer the execution of a program to malicious outcomes, altering existing on-board code without direct access to the device memory. Moreover, Side-Channel Attacks (SCAs) may reveal secret information to the attacker based on mere observation of the device. Thwarting Code-Reuse Attacks (CRAs) and Side-Channel Attacks (SCAs) against embedded devices is especially challenging because embedded devices are usually resource constrained. Fine-grained code diversification can hinder CRAs by introducing uncertainty to the binary code; while software mechanisms can thwart timing or power SCAs. The resilience to either attack may come at the price of the overall efficiency. Moreover, a unified approach that preserves these mitigations against both CRAs and SCAs is not available. In this paper, we propose a novel Secure Diversity by Construction (SecDivCon) approach that tackles this challenge. SecDivCon is a combinatorial compiler-based approach that combines software diversification against CRAs with software mitigations against SCAs. SecDivCon restricts the performance overhead introduced by the generated code that thwarts the attacks and hence, offers a secure-by-design approach enabling control over the performance-security trade-off. Our experiments, using 16 benchmark programs, show that SCA-aware diversification is effective against CRAs, while preserving SCA mitigation properties at a low, controllable overhead. Given the combinatorial nature of our approach, SecDivCon is suitable for small, performance-critical functions that are sensitive to SCAs. SecDivCon may be used as a building block to whole-program code diversification or in a re-randomization scheme of cryptographic code.

The central building block of secure and privacy-preserving Vehicular Communication (VC) systems is a Vehicular Public Key Infrastructure (VPKI), which provides vehicles with multiple anonymized credentials, termedpseudonyms. These pseudonyms are used to ensure VC message authenticity and integrity while preserving vehicle (thus passenger) privacy. In the light of emerging large-scale multi-domain VC environments, the efficiency of the VPKI and, more broadly, its scalability are paramount. By the same token, preventing misuse of the credentials, in particular, Sybil-based misbehavior, and managing“honest-but-curious”VPKI entities are other facets of a challenging problem. In this paper, we leverage the state-of-the-art VPKI system andenhanceits functionality towards a highly-available, dynamically-scalable, and resilient design; this ensures that the system remains operational in the presence of benign failures or resource depletion attacks, and that it dynamicallyscales out, or possiblyscales in, according to request arrival rates. Our full-blown implementation on the Google Cloud Platform shows that deploying large-scale and efficient VPKI can be cost-effective: the processing latency to issue 100 pseudonyms is approximately 56 ms. More so, our experiments show that our VPKI system dynamically scales out or scales in according to the rate of pseudonyms requests. We formally assess the achieved security and privacy properties for the credential acquisition process. Overall, our scheme is a comprehensive solution that complements standards and can catalyze the deployment of secure and privacy-protecting VC systems.

Location-based services (LBS) increasingly rely on participatory or crowd-sensed data: users voluntarily contribute data about their whereabouts and points of interest (POIs) and allow the LBS to capture the dynamically changing environment, e.g., how crowded specific places, streets, or public transportation are. Popular LBS applications do not offer strong security, less so for their participatory sensing (PS) and data contribution part. Openness favors participation and increases data, but it also makes attacks easier. Sporadic misbehavior incidents and the presumed user honesty should not be reassuring: an attacker could exploit the PS components and submit a large volume of forged data to dominate the PS-collected LBS data, locally or at a large scale. Individuals, organizations, or entire areas could be targeted, e.g., having customers diverted or causing public transportation routes or roads to appear congested. The lingering open question is whether such attacks can be perpetrated against well-established popular LBS with PS components. This paper affirms this: we investigate Google Maps, the single most popular application in this domain, and show a range of effective and scalable attacks based on very modest adversarial assumptions. We reverse-engineer the data submission process and automate attacks that craft and submit false data in volume and a targeted fashion. We collect evidence that our attacks work on POI crowdedness, traffic congestion levels, and public transportation crowdedness with extreme caution. We responsibly disclosed the attacks to Google, acknowledged them and awarded recognition. The attack methodology carries over to other LBS applications but, most importantly, raises awareness and motivates countermeasures, which we also outline here, for stronger LBS and PS security overall.

Cooperative Adaptive Cruise Control, a promising Vehicular Ad-hoc Network application, automates transportation and improves efficiency. Vehicles form a platoon, following a leader, with their controllers automatically adjusting velocity, based on messages by other vehicles, to keep appropriate distances for safety. Towards deploying secure Cooperative Adaptive Cruise Control, several proposals in academia and standardization leave significant questions unanswered. Thwarting adversaries is hard: cryptographic protection ensures access control (authentication and authorization) but falsified kinematic information by faulty insiders (platoon members with credentials, even the platoon leader) can cause platoon instability or vehicle crashes. Filtering out such adversarial data is challenging (computational cost and high false positive rates) but, most important, state-of-the-art misbehavior detection algorithms completely fail during platoon maneuvering. In this paper, we systematically investigate how and to what extent controllers for existing platooning applications are vulnerable, mounting a gamut of attacks, ranging from falsification attacks to jamming and collusion; including two novel attacks during maneuvering. We show how the existing middle-join and leave processes are vulnerable to falsification or 'privilege escalation' attacks. We mitigate such vulnerabilities and enable vehicles joining and exiting from any position (middle-join and middle-exit). We propose a misbehavior detection system that achieves an F1 score of 87% on identifying attacks throughout the lifetime of the platoon formation, including maneuvers. Our cyberphysical simulation framework can be extended to assess any other driving automation functionality in the presence of attackers.

While recent research on intelligent transportation systems including vehicular communication systems has focused on technical aspects, little research work has been conducted on drivers’ privacy perceptions and preferences. Understanding the driver’s privacy perceptions and preferences will allow researchers to design usable privacy and identity management systems offering user privacy choices and controls for intelligent transportation systems. We conducted in-depth semi-structured interviews with 17 Swedish drivers to analyse their privacy perceptions and preferences for intelligent transportation systems, particularly for user control and for privacy trade-offs with cost, safety and usability. We also compare our results from the interviews with Swedish drivers with results from interviews that we conducted previously with South African drivers. Our cross-cultural comparison shows that perceived privacy implications, the drivers’ willingness to share location information under certain conditions with other parties, as well as their appreciation of Privacy Enhancing Technologies differ significantly across drivers with different cultural backgrounds. We further discuss the cultural impact on privacy preferences, including those for privacy trade-offs, and the implications of our results for usable privacy-enhancing Identity Management for future vehicular communication systems. In particular, we provide recommendations for suitable pre-defined privacy options to be offered to users with different cultural backgrounds enabling them to easily make privacy-related control choices.

We propose HERMES, a scalable, secure, and privacy-enhancing system for users to share and access vehicles. HERMES securely outsources operations of vehicle access token (AT) generation to a set of untrusted servers. It builds on an earlier proposal, namely, SePCAR, and extends the system design for improved efficiency and scalability. To cater to system and user needs for secure and private computations, HERMES utilizes and combines several cryptographic primitives with secure multiparty computation (MPC) efficiently. It conceals secret keys of vehicles and transaction details from the servers, including vehicle booking details, AT information, and user and vehicle identities. It also provides user accountability in case of disputes. Besides, we provide semantic security analysis and prove that HERMES meets its security and privacy requirements. Last but not least, we demonstrate that HERMES is efficient and, in contrast to SePCAR, scales to a large number of users and vehicles, making it practical for real-world deployments. We build our evaluations with two different MPC protocols: 1) HtMAC-MiMC and 2) CBC-MAC-AES. Our results demonstrate that HERMES is in the range of milliseconds for generating an AT, whether it operates for a single-vehicle owner or a large rental-company branch with over 1000 vehicles; handling 546 and 84 AT generations per second, respectively. As a result, HERMES is an order of magnitude faster compared to SePCAR. Specifically, it delivers 696 (with HtMAC-MiMC) and 42 (with CBC-MAC-AES) more ATs compared to in SePCAR for a single-vehicle owner AT generation. Furthermore, we show that HERMES is practical on the vehicle side, too, as AT operations performed on a prototype vehicle on-board unit take only$\approx 62 $ms.

Large service providers use load balancers to dispatch millions of incoming connections per second towards thousands of servers. There are two basic yet critical requirements for a load balancer:uniform load distributionof the incoming connections across the servers, which requires to support advanced load balancing mechanisms, andper-connection-consistency(PCC), i.e, the ability to map packets belonging to the same connection to the same server even in the presence of changes in the number of active servers and load balancers. Yet, simultaneously meeting these requirements has been an elusive goal. Today’s load balancers minimize PCC violations at the price of non-uniform load distribution. This paper presents Cheetah, a load balancer that supports advanced load balancing mechanismsandPCC while being scalable, memory efficient, fast at processing packets, and offers comparable resilience to clogging attacks as with today’s load balancers. The Cheetah LB design guarantees PCC foranyrealizable server selection load balancing mechanism and can be deployed in both stateless and stateful manners, depending on operational needs. We implemented Cheetah on both a software and a Tofino-based hardware switch. Our evaluation shows that a stateless version of Cheetah guarantees PCC, has negligible packet processing overheads, and can support load balancing mechanisms that reduce the flow completion time by a factor of$2-3 \times $.

Backscatter enables wireless transmissions at dramatically lower power compared to mainstream Internet of Things (IoT) transmitters. This significantly improves battery life or even eliminates the need of batteries for backscatter-based 'tags' operating on energy harvested from the environment. However, trading off complexity for low power consumption exposing backscatter tags to a multitude of security risks. A significant challenge is imposter tags that mimic legitimate tag behaviour, compromising the system data integrity. In this work, we argue that tag simplicity and operation on harvested energy can help identify imposter transmissions, thus safeguarding data integrity. Our experimental study reveals that commonly used low-power tag oscillators demonstrate unique fingerprint patterns when exposed to the dynamics of harvested energy. Based on this observation, we design and propose HarvestPrint, which leverages these fingerprints to differentiate authentic backscatter transmissions from imposter transmissions. Experiments with a tag powered through a small solar cell show the potential of HarvestPrint.

Non-orthogonal multiple access (NOMA) and massive multiple-input multiple-output (MIMO) systems are highly efficient. Massive MIMO systems are inherently resistant to passive attackers (eavesdroppers), thanks to transmissions directed to the desired users. However, active attackers can transmit a combination of legitimate user pilot signals during the channel estimation phase. This way they can mislead the base station (BS) to rotate the transmission in their direction, and allow them to eavesdrop during the downlink data transmission phase. In this paper, we analyse this vulnerability in an improved system model and stronger adversary assumptions, and investigate how physical layer security can mitigate such attacks and ensure secure (confidential) communication. We derive the secrecy outage probability (SOP) and a lower bound on the ergodic secrecy capacity, using stochastic geometry tools when the number of antennas in the BSs tends to infinity. We adapt the result to evaluate the secrecy performance in massive orthogonal multiple access (OMA). We find that appropriate power allocation allows NOMA to outperform OMA in terms of ergodic secrecy rate and SOP.

Global Navigation Satellite Systems (GNSSs) are ubiquitously relied upon for positioning and timing. Detection and prevention of attacks against GNSS have been researched over the last decades, but many of these attacks and countermeasures were evaluated based on simulation. This work contributes to the experimental investigation of GNSS vulnerabilities, implementing a relay/replay attack with off-the-shelf hardware. Operating at the signal level, this attack type is not hindered by cryptographically protected transmissions, such as Galileo's Open Service Navigation Message Authentication (OS-NMA). The attack we investigate involves two colluding adversaries, relaying signals over large distances, to effectively spoof a GNSS receiver. We demonstrate the attack using off-the-shelf hardware, we investigate the requirements for such successful colluding attacks, and how they can be enhanced, e.g., allowing for finer adversarial control over the victim receiver.

To mitigate spoofing attacks targeting global navigation satellite systems (GNSS) receivers, one promising method is to rely on alternative time sources, such as network-based synchronization, in order to detect clock offset discrepancies caused by GNSS attacks. However, in case of no network connectivity, such validation references would not be available. A viable option is to rely on a local time reference; in particular, precision hardware clock ensembles of chip-scale thermally stable oscillators with extended holdover capabilities. We present a preliminary design and results towards a custom device capable of providing a stable reference, with smaller footprint and cost compared to traditional precision clocks. The system is fully compatible with existing receiver architecture, making this solution feasible for most industrial scenarios. Further integration with network-based synchronization can provide a complete time assurance system, with high short- and long-term stability.

Vehicular communications disclose rich information about the vehicles and their whereabouts. Pseudonymous authentication secures communication while enhancing user privacy. To enhance location privacy, cryptographic mix zones were proposed to facilitate vehicles covertly transition to new ephemeral credentials. The resilience to (syntactic and semantic) pseudonym linking (attacks) highly depends on the geometry of the mix zones, mobility patterns, vehicle density, and arrival rates. We introduce a tracking algorithm for linking pseudonyms before and after a cryptographically protected mix zone. Our experimental results show that an eavesdropper, leveraging standardized vehicular communication messages and road layout, could successfully link ≈73% of pseudonyms during nonrush hours and ≈62% of pseudonyms during rush hours after vehicles change their pseudonyms in a mix zone. To mitigate such inference attacks, we present a novel cooperative mix zone scheme that enhances user privacy regardless of the vehicle mobility patterns, vehicle density, and arrival rate to the mix zone. A subset of vehicles, termed relaying vehicles, is selected to be responsible for emulating nonexisting vehicles. Such vehicles cooperatively disseminate decoy traffic without affecting safety-critical operations: with 50% of vehicles as relaying vehicles, the probability of linking pseudonyms (for the entire interval) drops from ≈68% to ≈18%. On average, this imposes 28 ms extra computation overhead, per second, on the roadside unit (RSU) and 4.67 ms extra computation overhead, per second, on the (relaying) vehicle side; it also introduces 1.46 kB/s extra communication overhead by (relaying) vehicles and 45 kB/s by RSUs for the dissemination of decoy traffic. Thus, user privacy is enhanced at the cost of low computation and communication overheads.

In spite of progress in securing vehicular communication (VC) systems, there is no consensus on how to distribute certificate revocation lists (CRLs). The main challenges lie exactly in (i) crafting an efficient and timely distribution of CRLs for numerous anonymous credentials, pseudonyms, (ii) maintaining strong privacy for vehicles prior to revocation events, even with honest-but-curious system entities, (iii) and catering to computation and communication constraints of on-board units with intermittent connectivity to the infrastructure. Relying on peers to distribute the CRLs is a double-edged sword: abusive peers could “pollute” the process, thus degrading the timely CRLs distribution. In this paper, we propose a vehicle-centric solution that addresses all these challenges and thus closes a gap in the literature. Our scheme radically reduces CRL distribution overhead: each vehicle receives CRLs corresponding only to its region of operation and its actual trip duration. Moreover, a “fingerprint” of CRL `pieces' is attached to a subset of (verifiable) pseudonyms for fast CRL `piece' validation (while mitigating resource depletion attacks abusing the CRL distribution). Our experimental evaluation shows that our scheme is efficient, scalable, dependable, and practical: with no more than 25 KB/s of traffic load, the latest CRL can be delivered to 95 percent of the vehicles in a region (15×15 KM) within 15s, i.e., more than 40 times faster than the state-of-the-art. Overall, our scheme is a comprehensive solution that complements standards and can catalyze the deployment of secure and privacy-protecting VC systems.

The central building block of secure and privacy-preserving Vehicular Communication (VC) systems is a Vehicular Public-Key Infrastructure (VPKI), which provides vehicles with multiple anonymized credentials, termed pseudonyms. These pseudonyms are used to ensure message authenticity and integrity while preserving vehicle (thus passenger) privacy. In the light of emerging large-scale multi-domain VC environments, the efficiency of the VPKI and, more broadly, its scalability are paramount. By the same token, preventing misuse of the credentials, in particular, Sybil-based misbehavior, and managing "honest-but-curious" insiders are other facets of a challenging problem. In this paper, we leverage the state-of-the-art VPKI system and enhance its functionality towards a highly-available, dynamically-scalable, and resilient design; this ensures that the system remains operational in the presence of benign failures or resource depletion attacks, and that it dynamically scales out, or possibly scales in, according to request arrival rates. Our full-blown implementation on the Google Cloud Platform shows that deploying large-scale and efficient VPKI can be cost-effective.

Location-Based Services (LBSs) provide valuable services, with convenient features for mobile users. However, the location and other information disclosed through each query to the LBS erodes user privacy. This is a concern especially because LBS providers can be honest-but-curious , collecting queries and tracking users’ whereabouts and infer sensitive user data. This motivated both centralized and decentralized location privacy protection schemes for LBSs: anonymizing and obfuscating LBS queries to not disclose exact information, while still getting useful responses. Decentralized schemes overcome disadvantages of centralized schemes, eliminating anonymizers, and enhancing users’ control over sensitive information. However, an insecure decentralized system could create serious risks beyond private information leakage. More so, attacking an improperly designed decentralized LBS privacy protection scheme could be an effective and low-cost step to breach user privacy. We address exactly this problem, by proposing security enhancements for mobile data sharing systems. We protect user privacy while preserving accountability of user activities, leveraging pseudonymous authentication with mainstream cryptography. We show our scheme can be deployed with off-the-shelf devices based on an experimental evaluation of an implementation in a static automotive testbed.

We study the State-Dependent Gaussian Z-Interference Channel (SDG-ZIC), with two senders transmitting two independent messages through a Gaussian Z-interference channel with the same state. Transmitter 1 interferes with receiver 2, while transmitter 2 does not interfere with receiver 1. In addition, both receivers suffer from the same but differently scaled random state sequence, which is non-causally known at both transmitters. As mentioned in [1], the challenge here is to fully cancel differently scaled states at both receivers. Proposing transmission schemes based on nested lattice codes, we show that under some new conditions, the state at both receivers can be fully canceled and the capacity region can be fully achieved.

We study, using information-theoretic security methods, the so-called symmetric two-hop channel with an untrusted relay. In this model, a source wants to send its message reliably and securely to the destination through an honest but curious relay. The relay acts as a passive eavesdropper. Our investigation, in line with the relevant literature, seeks to determine what rate, termed secrecy rate, is achievable. To do that, we consider a typical setting, with the destination cooperating with the source, sending a 'scrambling' signal to conceal the message from the relay. To derive the achievable secrecy rate, we propose a novel scheme based on nested lattice codes. We show that our scheme outperforms all existing schemes and it achieves the outer bound for this channel model within 0.33 bits.

Participatory sensing systems need to gather information from a large number of participants. However, the openness of the system is a double-edged sword: by allowing practically any user to join, the system can be abused by an attacker who introduces a large number of virtual devices. This poster proposes a hardened registration process for Participatory Sensing to raise the bar: registrations are screened through a number of defensive measures, towards rejecting spurious registrations that do not correspond to actual devices. This deprives an adversary from a relatively easy take-over and, at the same time, allows a flexible and open registration process. The defensive measures are incorporated in the participatory sensing application.

Security mechanisms for battery-free devices have to operate under severe energy constraints relying on harvested energy. This is challenging, as the energy harvested from the ambient environment is usually scarce, intermittent and unpredictable. One of the challenges for developing security mechanisms for such settings is the lack of hardware platforms that recreate energy harvesting conditions experienced on a battery-free sensor node. In this demonstration, we present an energy harvesting security (EHS) platform that enables the development of security algorithms for battery-free sensors. Our results demonstrate that our platform is able to harvest sufficient energy from indoor lighting to support several widely used cryptography algorithms.

Radio Tomographic Imaging (RTI) enables novel radio frequency (RF) sensing applications such as intrusion detection systems by observing variations in radio links caused by human actions. RTI applications are, however, severely limited by the requirement to retrofit existing infrastructure with energy-expensive sensors. In this demonstration, we present our ongoing efforts to develop the first battery-free RTI system that operates on minuscule amounts of energy harvested from the ambient environment. Our system eliminates the energy-expensive components employed on state-of-the-art RTI systems achieving two orders of magnitude lower power consumption. Battery-free operation enables a sustainable deployment, as RTI sensors could be deployed for long periods of time with little maintenance effort. Our demonstration showcases an intrusion detection scenario enabled by our system.

Safety beaconing is a basic, yet essential component in secure Vehicular Communication systems. Safety beacons, broadcasted periodically, provide real-time vehicle status to surrounding vehicles, which can be used to provide spatial and mobility awareness. However, secure and privacy-preserving beacons incur high computation overhead, especially when the vehicle density is high or in the presence of adversarial nodes. Here, we show through experimental evaluation how to significantly decrease beacon verification delay.

Inter-vehicle communications disclose rich information about vehicle whereabouts. Pseudonymous authentication secures communication while enhancing user privacy thanks to a set of anonymized certificates, termed pseudonyms. Vehicles switch the pseudonyms (and the corresponding private key) frequently; we term this pseudonym transition process. However, exactly because vehicles can in principle change their pseudonyms asynchronously, an adversary that eavesdrops (pseudonymously) signed messages, could link pseudonyms based on the times of pseudonym transition processes. In this poster, we show how one can link pseudonyms of a given vehicle by simply looking at the timing information of pseudonym transition processes. We also propose "mix-zone everywhere": time-aligned pseudonyms are issued for all vehicles to facilitate synchronous pseudonym update; as a result, all vehicles update their pseudonyms simultaneously, thus achieving higher user privacy protection.

In spite of progress in securing Vehicular Communication (VC) systems, there is no consensus on how to distribute Certificate Revocation Lists (CRLs). The main challenges lie exactly in (i) crafting an efficient and timely distribution of CRLs for numerous anonymous credentials, pseudonyms, (ii) maintaining strong privacy for vehicles prior to revocation events, even with honest-but-curious system entities, (iii) and catering to computation and communication constraints of on-board units with intermittent connectivity to the infrastructure. Relying on peers to distribute the CRLs is a double-edged sword: abusive peers could "pollute" the process, thus degrading the timely CRLs distribution. In this paper, we propose a vehicle-centric solution that addresses all these challenges and thus closes a gap in the literature. Our scheme radically reduces CRL distribution overhead: each vehicle receives CRLs corresponding only to its region of operation and its actual trip duration. Moreover, a "fingerprint" of CRL 'pieces' is attached to a subset of (verifiable) pseudonyms for fast CRL 'piece' validation (while mitigating resource depletion attacks abusing the CRL distribution). Our experimental evaluation shows that our scheme is efficient, scalable, dependable, and practical: with no more than 25 KB/s of traffic load, the latest CRL can be delivered to 95% of the vehicles in a region (50x50 KM) within 15s, i.e., more than 40 times faster than the state-of-the-art. Overall, our scheme is a comprehensive solution that complements standards and can catalyze the deployment of secure and privacy-protecting VC systems.

The central building block of secure and privacy-preserving Vehicular Communication (VC) systems is a Vehicular Public-Key Infrastructure (VPKI), which provides vehicles with multiple anonymized credentials, termed pseudonyms. These pseudonyms are used to ensure message authenticity and integrity while preserving vehicle (and thus passenger) privacy. In the light of emerging large-scale multi-domain VC environments, the efficiency of the VPKI and, more broadly, its scalability are paramount. In this extended abstract, we leverage the state-of-the-art VPKI system and enhance its functionality towards a highly-available and dynamically-scalable design; this ensures that the system remains operational in the presence of benign failures or any resource depletion attack, and that it dynamically scales out, or possibly scales in, according to the requests' arrival rate. Our full-blown implementation on the Google Cloud Platform shows that deploying a VPKI for a large-scale scenario can be cost-effective, while efficiently issuing pseudonyms for the requesters.

Vehicular ad-hoc networks (VANETs) are designed to play a key role in the development of future transportation systems. Although cooperative awareness messages provide the required situational awareness for new safety and efficiency applications, they also introduce a new attack vector to compromise privacy. The use of ephemeral credentials called pseudonyms for privacy protection was proposed while ensuring the required security properties. In order to prevent an attacker from linking old to new pseudonyms, mix-zones provide a region in which vehicles can covertly change their signing material. In this poster, we extend the idea of mix-zones to mitigate pseudonym linking attacks with a mechanism inspired by chaff-based privacy defense techniques for mix-networks. By providing chaff trajectories, our system restores the efficacy of mix-zones to compensate for a lack of vehicles available to participate in the mixing procedure. Our simulation results of a realistic traffic scenario show that a significant improvement is possible.

Global Navigation Satellite Systems (GNSS) are vulnerable to jamming, spoofing and replaying attacks because of their characteristics. Concerns regarding these attacks are being heightened because unmanned and autonomous vehicles become popular recently. Cryptographic methods have been proposed and are to be implemented in the Galileo and the GPS systems to counter spoofing attacks. However, replaying attacks could still potentially harm GNSS receivers by bypassing the cryptographic methods. Distance-decreasing attacks is a strong type of replay attacks: it essentially resolves, from the attacker's point of view, the issue of introducing processing delay by implementing two phases: early detection and late commit. This poster analyzes the feasibility of distance-decreasing attacks against the GNSS navigation message authenticated signals and proposes countermeasures.

Several years of academic and industrial research efforts have converged to a common understanding on fundamental security building blocks for the upcoming vehicular communication (VC) systems. There is a growing consensus toward deploying a special-purpose identity and credential management infrastructure, i.e., a vehicular public-key infrastructure (VPKI), enabling pseudonymous authentication, with standardization efforts toward that direction. In spite of the progress made by standardization bodies (IEEE 1609.2 and ETSI) and harmonization efforts [Car2Car Communication Consortium (C2C-CC)], significant questions remain unanswered toward deploying a VPKI. Deep understanding of the VPKI, a central building block of secure and privacy-preserving VC systems, is still lacking. This paper contributes to the closing of this gap. We present SECMACE, a VPKI system, which is compatible with the IEEE 1609.2 and ETSI standards specifications. We provide a detailed description of our state-of-the-art VPKI that improves upon existing proposals in terms of security and privacy protection, and efficiency. SECMACE facilitates multi-domain operations in the VC systems and enhances user privacy, notably preventing linking pseudonyms based on timing information and offering increased protection even against honest-but-curious VPKI entities. We propose multiple policies for the vehicle-VPKI interactions and two large-scale mobility trace data sets, based on which we evaluate the full-blown implementation of SECMACE. With very little attention on the VPKI performance thus far, our results reveal that modest computing resources can support a large area of vehicles with very few delays and the most promising policy in terms of privacy protection can be supported with moderate overhead.

Location-based Services (LBSs) provide valuable features but can also reveal sensitive user information. Decentralized privacy protection removes the need for a so-called anonymizer, but relying on peers is a double-edged sword: adversaries could mislead with fictitious responses or even collude to compromise their peers' privacy. We address here exactly this problem: we strengthen the decentralized LBS privacy approach, securing peer-to-peer (P2P) interactions. Our scheme can provide precise timely P2P responses by passing proactively cached Point of Interest (POI) information. It reduces the exposure both to the honest-but-curious LBS servers and peer nodes. Our scheme allows P2P responses to be validated with very low fraction of queries affected even if a significant fraction of nodes are compromised. The exposure can be kept very low even if the LBS server or a large set of colluding curious nodes collude with curious identity management entities.

Security and privacy are important properties that have to be considered for the adoption of Vehicular Ad-hoc Networks (VANETs). Short-lived credentials, termed pseudonyms, are used to ensure message integrity and authentication while preserving vehicle (thus, their passengers') privacy. However, this introduces extra communication and computation overhead: pseudonyms have to be attached to the messages and signatures on pseudonyms and messages need to be verified before they can be accepted. In this poster, we are concerned with computation overhead for pseudonym validation. We preload vehicular On-Board Units (OBUs) with a Bloom Filter (BF) to facilitate pseudonym validation while traditional approach (i.e., signature verification on pseudonyms) can still be preserved as a fallback approach. We evaluate our scheme on automotive testbed with a preliminary implementation. Our scheme provides low processing delay for pseudonym validation at a cost of communication overhead for pre-downloading the BF.

We investigate large wireless networks subject to security constraints. In contrast to point-to-point, interference-limited communications considered in prior works, we propose active cooperative relaying-based schemes. We consider a network with nl legitimate nodes, ne eavesdroppers, and path loss exponent α ≥ 2. As long as ne2(log(ne))γ= o(nl), for some positive γ, we show that one can obtain unbounded secure aggregate rate. This means zero-cost secure communication, given fixed total power constraint for the entire network. We achieve this result through: 1) the source using Wyner randomized encoder and a serial (multi-stage) block Markov scheme, to cooperate with the relays and 2) the relays acting as a virtual multi-antenna to apply beamforming against the eavesdroppers. Our simpler parallel (two-stage) relaying scheme can achieve the same unbounded secure aggregate rate when neα/2+1(log(ne))γ +δ(α/2+1)= o(nl) holds, for some positive γ, δ. Finally, we study the improvement (to the detriment of legitimate nodes) that the eavesdroppers achieve in terms of the information leakage rate in a large cooperative network in the case of collusion. We show that again the zero-cost secure communication is possible, if ne(2+2/α)(log ne)γ= o(nl) holds, e for some positive γ; that is, in the case of collusion slightly fewer eavesdroppers can be tolerated compared with the non-colluding case.

There is already a significant body of work on security and privacy for vehicular communication systems and the conditions for deploying the technology are maturing. This tutorial provides a crystalized and easily accessible view of the state of the art.

We consider a secure communication scenario through the two-user Gaussian interference channel: each transmitter (user) has a confidential message to send reliably to its intended receiver while keeping it secret from the other receiver. Prior work investigated the performance of two different approaches for this scenario; i.i.d. Gaussian random codes and real alignment of structured codes. While the latter achieves the optimal sum secure degrees of freedom (s.d.o.f.), its extension to finite SNR regimes is challenging. In this paper, we propose a new achievability scheme for the weak and the moderately weak interference regimes, in which the reliability as well as the confidentiality of the transmitted messages are maintained at any finite SNR value. Our scheme uses lattice structure, structured jamming codewords, and lattice alignment in the encoding and the asymmetric compute-and-forward strategy in the decoding. We show that our lower bound on the sum secure rates scales linearly with log(SNR) and hence, it outperforms i.i.d. Gaussian random codes. Furthermore, we show that our achievable result is asymptotically optimal. Finally, we provide a discussion on an extension of our scheme to K > 2 users.

The zero-error secrecy capacity of uncertain wiretap channels is defined. If the sensor-estimator channel is perfect, it is also calculated. Further properties are discussed. The problem of estimating a dynamical system with nonstochastic disturbances is studied where the sensor is connected to the estimator and an eavesdropper via an uncertain wiretap channel. The estimator should obtain a uniformly bounded estimation error whereas the eavesdropper's error should tend to infinity. It is proved that the system can be estimated securely if the zero-error capacity of the sensor-estimator channel is strictly larger than the logarithm of the system's unstable pole and the zero-error secrecy capacity of the uncertain wiretap channel is positive.

Recent advances in sensing, computing, and networking have paved the way for the emerging paradigm of mobile crowd sensing (MCS). The openness of such systems and the richness of data MCS users are expected to contribute to them raise significant concerns for their security, privacy-preservation and resilience. Prior works addressed different aspects of the problem. But in order to reap the benefits of this new sensing paradigm, we need a holistic solution. That is, a secure and accountable MCS system that preserves user privacy, and enables the provision of incentives to the participants. At the same time, we are after an MCS architecture that is resilient to abusive users and guarantees privacy protection even against multiple misbehaving and intelligent MCS entities (servers). In this paper, we meet these challenges and propose a comprehensive security and privacy-preserving architecture. With a full blown implementation, on real mobile devices, and experimental evaluation we demonstrate our system's efficiency, practicality, and scalability. Last but not least, we formally assess the achieved security and privacy properties. Overall, our system offers strong security and privacy-preservation guarantees, thus, facilitating the deployment of trustworthy MCS applications.

The openness of PS systems renders them vulnerable to malicious users that can pollute the measurement collection process, in an attempt to degrade the PS system data and, overall, its usefulness. Mitigating such adversarial behavior is hard. Cryptographic protection, authentication, authorization, and access control can help but they do not fully address the problem. Reports from faulty insiders (participants with credentials) can target the process intelligently, forcing the PS system to deviate from the actual sensed phenomenon. Filtering out those faulty reports is challenging, with practically no prior knowledge on the participants' trustworthiness, dynamically changing phenomena, and possibly large numbers of compromised devices. This paper proposes SHIELD, a novel data verification framework for PS systems that can complement any security architecture. SHIELD handles available, contradicting evidence, classifies efficiently incoming reports, and effectively separates and rejects those that are faulty. As a result, the deemed correct data can accurately represent the sensed phenomena, even when 45% of the reports are faulty, intelligently selected by coordinated adversaries and targeted optimally across the system's coverage area.

Abstract A large number of random key pre‐distribution (RKD) schemes have been proposed in the literature to secure wireless sensor network applications, relying on symmetric key cryptography. However, sensor nodes are exposed to physical compromise by adversaries, who target the symmetric keys stored at each node. With the stolen keys in their possession, the adversaries are then able to compromise communication links between benign nodes. Here, the big challenge arises: how to increase resilience of RKD schemes for wireless sensor networks to node capture, while maintaining the flexibility and low‐cost features of RKD? We propose the idea of key splitting to address this problem, without the need of any special‐purpose hardware. Our key splitting scheme neither increases per‐node storage nor introduces additional computation and communication overheads. Nevertheless, it can achieve better connectivity. More importantly, it significantly increases resilience to node compromise, when the adversary does not have overwhelming computational power. Copyright © 2014 John Wiley & Sons, Ltd.

Increasing smartphone penetration, combined with the wide coverage of cellular infrastructures, renders smartphone-based traffic information systems (TISs) an attractive option. The main purpose of such systems is to alleviate traffic congestion that exists in every major city. Nevertheless, to reap the benefits of smartphone-based TISs, we need to ensure their security and privacy and their effectiveness (e.g., accuracy). This is the motivation of this paper: We leverage state-of-the-art cryptographic schemes and readily available telecommunication infrastructure. We present a comprehensive solution for smartphone-based traffic estimation that is proven to be secure and privacy preserving. We provide a full-blown implementation on actual smartphones, along with an extensive assessment of its accuracy and efficiency. Our results confirm that smartphone-based TISs can offer accurate traffic state estimation while being secure and privacy preserving.

We investigate large wireless networks subject to security constraints. In contrast to point-to-point, interference-limited communications considered in prior works, we propose active cooperative relaying based schemes. We consider a network with nllegitimate nodes and neeavesdroppers, and path loss exponent α ≥ 2. As long as ne2(log(ne))γ= o(nl) holds for some positive γ, we show one can obtain unbounded secure aggregate rate. This means zero-cost secure communication, given a fixed total power constraint for the entire network. We achieve this result with (i) the source using Wyner randomized encoder and a serial (multi-stage) block Markov scheme, to cooperate with the relays, and (ii) the relays acting as a virtual multi-antenna to apply beamforming against the eavesdroppers. Our simpler parallel (two-stage) relaying scheme can achieve the same unbounded secure aggregate rate when neα/2 + 1(log(ne))γ+δ(α/2+1)= o(nl) holds, for some positive γ, δ.

We investigate the problem of reliable communication in the presence of active adversaries that can tamper with the transmitted data. We consider a legitimate transmitter-receiver pair connected over multiple communication paths (routes). We propose two new models of adversary, a “memoryless” and a “foreseer” adversary. For both models, the adversaries are placing themselves arbitrarily on the routes, keeping their placement fixed throughout the transmission block. This placement may or may not be known to the transmitter. The adversaries can choose their best modification strategy to increase the error at the legitimate receiver, subject to a maximum distortion constraint. We investigate the communication rates that can be achieved in the presence of the two types of adversaries and the channel (benign) stochastic behavior. For memoryless adversaries, the capacity is derived. Our method is to use the typical set of the anticipated received signal for all possible adversarial strategies (including their best one) in a compound channel that also captures adversarial placement. For the foreseer adversaries, which have enhanced observation capabilities compared to the memoryless ones, we propose a new coding scheme to guarantee resilience, i.e., recovery of the codeword independently of the adversarial (best) choice. We derive an achievable rate and we propose an upper bound on the capacity. We evaluate our general results for specific cases (e.g., binary symbol replacement or erasing attacks), to gain insights.

Recent advances in sensing, computing, and networking have paved the way for the emerging paradigm of participatory sensing (PS). The openness of such systems and the richness of user data they entail raise significant concerns for their security, privacy and resilience. Prior works addressed different aspects of the problem. But in order to reap the benefits of this new sensing paradigm, we need a comprehensive solution. That is, a secure and accountable PS system that preserves user privacy, and enables the provision of incentives to the participants. At the same time, we are after a PS system that is resilient to abusive users and guarantees privacy protection even against multiple misbehaving PS entities (servers). We address these seemingly contradicting requirements with our SPPEAR architecture. Our full blown implementation and experimental evaluation demonstrate that SPPEAR is efficient, practical, and scalable. Last but not least, we formally assess the achieved security and privacy properties. Overall, our system is a comprehensive solution that significantly extends the state-of-the-art and can catalyze the deployment of PS applications.

Location-aware smartphones support various location-based services (LBSs): users query the LBS server and learn on the fly about their surroundings. However, such queries give away private information, enabling the LBS to track users. We address this problem by proposing a user-collaborative privacy-preserving approach for LBSs. Our solution does not require changing the LBS server architecture and does not assume third party servers; yet, it significantly improves users’ location privacy. The gain stems from the collaboration of mobile devices: they keep their context information in a buffer and pass it to others seeking such information. Thus, a user remains hidden from the server, unless all the collaborative peers in the vicinity lack the sought information. We evaluate our scheme against the Bayesian localization attacks that allow for strong adversaries who can incorporate prior knowledge in their attacks. We develop a novel epidemic model to capture the, possibly time-dependent, dynamics of information propagation among users. Used in the Bayesian inference framework, this model helps analyze the effects of various parameters, such as users’ querying rates and the lifetime of context information, on users’ location privacy. The results show that our scheme hides a high fraction of location-based queries, thus significantly enhancing users’ location privacy. Our simulations with real mobility traces corroborate our model-based findings. Finally, our implementation on mobile platforms indicates that it is lightweight and the cost of collaboration is negligible.

Intensive efforts in industry, academia and standardization bodies have brought vehicular communications (VC) one step before commercial deployment. In fact, future vehicles will become significant mobile platforms, extending the digital life of individuals with an ecosystem of applications and services. To secure these services and to protect the privacy of individuals, it is necessary to revisit and extend the vehicular Public Key Infrastructure (PKI)-based approach towards a multi-service security architecture. This is exactly what this work does, providing a design and a proof-of-concept implementation. Our approach, inspired by long-standing standards, is instantiated for a specific service, the provision of short-term credentials (pseudonyms). Moreover, we elaborate on its operation across multiple VC system domains, and craft a roadmap for further developments and extensions that leverage Web-based approaches. Our current results already indicate our architecture is efficient and can scale, and thus can meet the needs of the foreseen broad gamut of applications and services, including the transportation and safety ones.

We develop a formal framework for the analysis of security protocols in wireless networks. The framework captures characteristics necessary to reason about neighbor discovery protocols, such as the neighbor relation, device location, and message propagation time. We use this framework to establish general results about the possibility of neighbor discovery. In particular, we show that time-based protocols cannot in general provide secure neighbor discovery. Given this insight, we also use the framework to prove the security of four concrete neighbor discovery protocols, including two novel time-and-location-based protocols. We mechanize the model and some proofs in the theorem prover Isabelle.

A growing number of ad hoc networking protocols and location-aware services require that mobile nodes learn the position of their neighbors. However, such a process can be easily abused or disrupted by adversarial nodes. In absence of a priori trusted nodes, the discovery and verification of neighbor positions presents challenges that have been scarcely investigated in the literature. In this paper, we address this open issue by proposing a fully distributed cooperative solution that is robust against independent and colluding adversaries, and can be impaired only by an overwhelming presence of adversaries. Results show that our protocol can thwart more than 99 percent of the attacks under the best possible conditions for the adversaries, with minimal false positive rates.

Random key pre-distribution (RKPD) has been investigated for large wireless sensor networks, in order to achieve efficient security and robustness against limited node compromise. While it is possible that an adversary obtains a subset of the symmetric keys in use, it has been unclear how to use those to compromise specific secure links. We investigate how the adversary could do this practically. We term this the Stealthy Pre-Attack (SPA), because the adversarial nodes leverage benign behavior to guide their attack. The contribution of this paper is the identification of this adversarial behavior, the evaluation of its benefits for the attacker, which can then much more effectively compromise security, and the proposal of counter-measures to mitigate it.

A large number of Wireless Sensor Network (WSN) security schemes have been proposed in the literature, relying primarily on symmetric key cryptography. To enable those, Random Key pre-Distribution (RKD) systems have been widely accepted. However, WSN nodes are vulnerable to physical compromise. Capturing one or more nodes operating with RKD would give the adversary keys to compromise communication of other benign nodes. Thus the challenge is to enhance resilience of WSN to node capture, while maintaining the flexibility and low-cost features of RKD. We address this problem, without any special-purpose hardware, proposing a new and simple idea: key splitting. Our scheme does not increase per-node storage, and computation and communication overheads, and it can increase connectivity. More important, it achieves a significant increase in resilience to compromise compared to the state of the art, notably when the adversary does not have overwhelming computational power.

To provide high ranging precision in multipath environments, a ranging protocol should find the first arriving path, rather than the strongest path. We demonstrate a new attack vector that disrupts such precise Time-of-Arrival (ToA) estimation, and allows an adversary to decrease the measured distance by a value in the order of the channel spread (10-20 meters). This attack vector can be used in previously reported physical-communication-layer (PHY) attacks against secure ranging (or distance bounding). Furthermore, it creates a new type of attack based on malicious interference: This attack is much easier to mount than the previously known external PHY attack (distance-decreasing relay) and it can work even if secret preamble codes are used. We evaluate the effectiveness of this attack for a PHY that is particularly well suited for precise ranging in multipath environments: Impulse Radio Ultra-Wideband (IR-UWB). We show, with PHY simulations and experiments, that the attack is effective against a variety of receivers and modulation schemes. Furthermore, we identify and evaluate three types of countermeasures that allow for precise and secure ranging.

Unattended wireless sensor networks (WSNs) collect and store sensed data in the absence of a base station (sink). WSN data aggregation is a widely accepted approach to improve storage and communication efficiency. But the vulnerability of low-cost WSN nodes to compromise makes the use of secure protocols mandatory. As most secure data aggregation algorithms use the base station as a trust anchor, unattended WSNs need new solutions for secure data aggregation. We address exactly this problem, proposing a new resilient data aggregation scheme that protects data integrity and remains robust to a wide range of attacks, integrating Quality-of-Information (Qol) as a defense mechanism. We argue that a Qol metric accompanying every aggregation result is necessary for the WSN user, to assess the quality of obtained data and detect errors or attacks. Even with a significant fraction of the WSN nodes controlled by the attacker, our scheme identifies and mitigates the effect of the attacks. This is supported by our analysis, with simulations of realistic strong attacks. The practicality of our scheme is supported by our proof of concept implementation.

Location-aware smart phones support various location-based services (LBSs): users query the LBS server and learn on the fly about their surroundings. However, such queries give away private information, enabling the LBS to identify and track users. We address this problem by proposing the first, to the best of our knowledge, user-collaborative privacy preserving approach for LBSs. Our solution, MobiCrowd, is simple to implement, it does not require changing the LBS server architecture, and it does not assume third party privacy-protection servers; still, MobiCrowd significantly improves user location-privacy. The gain stems from the collaboration of MobiCrowd-ready mobile devices: they keep their context information in a buffer, until it expires, and they pass it to other users seeking such information. Essentially, the LBS does not need to be contacted unless all the collaborative peers in the vicinity lack the sought information. Hence, the user can remain hidden from the server, unless it absolutely needs to expose herself through a query. Our results show that MobiCrowd hides a high fraction of location-based queries, thus significantly enhancing user location-privacy. To study the effects of various parameters, such as the collaboration level and contact rate between mobile users, we develop an epidemic model. Our simulations with real mobility datasets corroborate our model-based findings. Finally, our implementation of MobiCrowd on Nokia platforms indicates that it is lightweight and the collaboration cost is negligible.

Vehicular communication (VC) systems are being developed primarily to enhance transportation safety and efficiency. Vehicle-to-vehicle communication, in particular, frequent cooperative awareness messages or safety beacons, has been considered over the past years as a main approach. Meanwhile, the need to provide security and to safeguard users' privacy is well understood, and security architectures for VC systems have been proposed. Although technical approaches to secure VC have several commonalities and a consensus has formed, there are critical questions that have remained largely unanswered: Are the proposed security and privacy schemes practical? Can the secured VC systems support the VC-enabled applications as effectively as unsecured VC would? How should security be designed so that its integration into a VC system has a limited effect on the system's performance? In this paper, we provide answers to these questions, investigating the joint effect of a set of system parameters and components. We consider the state-of-the-art approach in secure VC, and we evaluate analytically and through simulations the interdependencies among components and system characteristics. Overall, we identify key design choices for the deployment of efficient, effective, and secure VC systems.

Impulse Radio Ultra-Wideband, in particular the recent standard IEEE 802.15.4a, is a primary candidate for implementing distance bounding protocols, thanks to its ability to perform accurate indoor ranging. Distance bounding protocols allow two wireless devices to securely estimate the distance between themselves, with the guarantee that the estimate is an upper-bound on the actual distance. These protocols serve as building blocks in security-sensitive applications such as tracking, physical access control, or localization. We investigate the resilience of IEEE 802.15.4a to physical-communication-layer attacks that decrease the distance measured by distance bounding protocols, thus violating their security. We consider two attack types: malicious prover (internal) and distance-decreasing relay (external). We show that if the honest devices use energy-detection receivers (popular due to their low cost and complexity), then an adversary can perform highly effective internal and external attacks, decreasing the distance by hundreds of meters. However, by using more sophisticated rake receivers, or by implementing small modifications to IEEE 802.15.4a and employing energy-detection receivers with a simple countermeasure, honest devices can reduce the effectiveness of external distance-decreasing relay attacks to the order of 10m. The same is true for malicious prover attacks, provided that an additional modification to IEEE 802.15.4a is implemented.

Wireless ad hoc networks are inherently vulnerable, as any node can disrupt the communication of potentially any other node in the network. Many solutions to this problem have been proposed. In this paper, we take a fresh and comprehensive approach that addresses simultaneously three aspects: security, scalability and adaptability to changing network conditions. Our communication protocol, Castor, occupies a unique point in the design space: it does not use any control messages except simple packet acknowledgments, and each node makes routing decisions locally and independently without exchanging any routing state with other nodes. Its novel design makes Castor resilient to a wide range of attacks and allows the protocol to scale to large network sizes and to remain efficient under high mobility. We compare Castor against four representative protocols from the literature. Our protocol achieves up to two times higher packet delivery rates, particularly in large and highly volatile networks, while incurring no or only limited additional overhead. At the same time, Castor is able to survive more severe attacks and recovers from them faster.

We expose the vulnerability of an emerging wireless ranging technology, impulse radio ultra-wide band (IR-UWB), to distance-decreasing attacks on the physical communication layer (PHY). These attacks violate the security of secure ranging protocols that allow two wireless devices to securely estimate the distance between them, with the guarantee that the estimate is an upper-bound on the actual distance. Such protocols serve as crucial building blocks in security-sensitive applications such as location tracking, physical access control, or localization.

Due to their limited capabilities, wireless sensor nodes are subject to physical attacks that are hard to defend against. In this paper, we first identify a typical attacker, called parasitic adversary, who seeks to exploit sensor networks by obtaining measurements in an unauthorized way. As a countermeasure, we first employ a randomized key refreshing: with low communication cost, it aims at confining (but not eliminating) the effects of the adversary. Moreover, our low-complexity solution, GossiCrypt, leverages on the large scale of sensor networks to protect data confidentiality, efficiently and effectively. GossiCrypt applies symmetric key encryption to data at their source nodes; and it applies re-encryption at a randomly chosen subset of nodes en route to the sink. The combination of randomized key refreshing and GossiCrypt protects data confidentiality with a probability of almost 1; we show this analytically and with simulations. In addition, the energy consumption of GossiCrypt is lower than a public-key based solution by several orders of magnitude.

Wireless networking relies on a fundamental building block, neighbor discovery (ND). The nature of wireless communications, however, makes attacks against ND easy: An adversary can simply replay or relay (wormhole) packets across the network and mislead disconnected nodes into believing that they communicate directly. Such attacks can compromise the overlying protocols and applications. Proposed methods in the literature seek to secure ND, allowing nodes to verify they are neighbors. However, they either rely on specialized hardware or infrastructure, or offer limited security. In this paper, we address these problems, designing a practical and secure neighbor verification protocol for constrained Wireless Sensor networks (WSNs). Our scheme relies on estimated distance between nodes and simple geometric tests, and it is fully distributed. We prove our protocol is secure against the classic 2-end wormhole attack. Moreover, we provide a proof-of-concept implementation with off-the-shelf WSN equipment: Cricket motes.

Wireless communication enables a broad spectrum of applications, ranging from commodity to tactical systems. Neighbor discovery (ND), that is, determining which devices are within direct radio communication, is a building block of network protocols and applications, and its vulnerability can severely compromise their functionalities. A number of proposals to secure ND have been published, but none have analyzed the problem formally. In this paper, we contribute such an analysis: We build a formal model capturing salient characteristics of wireless systems, most notably obstacles and interference, and we provide a specification of a basic variant of the ND problem. Then, we derive an impossibility result for a general class of protocols we term "time-based protocols," to which many of the schemes in the literature belong. We also identify the conditions under which the impossibility result is lifted. Moreover, we explore a second class of protocols we term "time- and location-based protocols," and prove they can secure ND.

We argue that the traditional notion of trust as a relation among entities, while useful, becomes insufficient for emerging data-centric mobile ad hoc networks. In these systems, setting the data trust level equal to the trust level of the data- providing entity would ignore system salient features, rendering applications ineffective and systems inflexible. This would be even more so if their operation is ephemeral, i.e., characterized by short-lived associations in volatile environments. In this paper, we address this challenge by extending the traditional notion of trust to data-centric trust: trustworthiness attributed to node-reported data per se. We propose a framework for data-centric trust establishment: First, trust in each individual piece of data is computed; then multiple, related but possibly contradictory, data are combined; finally, their validity is inferred by a decision component based on one of several evidence evaluation techniques. We consider and evaluate an instantiation of our framework in vehicular networks as a case study. Our simulation results show that our scheme is highly resilient to attackers and converges stably to the correct decision.

Resource and cost constraints remain a challenge for wireless sensor network security. In this paper, we propose a new approach to protect confidentiality against a parasitic adversary, which seeks to exploit sensor networks by obtaining measurements in an unauthorized way. Our low-complexity solution, GossiCrypt, leverages on the large scale of sensor networks to protect confidentiality efficiently and effectively. GossiCrypt protects data by symmetric key encryption at their source nodes and re-encryption at a randomly chosen subset of nodes en route to the sink. Furthermore, it employs key refreshing to mitigate the physical compromise of cryptographic keys. We validate GossiCrypt analytically and with simulations, showing it protects data confidentiality with probability almost one. Moreover, compared with a system that uses public-key data encryption, the energy consumption of GossiCrypt is tens to thousands of times lower.

Vehicular networks, in which cars communicate wirelessly to exchange information on traffic conditions, offer a promising way to improve road safety. Yet ensuring the correct functioning of such a system is essential: malicious or faulty devices transmitting inaccurate messages could trigger accidents. Therefore, any errant device, along with the messages it generates, must be identified and ignored as quickly as possible. This task is especially challenging because traditional approaches to revoking credentials use a central authority, causing long delays during which the network is vulnerable. To eliminate this window of vulnerability, we propose that vehicles locally decide whether to exclude errant devices. We describe two ways of doing so: first, LEAVE, an existing protocol which allows devices to vote by exchanging signed claims of impropriety, and second, Stinger, a new protocol where a device unilaterally removes a misbehaving neighbor by agreeing to limit its own participation. We provide detailed simulations that offer insight into the protocols' operations in the context of vehicular networks and enable a powerful comparison between the strategies. We compare the security and performance properties of LEAVE and Stinger while varying attacker capabilities, traffic conditions, and the accuracy of the misbehavior detection mechanisms. We identify several interesting trade-offs: Stinger is significantly faster than LEAVE at removing errant devices, but LEAVE excludes fewer good devices when the attacker has compromised several devices simultaneously; LEAVE is better at handling false positives, but Stinger scales better when the traffic density increases. As a result, we conclude by outlining a combined protocol that balances the security and performance characteristics of both strategies.

With a number of projects developing vehicular communication systems, there is rising awareness on threats and the need to introduce security and privacy-enhancing mechanisms. With recent results, in principle in agreement across different major projects, there has been little work on implementation and demonstration of security and privacy-enhancing mechanisms. The contribution of this work is exactly in this direction: we present a demonstration of our system, comprising a range of mechanisms, developed to secure vehicular communications (VC) and enhance the location privacy of the users of VC systems.

The privacy of users of mobile devices has been at stake, with emerging systems based on the mobile ad hoc networking technology raising additional concerns. The establishment of a connection between two nodes could readily reveal information to an eavesdropper. One approach to prevent this is to provide receiver anonymity, i.e., conceal the identity of the receiver, during the establishment of a communication path. In this paper, we introduce such a scheme that improves the efficiency of anonymous discovery, balances its cost among network nodes, and can be adaptive, trading off the degree of anonymity for the receiver.

Vehicular communication (VC) systems have the potential to improve road safety and driving comfort. Nevertheless, securing the operation is a prerequisite for deployment. So far, the security of VC applications has mostly drawn the attention of research efforts, while comprehensive solutions to protect the network operation have not been developed. In this paper, we address this problem: we provide a scheme that secures geographic position-based routing, which has been widely accepted as the appropriate one for VC. Moreover, we focus on the scheme currently chosen and evaluated in theCar2CarCommunicationConsortium(C2C-CC). We integrate security mechanisms to protect the position-based routing functionality and services (beaconing, multi-hop forwarding, and geo-location discovery), and enhance the network robustness. We propose defense mechanisms, relying both on cryptographic primitives and plausibility checks mitigating false position injection. Our implementation and initial measurements show that the security overhead is low and the proposed scheme deployable.

Vehicular networks (VNs) are emerging, among civilian applications, as a convincing instantiation of the mobile networking technology. However, security is a critical factor and a significant challenge to be met. Misbehaving or faulty network nodes have to be detected and prevented from disrupting network operation, a problem particularly hard to address in the life-critical VN environment. Existing networks rely mainly on node certificate revocation for attacker eviction, but the lack of an omnipresent infrastructure in VNs may unacceptably delay the retrieval of the most recent and relevant revocation information; this will especially be the case in the early deployment stages of such a highly volatile and large-scale system. In this paper, we address this specific problem. We propose protocols, as components of a framework, for the identification and local containment of misbehaving or faulty nodes, and then for their eviction from the system. We tailor our design to the VN characteristics and analyze our system. Our results show that the distributed approach to contain nodes and contribute to their eviction is efficiently feasible and achieves a sufficient level of robustness.

Secure routing protocols for mobile ad hoc networks have been developed recently, yet, it has been unclear what are the properties they achieve, as a formal analysis of these protocols is mostly lacking. In this paper, we are concerned with this problem, how to specify and how to prove the correctness of a secure routing protocol. We provide a definition of what a protocol is expected to achieve independently of its functionality, as well as a communication and adversary models. This way, we enable formal reasoning on the correctness of secure routing protocols. We demonstrate this by analyzing two protocols from the literature.

The ad hoc networking technology can enable novel civilian and military applications. However, ad hoc networking protocols are vulnerable to a wide range of attacks. The design of defense mechanisms is a challenging problem, especially in comparison to securing traditional, fixed-infrastructure networks. In this paper, we discuss challenges and guidelines to secure ad hoc networking protocols, and describe a protocol suite for secure and fault-tolerant communication.

In this paper we propose a cross-layer design for IEEE 802.15.4 MAC protocol that is based on a distributed backoff strategy governed by the wireless link quality measurements which are part of the standard. Our performance evaluation indicates that our scheme is more effective, achieving up to 69% higher goodput, and more efficient, delivering up to 154% more data bits per unit of energy consumed in the network, at the expense of an up to 18% degradation in fairness, compared to the basic 802.15.4.

We address the problem of secure and fault-tolerant communication in the presence of adversaries across a multihop wireless network with frequently changing topology. To effectively cope with arbitrary malicious disruption of data transmissions, we propose and evaluate the secure message transmission (SMT) protocol and its alternative, the secure single-path (SSP) protocol. Among the salient features of SMT and SSP is their ability to operate solely in an end-to-end manner and without restrictive assumptions on the network trust and security associations. As a result, the protocols are applicable to a wide range of network architectures. We demonstrate that highly reliable communication can be sustained with small delay and small delay variability, even when a substantial portion of the network nodes systematically or intermittently disrupt communication. SMT and SSP robustly detect transmission failures and continuously configure their operation to avoid and tolerate data loss, and to ensure the availability of communication. This is achieved at the expense of moderate transmission and routing overhead, which can be traded off for delay. Overall, the ability of the protocols to mitigate both malicious and benign faults allows fast and reliable data transport even in highly adverse network environments.

Topological changes in mobile ad hoc networks frequently render routing paths unusable. Such recurrent path failures have detrimental effects on the network ability to support QoS-driven services. A promising technique for addressing this problem is to use multiple redundant paths between the source and the destination. However while multipath routing algorithms can tolerate network failures well their failure resilience only holds if the paths are selected judiciously. In particular the correlation between the failures of the paths in a redundant path set should be as small as possible. However selecting an optimal path set is an NP-complete problem. Heuristic solutions proposed in the literature are either too complex to be performed in real-time or too ineffective or both. This paper proposes a multipath routing algorithm called Disjoint Pathset Selection Protocol (DPSP) based on a novel heuristic that in nearly linear time on average picks a set of highly reliable paths. The convergence to a highly reliable path set is very fast and the protocol provides flexibility in path selection and routing algorithm. Furthermore DPSP is suitable for real-time execution with nearly no message exchange overhead and with minimal additional storage requirements. This paper presents evidence that multipath routing can mask a substantial number of failures in the network compared to single path routing protocols and that the selection of paths according to DPSP can be beneficial for mobile ad hoc networks since it dramatically reduces the rate of route discoveries.