Deepfakes are a type of synthetic media created using artificial intelligence, specifically deep learning algorithms. This technology can for example superimpose faces and voices onto videos, creating hyper-realistic but artificial representations. Deepfakes pose significant risks regarding misinformation and fake news, because they can spread false information by depicting public figures saying or doing things they never did, undermining public trust. In this paper, we propose a method that leverages BLS signatures (Boneh, Lynn, and Shacham 2004) to implement signatures that remain valid after image cropping, but are invalidated in all the other types of manipulation, including deepfake creation. Our approach does not require who crops the image to know the signature private key or to be trusted in general, and it is ${\mathcal{O}}(1)$ in terms of signature size, making it a practical solution for scenarios where images are disseminated through web servers and cropping is the primary transformation. Finally, we adapted the signature scheme for the JPEG standard, and we experimentally tested the size of a signed image.

Attribute-Based Encryption (ABE) has been proposed to ensure the confidentiality of over-the-air (OTA) software updates in the automotive sector. Existing schemes predominantly rely on pairing-based cryptography, which is vulnerable to quantum computing attacks. This paper explores an ABE scheme based on Ring Learning with Errors (RLWE), a quantum-resistant cryptographic primitive. We implement a prototype on an embedded platform to assess the scheme's performance in terms of processing time and memory usage on the vehicle side. Results indicate that the RLWE-based ABE scheme can be efficiently integrated into OTA update frameworks with minimal performance overhead.

This paper presents an enhanced edge-cloud service-continuity platform that integrates advanced Transport Layer Security (TLS) 1.3 features to address performance and security challenges in dynamic smart environments such as smart cities and logistics. Building on a previously proposed proxy-based architecture, we incorporate two key TLS mechanisms: hybrid post-quantum key exchange using X25519MLKEM768 to mitigate Store Now Decrypt Later (SNDL) attacks, and stateless session resumption for fast handover across edge proxies. Our open-source implementation relies on Envoy proxies and BoringSSL library. We evaluate the cryptographic, data, and latency overheads across multiple network conditions. Results show that hybrid post-quantum TLS introduces manageable overheads while significantly enhancing security, and that session resumption reduces connection costs by up to 73%. These findings confirm the viability of strong cryptographic protections without sacrificing service performance, making the solution suitable for secure, seamless continuity in smart city edge computing scenarios.

Purpose Information security awareness (ISA) mainly refers to those aspects that need to be addressed to effectively respond to information security challenges. This research used focus groups to empirically investigate the main ISA dimensions that emerge from the Italian public health-care sector. This study aims to identify the most critical dimension of ISA and to evaluate the diffusion and maturity of information security policies (ISPs) of health-care infrastructure and training programs. Design/methodology/approach This research adopted a qualitative research design and focus groups as a research methodology. Data analysis was conducted using the NVIVO 14 software package and followed the principles of thematic analysis. Findings The focus group results highlighted that health-care personnel find it difficult to comply with the main ISA dimensions, a situation that leads to risky behaviors. Password management, data storage and transfer and instant messaging applications emerged as the most critical of the main ISA dimensions in the context of this research. It also transpired that ISPs are not all-encompassing as they mainly focus on privacy problems but neglect security concerns. Finally, training programs are not fully implemented in the investigated context, thus undermining their positive enhancing role for ISA. Originality/value The public health-care sector emerged as a critical yet still under-investigated context. The need for an in-depth investigation of organizational sciences approaches to overcoming information security challenges is also recommended in several prior research studies.

Fully Homomorphic Encryption (FHE) is a key technological enabler for secure computations as it allows a third-party to perform arbitrary computations on encrypted data learning neither the input nor the results of a computation. Notwithstanding the recent theoretical breakthroughs in FHE, building a secure and efficient FHE-based application is still a challenging engineering task where optimal choices are heavily application-dependent.

Cyber-Physical Systems (CPSs) are a large class of systems characterized by networked co-operating sub-systems, that perceive surrounding environment via sensors and actuators. Cybersecurity is relevant in CPSs because, on the one hand, these systems expose a wide cyber-attack surface while, on the other hand, a security infringement may translate into a safety infringement. This work presents a methodology for developing an intrusion detection system for CPSs based on neural networks. The methodology exploits a digital twin of the CPS to generate traces of executions. An instrumented approach is used to extend the digital twin model by introducing functions that simulate the effects of various class of attacks on the system. The instrumented digital twin is used to gather data of the system’s behaviour with and without attacks. Collected data are used for training the neural network. To illustrate the methodology we consider a case-study featuring an Adaptive Cruise Control System in autonomously driving vehicles. A Multi-Layer Perceptron neural network is trained to detect attacks to sensors. Results show an high accuracy in detecting attacks.

The Internet of Things (IoT) is an information service paradigm based on the integration of smart objects, mobile devices, and computers via the Internet. IoT technologies are key enablers for a multitude of applications in diverse fields, such as digital health, smart city, industrial automation, and supply chain. This raises new security and privacy challenges that can be addressed by advanced cryptographic methods. One of the most prominent is attribute-based encryption (ABE), which allows one to encrypt data while enforcing fine-grained access control on it. ABE is advantageous in many IoT applications since it allows data to be safely stored on untrusted storage, such as third-party cloud servers, hackable publish-subscribe brokers, physically accessible sensors, etc. This article surveys the ABE literature proposing schemes and solutions that are best suited for IoT applications. To do so, it first identifies three performance indicators that are key in IoT, namely, the data producer CPU efficiency, the data producer bandwidth efficiency, and the key authority bandwidth efficiency. Then, it analyzes only those schemes that are promising from the point of view of one or more indicators and, therefore, more applicable in typical IoT applications. As a further contribution, this article selects a subset of representative schemes and assesses their efficiency by thorough simulations. Such simulations show that no scheme excels in all three performance indicators at once, but some simultaneously perform well in two indicators.

Lately, many cloud-based applications proposed attribute-based encryption (ABE) as an all-in-one solution for achieving confidentiality and access control. Within this paradigm, data producers store the encrypted data on a semi-trusted cloud server, and users, holding decryption keys issued by a key authority, can decrypt data according to some access control policy. To be used in practical cases, any ABE scheme should implement a key revocation mechanism which assures that a compromised decryption key cannot be used anymore to decrypt data. Yuet al.(2010) introduced an ABE scheme with revocation capabilities that enjoys several unique advantages, such as reactivity and efficiency. In the scheme, the cloud server is entitled to update keys and ciphertexts in order to achieve revocation. Unfortunately, the cloud server retains the power to undo the revocation of a key (revocation undoing attack) so endangering confidentiality. In this article, we propose a revocable ABE scheme that still ensures the advantages of Yuet al.’s scheme, but it also resists to the revocation undoing attack. We formally prove the security of our scheme and show through simulations that the user experiences a slightly higher computational cost with respect to Yuet al.’s scheme.

Bitcoin-based smart city services are an ever increasing up-and-coming reality. For these services, simulating the Bitcoin blockchain is important to parametrize the system and tailor the costs and the economic incentives. In this regard, SimBlock simulator is the current state-of-the-art tool for blockchain simulations. Unfortunately, based on an up-to-date parametrization, SimBlock turns out not to simulate the mining of blocks. Furthermore, it does not simulate the incentive mechanism. These limitations strongly confine SimBlock's effective usage towards evaluating Bitcoin-based services relevant to many application contexts, including smart cities. To overcome these limitations, we propose an improved SimBlock's implementation. Upon it, we assess whether SimBlock can abstract the current Bitcoin blockchain. The experimental analysis shows that the proposed implementation can effectively simulate the current Bitcoin blockchain. Though, introducing relay network modelling in SimBlock should even improve the accuracy of the simulation.

Over- The-Air (OTA) update is an innovative paradigm that is rapidly spreading through the automotive industry. Software updates can be capillary distributed thanks to the many Vehicle-to-Everything (V2X) communication infrastructures that are part of a Smart City. Unfortunately, the majority of the existing OTA frameworks and schemes are not quantum resistant, meaning that when quantum computing will become reality, they will not be secure anymore. The U.S. National Institute of Standards and Technology (NIST) has announced a contest to determine the post-quantum standards for digital signatures schemes. In this paper, we evaluate the performance of the digital signature verification algorithms of two out of the three finalists for the NIST contest, namely FALCON and CRYSTALS-DILITHIUM. These algorithms are tested on automotive-oriented evaluation board, namely the Xilinx Zynq Ultrascale+ ZCU102. The results show that FALCON is a more promising algorithm compared to DILITHIUM both regarding signature verification execution time and signature size.

This paper describes the SAPIENT system, a real-time monitoring and control infrastructure for Air Traffic Management. Within the latter, aircrafts constantly measure the state and quality of their datalinks, and report these measurements to a ground entity, tagging them with a time/space reference. The ground entity, then, builds a map of the monitored portion of the sky, and can feed back information to the aircrafts themselves regarding conditions that they would not be able to measure otherwise. This allows optimal vertical handover decisions to be made, increasing service continuity and improving communication performance. We show that the SAPIENT system can be implemented using existing technologies, without the need for expensive hardware. Moreover, we show via simulation that a small, negligible increase in the communication overhead due to SAPIENT reporting brings about considerable benefits.

Wireless Sensor Networks (WSNs) are particularly prone to security attacks. However, it is well-known that perfect security is not achievable. Therefore, it is important to identify threats and evaluate their severity, for prioritizing the security countermeasures to be adopted, even since design time. In this work, we propose an approach that binds formal methods and network simulation for assessing the effects of security attacks on WSN applications from design time, starting from the abstract model of the system. Formal methods make it possible to build abstract system models and state properties of general validity, but cannot provide any concrete measurement regarding the network and the application. On the other hand, network simulators can provide precise and realistic information about simulated scenarios only. As a proof of concept, we design and prototype an application-level communication protocol, which is simulated both on attack free and attack scenarios. First, the protocol's formal properties are specified and proved via UPPAAL. Then, the resulting UPPAAL model is used to automatically generate a network model for the WSN simulator Castalia. Finally, the network model is simulated against attack free and attack scenarios, for gathering realistic information about the protocol behavior and performance.

Distributed ledgers allow us to replicate databases of records across mutually untrusted parties. The best known example of distributed ledger is perhaps the Bitcoin blockchain, which maintains a consistent history of financial transactions organized as a hashed chain of blocks. Distributed ledgers can be public, i.e., accessible by everyone, or private, i.e., accessible only by a given consortium of parties. In this paper, we explore the technological possibilities of applying Identity-Based Encryption and Attribute-Based Encryption to distributed ledgers. We introduce the novel concept of Virtual Private Ledger. A Virtual Private Ledger is a private distributed ledger embedded in a public cryptocurrency ledger by means of cryptography. A Virtual Private Ledger provides for the same confidentiality and integrity of a private distributed ledger, but without its high operational costs. In particular, nodes that maintain the ledger do not have to be always online to trust the order and the integrity of the records. We analytically show that Virtual Private Ledgers can be implemented over many existing cryptocurrency ledgers like Ethereum, EOS.IO, IOTA, XRP. Different cryptocurrencies lead to different trade-offs between the Virtual Private Ledger max record size, cost, validation time, and max consortium members.

Urban population is expected to continuously grow in size. The smart city concepts allows to handle the new challenges and issues created by this growth by applying a wide range of technologies that can provide citizens with a better living environment. Smart agriculture will play an important part of smart cities, as a sustainable and high quality food supply chain is crucial to facilitate the grow of human agglomerates. In this context, European laws imposes very strict requirements in the food industry, in order to ensure that food provenance is always guaranteed. Such fine-grained traceability can be only achieved by applying state-of-the-art technologies. In this paper, we present BRUSCHETTA, a blockchain-based application for the traceability and the certification of the Extra Virgin Olive Oil (EVOO) supply chain. EVOO is an emblematic food product for Italy, but it is also one of the most falsified ones. BRUSCHETTA provides a blockchain-based system to enforce the certification of this product by tracing its entire supply chain: from the plantation to the shops. The goal is to enable the final customer to access a tamper-proof history of the product, including the farming, harvesting, production, packaging, conservation, and transportation processes. BRUSCHETTA leverages Internet of Things (IoT) technologies in order to interconnect sensors dedicated to EVOO quality control, and to let them operate on the blockchain. We also provide a support for the correct tailoring of the BRUSCHETTA blockchain system, and we propose a mechanism for its dynamic auto-tuning to optimize it in case of high loads.

The Internet of Things (IoT) is enabling a new generation of innovative services based on the seamless integration of smart objects into information systems. Such IoT devices generate an uninterrupted flow of information that can be transmitted through an untrusted network and stored on an untrusted infrastructure. The latter raises new security and privacy challenges that require novel cryptographic methods. Attribute-Based Encryption (ABE) is a new type of public-key encryption that enforces a fine-grained access control on encrypted data based on flexible access policies. The feasibility of ABE adoption in fully-fledged computing systems, i.e. smartphones or embedded systems, has been demonstrated in recent works. In this paper we assess the feasibility of the adoption of ABE in typical IoT constrained devices, characterized by limited capabilities in terms of computing, storage and power. Specifically, an implementation of three ABE schemes for ESP32, a low-cost popular platform to deploy IoT devices, is developed and evaluated in terms of encryption/decryption time and energy consumption. The performance evaluation shows that the adoption of ABE on constrained devices is feasible, although it has a cost that increases with the number of attributes. The analysis in particular highlights how ABE has a significant impact in the lifetime of battery-powered devices, which is impaired significantly when a high number of attributes is adopted.

The Internet of Things (IoT) is a technological vision in which constrained or embedded devices connect together through the Internet. This enables common objects to be empowered with communication and cooperation capabilities. Industry can take an enormous advantage of IoT, leading to the so-called Industrial IoT. In these systems, integrity, confidentiality, and access control over data are key requirements. An emerging approach to reach confidentiality and access control is Attribute-Based Encryption (ABE), which is a technique able to enforce cryptographically an access control over data. In this paper, we propose fABElous, an ABE scheme suitable for Industrial IoT applications which aims at minimizing the overhead of encryption on communication. fABElous ensures data integrity, confidentiality, and access control, while reducing the communication overhead of 35% with respect to using ABE techniques naively.

The MAC standard amendment IEEE 802.15.4e is designed to meet the requirements of industrial and critical applications. In particular, the Time Slotted Channel Hopping (TSCH) mode divides time into periodic, equally sized, slotframes composed of transmission timeslots. Then, it combines time slotted access with multichannel and channel hopping capabilities, providing large network capacity, high reliability, and predictable latency while ensuring energy efficiency. Since every network node considers the same timeslots at each slotframe and selects physical channels according to a periodic function, TSCH produces a steady channel utilization pattern. This can be exploited by a selective jammer to entirely thwart communications of a victim node in a way that is stealthy, effective, and extremely energy efficient. This article shows how a selective jamming attack can be successfully performed even though TSCH uses the IEEE 802.15.4e security services. Furthermore, we propose DISH, a countermeasure which randomly permutes the timeslot and channel utilization patterns at every slotframe in a consistent and completely distributed way without requiring any additional message exchange. We have implemented DISH for the Contiki OS and tested its effectiveness on TelosB sensor nodes. Quantitative analysis for different network configurations shows that DISH effectively contrasts selective jamming with negligible performance penalty.

In the near future, a technological revolution will involve our cities, where a variety of smart services based on the Internet of Things will be developed to facilitate the needs of the citizens. Sensing devices are already being deployed in urban environments, and they will generate huge amounts of data. Such data are typically outsourced to some cloud storage because this lowers capital and operating expenses and guarantees high availability. However, cloud storage may have incentives to release stored data to unauthorized entities. In this work we present ABE-Cities, an encryption scheme for urban sensing which solves the above problems while ensuring fine-grained access control on data by means of Attribute-Based Encryption (ABE). Basically, ABE-Cities encrypts data before storing it in the cloud and provides users with keys able to decrypt only those portions of data the user is authorized to access. In ABE-Cities, the sensing devices perform only lightweight symmetric cryptography operations, thus they can also be resource-constrained. ABE-Cities provides planned expiration of keys, as well as their unplanned revocation. We propose methods to make the key revocation efficient, and we show by simulations the overall efficiency of ABE-Cities.

Android users are constantly threatened by an increasing number of malicious applications (apps), generically called malware. Malware constitutes a serious threat to user privacy, money, device and file integrity. In this paper we note that, by studying their actions, we can classify malware into a small number of behavioral classes, each of which performs a limited set of misbehaviors that characterize them. These misbehaviors can be defined by monitoring features belonging to different Android levels. In this paper we present MADAM, a novel host-based malware detection system for Android devices which simultaneously analyzes and correlates features at four levels: kernel, application, user and package, to detect and stop malicious behaviors. MADAM has been specifically designed to take into account those behaviors that are characteristics of almost every real malware which can be found in the wild. MADAM detects and effectively blocks more than 96 percent of malicious apps, which come from three large datasets with about 2,800 apps, by exploiting the cooperation of two parallel classifiers and a behavioral signature-based detector. Extensive experiments, which also includes the analysis of a testbed of 9,804 genuine apps, have been conducted to show the low false alarm rate, the negligible performance overhead and limited battery consumption.

The capability to verify positions reported by devices is called secure location verification. The majority of the proposed solutions entail the use of many fixed anchors often along with special hardware, e.g., ultra-wideband and ultrasonic transceivers. However, the deployment and maintenance costs of such solutions make them scarcely attractive. A cheaper alternative is to use mobile entities as trusted infrastructure. In particular, Unmanned Aerial Vehicles (UAVs) represent a promising approach. Indeed, recent studies used them to face the secure location verification problem. In this paper, we introduce a low-cost approach based on a swarm of UAVs and a common radio frequency protocol, e.g., WiFi. By experimental simulations, we show that by using only three UAVs our system detects more than 99% of the attacks against an adversary that falsifies its position of at least 20 m. We also consider an adversary capable of tracking UAVs positions. The success probability of such an advanced adversary is smaller than 1% starting from a falsification distance larger than 35m.

This paper presents a method to check data secure flow in security annotated AUTOSAR models. The approach is based on information flow analysis and abstract interpretation. The analysis computes the lowest security level of data sent on a communication, according to the annotations in the model and the code of runnables. An abstract interpreter executes runnables on abstract domains that abstract from real values and consider only data dependency levels. Data secure flow is verified if data sent on a communication always satisfy the security annotation in the model. The work has been developed in the EU project Safure, where modeling extensions to AUTOSAR have been proposed to improve security in automotive communications.

The increasing diffusion of smart devices opens to a new era for collecting large quantities of data from urban areas. Sensing information can be collected by using existing network infrastructures, but also by adopting small, cheap and configurable aerial vehicles, namely drones. Our work focusses on studying how to optimize their adoption for smart city applications designed to gather sensing data from user's devices roaming on the ground. To this purpose, we used HUMsim, a tool which generates realistic human traces, to mimic pedestrian mobility. From this dataset, we extract some sociality features that we exploit to plan a social-aware drone trajectory with the goal of maximizing the opportunities of interaction between drone and devices. Our experiments compare social-aware and social-oblivious trajectories showing that knowing the way people move and interact boosts the amount of retrievable data.

Time division multiple access (TDMA) is often used in wireless sensor networks (WSNs), especially for critical applications, as it provides high energy efficiency, guaranteed bandwidth, bounded and predictable latency, and absence of collisions. However, TDMA is vulnerable to selective jamming attacks. In TDMA transmission, slots are typically pre-allocated to sensor nodes, and each slot is used by the same node for a number of consecutive superframes. Hence, an adversary could thwart a victim node's communication by simply jamming its slot(s). Such attack turns out to be effective, energy efficient, and extremely difficult to detect. In this paper, we present JAMMY, a distributed and dynamic solution to selective jamming in TDMA-based WSNs. Unlike traditional approaches, JAMMY changes the slot utilization pattern at every superframe, thus making it unpredictable to the adversary. JAMMY is decentralized, as sensor nodes determine the next slot utilization pattern in a distributed and autonomous way. Results from performance analysis of the proposed solution show that JAMMY introduces negligible overhead yet allows multiple nodes to join the network, in a limited number of superframes.

Many dependable systems rely on the integrity of the position of their components. In such systems, two key problems are secure localization and secure location verification of the components. Researchers proposed several solutions, which generally require expensive infrastructures of several fixed stations (anchors) with trusted positions. In this paper, we explore the approach of replacing all the fixed anchors with a single drone that flies through a sequence of waypoints. At each waypoint, the drone acts as an anchor and securely determines the positions. This approach completely eliminates the need for many expensive anchors. The main challenge becomes how to find a convenient path for the drone to do this for all the devices. The problem presents novel aspects, which make existing path planning algorithms unsuitable. We propose LocalizerBee, VerifierBee, and PreciseVerifierBee: three path planning algorithms that allow a drone to respectively measure, verify, and verify with a guaranteed precision a set of positions in a secure manner. They are able to securely localize all the positions in a generic deployment area, even in the presence of drone control errors. Moreover, they produce short path lengths and they run in a reasonable processing time.

Android applications (apps) generate a consistent amount of data traffic. A noticeable share of this generated data traffic is used to convey third party advertisement, or to collect information about the user and its phone, generally with the target of profiling users. Such a traffic is not needed to the correct app execution and can be considered unwanted overhead. In this paper we propose Data-Sluice, a framework for Android devices which dynamically controls the connections opened by apps, enforcing fine grained policies designed to stop advertisement from altering the user experience, avoiding private data leakage and removing or strongly reducing the data traffic overhead. We apply Data-Sluice to a set of popular Android apps to analyze the generated traffic and removing the data overhead. Furthermore, we exploit Data-Sluice to successfully stop the action of a set of malicious apps.

This paper presents GREP, a highly scalable and efficient group rekeying protocol with the following merits. First, it rekeys the group with only two messages, introducing an overhead which is small, constant, and independent of the group size. Second, GREP considers collusion as a first-class attack. Third, GREP efficiently recovers the group from a collusion attack without recourse to a total member reinitialization. The recovery cost smoothly grows with the group size, and gradually increases with the attack severity. GREP achieves these results by organizing nodes into logical subgroups and exploiting the history of node joining events. This allows GREP to establish a total ordering among subgroups and among nodes in each subgroup, so making collusion recovery highly scalable and efficient. We evaluate performance from several standpoints, and show that GREP is deployable in large-scale networks of customary, even resource constrained, platforms.

Distance bounding protocols make it possible to determine a trusted upper bound on the distance between two devices. Their key property is to resist reduction attacks, i.e., attacks aimed at reducing the distance measured by the protocol. Recently, researchers have also focused on enlargement attacks, aimed at enlarging the measured distance. Providing security against such attacks is important for secure positioning techniques. The contribution of this paper is to provide a probabilistic model for the success of an enlargement attack against a distance bounding protocol realized with the IEEE 802.15.4a ultra-wideband standard. The model captures several variables, such as the propagation environment, the signal-to-noise ratio, and the time-of-arrival estimation algorithm. We focus on non-coherent receivers, which can be used in low-cost low-power applications. We validate our model by comparison with physical-layer simulations and goodness-of-fit tests. The results show that our probabilistic model is sufficiently realistic to replace physical-layer simulations. Our model can be used to evaluate the security of the ranging/positioning solutions that can be subject to enlargement attacks. We expect that it will significantly facilitate future research on secure ranging and secure positioning.

Wireless sensor networks enable a wealth of new applications in areas such as military, medical, environmental, transportation, smart city, and so on. In many of these scenarios, we need to measure in a secure way the positions of the sensors. Existing range-based techniques for secure positioning require a burdensome infrastructure, with many fixed anchors. Reducing the infrastructure would reduce deployment cost and foster the adoption of secure positioning solutions in wireless sensor networks. In this article, we propose SPEM, a secure positioning system based on multilateration and ultra-wideband (UWB) distance bounding protocols. The key idea behind SPEM is to leverage the low probability that an adversary has of controlling enlargement attacks against UWB. We estimate such a probability by a thorough study and signal-level simulations of the UWB physical layer. We test SPEM both in a simulated environment and in a real indoor environment using real UWB transceivers. We show that SPEM needs far less infrastructure than state-of-the-art solutions ( − 22% to − 93%, depending on the anchor deployment method), while achieving high levels of security against smart and determined adversaries.

The increasing complexity of automotive networks has led to broad security issues related to human safety. On the other hand, to solve problems of network overload, the automotive world is moving in the direction of using an Ethernet backbone for in-vehicle communications. Therefore, the security of Ethernet protocols for such applications has become a significant concern. The IEEE 802.1X-2010 standard could be a suitable solution for the key management of Ethernet-based encrypted communications. In this work, an efficient hardware accelerator for the intensive sections of the IEEE 802.1X-2010 is presented. The system was synthesized both on a Stratix V FPGA and on a 40nm standard-cell library. The former gives a usage of 3% of the Adaptive Logic Modules (ALMs) while the latter shows an occupation of 55 kgates. On the FPGA, the maximum throughput is 152 Mbps and 1.14 Gbps for the two considered sections of the standard while the standard-cell technology provides a maximum throughput of 457 Mbps and 3.85 Gbps. Results show that this architecture represents a fast and low-area key management solution for Ethernet networks in automotive applications.

Distance bounding protocols are secure protocols to determine an upper bound to the distance between two devices. These protocols have shown to be useful for many tasks, from proximity verification to secure positioning. Unfortunately, real distance bounding protocols hardly fulfill the claimed property. Attacks at the PHY layer may cause significant reductions on the estimated upper bound. These attacks can be mitigated, not eliminated, by changing the receiver architecture and the PHY layer. Every distance bounding protocol is thus non-ideal. In this paper, we study the impact of non-ideal distance bounding on the reliability of secure positioning techniques. We show that a reduction of 10 meters, which is possible against a real PHY layer, allows the adversary to falsify a position of 21 meters. We also propose two countermeasures to mitigate the problem, and then estimate their efficacy by simulations.

Many dependable systems rely implicitly on the integrity of the positions of their components. For example, let us consider a sensor network for pollution monitoring: it is sufficient that a hostile actor physically moves some sensors to completely disrupt the monitoring. In such scenarios, a key question is: how to securely verify the positions of devices? To answer this question, researchers proposed several solutions. However, these generally require several fixed stations (anchors) with trusted positions. In this paper, we explore the possibility to use the emerging drone technology in order to overcome the limitation of using several fixed anchors. In particular, our approach is to replace all the fixed anchors with a single drone that flies through a sequence of waypoints. At each waypoint, the drone “acts like” an anchor and securely verifies the positions of the devices. The main challenge here is to find a convenient path for the drone to do this. The problem presents novel aspects, thus existing path planning algorithms cannot be used. We present VerifierBee: a path planning algorithm that allows a drone to perform a secure location verification of a set of devices. VerifierBee finds a good approximation of the shortest path, and at the same time it respects a set of requirements about drone controllability, localization precision, and communication range.

The success of location-based services is growing together with the diffusion of GPS-equipped smart devices. As a consequence, privacy concerns are raising year by year. Location privacy is becoming a major interest in research and industry world, and many solutions have been proposed for it. One of the simplest and most flexible approaches is obfuscation, in which the precision of location data is artificially degraded before disclosing it. In this paper, we present an obfuscation approach capable of dealing with measurement imprecision, multiple levels of privacy, untrusted servers and adversarial knowledge of the map. We estimate its resistance against statistical-based deobfuscation attacks, and we improve it by means of three techniques, namely extreme vectors, enlarge-and-scale and hybrid vectors.

The amount of Wireless Sensor Network applications requiring security is getting higher and higher and also developers that are not security experts are often required to secure their applications. Many times they do it without any consciousness of the security performance trade-off arisen by this operation.In this paper we present a method for performance evaluation of a modular security architecture for WSNs. Our method evaluates the costs that have to be paid when introducing security, in terms of memory occupancy, network performance and energy consumption. Knowing these indexes leads to awareness of security costs and helps in fine tuning of security performance trade-offs. A designer may apply our method to know the impact on performance of the security modules he needs. Also, we present performance data collected by applying our method on the implementation of PLASA, a modular security architecture we have designed and evaluated.

We propose PICARD (ProbabIlistic Contract on Android), a framework to generate probabilistic contracts to detect repackaged applications for Android smart phones. A contract describes the sequences of actions that an application is allowed to perform at run-time, i.e. its legal behavior. In PICARD, contracts are generated from the set of traces that represent the usage profile of the application. Both the contract and the application's run-time behavior are represented through clustered probabilistic automata. At run-time, the PICARD monitoring system verifies the compliance of the application trace with the contract. This approach is useful in detecting repackaged applications, whose behavior is strongly similar to the original application but it differs only from small paths in the traces. In this paper, we discuss the framework of PICARD for describing and generating contracts through probabilistic automata and introduce the notion of Action Node, a cluster of related system calls, used to represent high level operations. Then, we present a first set of preliminary experiments on repackaged applications, to evaluate the viability of the proposed approach.

Wireless Sensor Networks (WSNs) are frequently adopted in industrial applications. However, they are particularly prone to cyber-physical attacks. Since addressing all possible attacks is not viable, due to performance and economic reasons, it is vital to choose which attacks to address and which countermeasures to adopt. Hence, a quantitative analysis of attack impact is crucial to make an effective choice. In this paper, we present a simulative approach to attack impact analysis, and show that simulation results provide valuable insights on the attack severity. To fix ideas, we refer to a WSN monitoring pollutant emissions of a critical infrastructure. We analyze effects of cyber-physical attacks against the network, and rank them according to their impact severity. This supports designers in deciding which attacks to address and which countermeasures to select.

Wireless Sensor Networks (WSNs) are currently used in many application scenarios, including industrial applications and factory automation. In such scenarios, Time Division Multiple Access (TDMA) is typically used for data communication among sensor nodes. However, TDMA-based WSNs are particularly prone to Selective Jamming attack, a specific form of Denial of Service attack aimed at severely thwarting network reliability. In this paper, we present SAD-SJ, a self-adaptive and decentralized MAC-layer solution against selective jamming in TDMA-based WSNs. SAD-SJ does not need a central entity, requires sensor nodes to rely only on local information, and allows them to join and leave the network without hindering other nodes activity. We show that SAD-SJ introduces a limited overhead, in terms of computation, communication and energy consumption.

Group communication is a suitable and effective communication model for large-scale distributed systems. To be fully exploitable, group communication must be protected. This is normally achieved by providing members with a group key which is revoked and redistributed upon every member's joining (backward security) or leaving (forward security). Such a rekeying process must be efficient and highly scalable. In this paper, we present HISS, a highly scalable group rekeying scheme that efficiently rekeys the group into two broadcast rekeying messages. HISS features two novel contributions. First, it exhibits a rekeying cost which is constant and independent of the group size, thus being highly scalable with the number of users. At the same time, memory occupancy and computational overhead are affordable on customary platforms. Second, HISS considers collusion as a first-class attack and recovers the group in such a way that it does not require a total group recovery. Efficiency of collusion recovery gracefully decreases with the attack severity. We prove the correctness of HISS, analytically evaluate its performance and argue that it is deployable on customary platforms. Finally, we show that it is possible to practically contrast or even prevent collusion attacks by properly allocating users to subgroups.

Wireless Sensor Networks are vulnerable to quite a good deal of logical and physical security attacks. However, providing security countermeasures for every possible attack is practically unfeasible for cost and performance reasons. Thus, it is vital to properly rank security attacks in order to establish priorities and then select appropriate countermeasures. In this paper, we present ASF, an attack simulation framework that allows us to describe attacks and quantitatively evaluate their effects on the application and network behavior and performance. ASF helps users to evaluate the impact of an attack, a crucial step in the attacks ranking activity. Also, we present an early prototype of ASF built on top of the popular simulator Castalia. Finally, we show the capabilities of ASF by analysing four attacks against a realistic application scenario.

An Underwater Acoustic Network (UAN) raises many issues in terms of security. In this paper we focus on attacks performed during the network discovery phase. At the state of art, all underwater discovery protocols do not provide message authenticity so they are exposed to spoofing-based attacks against network integrity and availability. In this paper, we focus on FLOOD, a network discovery protocol for UANs and we extend it in order to provide protection against network authenticity and integrity attacks. In particular we show that certain attacks against integrity and leading to Denial of Service are avoided.

An underwater acoustic scenario raises many problems in terms of security because of the limited bandwidth provided by the underwater medium. In this paper we face with the problem of secure cooperation among underwater acoustic vehicles. We propose a cryptographic suite able to reduce at the minimum the message overhead added by security. The cryptographic suite provides vehicles authentication, confidentiality and integrity of messages and key management. A prototype has been implemented and preliminary performance evaluation tests are shown.

Decentralized coordination of multi-agents requires that every agent reliably and efficiently disseminates its state to neighbours through a wireless network. If dissemination is unreliable, safety issues may ensue. Unfortunately, the broadcast service of wireless network is efficient but unreliable (e.g., IEEE 802.11). The Neighbourhood Monitoring Protocol (NMP) is an efficient and scalable protocol that assures a reliable state dissemination between mobile agents, under some conditions of channel utilization. NMP runs on top of IEEE 802.11. In this paper we evaluate NMP with a specific decentralized collision avoidance algorithm based on the GRP policy. The algorithm is particularly challenging because it accommodates an arbitrary number non-holonomic agents. We show that NMP allows the system to scale well and provides a very high state delivery ratio even if it operates on the unreliable broadcast service like 802.11. Doing so, NMP assures the correct state information to the collision avoidance algorithm.

Group communication has proven a powerful paradigm for designing applications and services in Wireless Sensor Networks (WSNs). Given the tight interaction between WSNs and the physical world, a security infringement may translate into a safety infringement. Therefore, in order to fully exploit the group communication paradigm we need to secure it. Traditionally, this requirement has been formalized in terms of backward and forward security and fulfilled by means of rekeying . In WSNs, group rekeying becomes particularly a complex problem because communication takes place over an easily accessible wireless medium and because sensor nodes have severe limitations in terms of computing, storage, energy, and tamper-resistance capabilities for cost reasons. In this article we present a Lightweight Authenticated ReKeying (LARK) scheme for clustered WSNs. LARK guarantees backward and forward security, is scalable in terms of communication overhead, and efficient in terms of computing overhead for key authentiticy verification. LARK achieves security, efficiency, and scalability by exploiting two basic well-known mechanisms, namely key graph and key chain , and integrating them in an original way. LARK supports a general group model where groups can be hierachical and partially overlapping. In contrast to other WSN group rekeying schemes, LARK considers grouping a tool for designing and implementing applications and services rather than for network management. Consequently, LARK receives a group topology reflecting the application needs and manages rekeying at single-group level. In the article we describe LARK, formally argue that it meets the backward and forward security requirements, and, finally, evaluate its performance in terms of communication, computing, and storage overhead in limited-resources sensor nodes.

Delay Tolerant Network (DTN) is a network paradigm used to deliver messages when network connectivity is not guaranteed. In a DTN, communication is made possible by carriers, mobile nodes that physically carry messages from a network partition to another. Selecting carriers that provide the best delivery probability is a crucial issue. However, if carriers misbehave, the integrity and availability of a DTN is endangered. In this paper we present a decentralised reputation-based system aimed at tolerating misbehaving carriers. A prototype of the system has been integrated into Context Aware Routing (CAR) [1]. Simulations show that the resulting system RCAR provides a greater delivery probability than CAR and Epidemic Routing [2] without increasing the average delivery delay.

In the last twenty years, secure group communication has received ever increasing interest. Many rekeying schemes have been proposed in the literature that are both scalable and able to fulfil backward and forward security in a dynamic group model. However, all these schemes assume a single-group model and thus are not efficient when applied to a class of ermerging applications that require a more general multi-group model, where groups may overlap both partially and totally. In this paper, we present MG-LKH, a new centralised rekeying scheme for a dynamic multi-group model that is scalable in terms of storage, computing, and, especially, communication with respect to the number of users and the number and size of groups. Furthermore, we evaluate MG-LKH performance and compare it to traditional rekeying schemes adapted to the multi-group scenario.

In this paper we present a secure publish-subscribe service conceived to support cooperation between organizations. The service is based on the notion of security group, an overlay composed of brokers representing organizations that guarantees confidentiality and integrity in end-to-end delivery of messages and supports clients mobility. A security group is dynamic and can be formed only by trusted brokers, i.e., brokers fulfilling the group admission policy. An early prototype of the system has been implemented.

In this paper we present Bloumail, a tool for detecting bot-generated spam. Bloumail operates, at the user-side on single user's email streams, handles reduced user-specific email traffic, and thus is able to effectively detect spam in real-time. Sometimes Bloumail requires user intervention. However, by properly training it, such an intervention can be kept at minimum.

This paper addresses a security problem in robotic multi-agent systems, where agents are supposed to cooperate according to a shared protocol. A distributed Intrusion Detection System (IDS) is proposed here, that detects possible non-cooperative agents. Previous work by the authors showed how single monitors embedded on-board the agents can detect non- cooperative behavior, using only locally available information. In this paper, we allow such monitors to share the collected information in order to overcome their sensing limitation. In this perspective, we show how an agreement on the type of behavior of a target-robot may be reached by the monitors, through execution of a suitable consensus algorithm. After formulating a consensus problem over non-scalar quantities, and with a generic update function, we provide conditions for the consensus convergence and an upper bound to its transient duration. Effectiveness of the proposed solution is finally shown through simulation of a case study.

The failure of sensor nodes could hinder the usefulness and the effectiveness of a WNS. In this paper we present a method to repair network partitioning by using a mobile node. By reasoning upon the degree of connectivity with neighbours, the mobile node finds the position where to deploy new sensor nodes in order to restore the network connectivity. Factors influencing the algorithm performance are discussed. Simulations show that the proposed method is effective and efficient not withstanding packet loss.

Nowadays, small, low-cost sensor nodes are being widely used to build self-organizing, large-scale, wireless networks for various applications, such as environmental surveillance, health monitoring and so on. Given its unique features, protecting a wireless sensor network is a difficult challenge. In this paper, we present S2RP, a secure and scalable rekeying protocol for sensor networks. S2RP aims at a trade-off between security and resource consumption while it guarantees an authentic distribution of keys that preserves both forward and backward security. The proposed protocol is efficient in terms of communication overhead as it reduces the number and the size of rekeying messages. It is efficient in terms of computation overhead as it guarantees the necessary level of confidentiality and authenticity of rekeying messages by only using symmetric ciphers and one-way hash functions. It follows that S2RP meets the reduced capabilities of sensor nodes, results scalable, and particularly attractive for large and/or highly dynamic groups

Remote attestation in trusted computing is about the ability of a local platform to authenticate the hardware and the software stack running on a remote trusted platform. We say that this process is successful, if a local platform is able to authenticate each layer in the remote stack; it is meaningful if, by using this information, the local platform can make its own evaluation on the safety of the platform environment where the remote application is running. In this paper we analyze the credentials and beliefs that are necessary to a local platform in order for the remote attestation process to be both successful and meaningful.

In this paper, we present a scalable and secure protocol for key revocation in wireless sensor networks. The protocol guarantees an authenticated distribution of new keys that is efficient in terms of storage, communication and computing overhead. The proposed protocol reduces the number and the size of rekeying messages. It achieves the necessary level of confidentiality and authenticity of rekeying messages by only using symmetric ciphers and one-way functions. Hence, the protocol results scalable, and particularly attractive for large and/or highly dynamic groups

We present a thorough analysis of the memory behaviour of page caching and prefetching algorithms. The analysis is restricted to programs whose execution consists of iteration of a sequence of page accesses. Program activity is characterized in terms of utilization of system resources. A graphical model of program execution is used to describe both page placement in the primary memory and the actions of page fetch and replacement. The algorithms are compared from the point of view of a number of performance indexes that include program response time and utilization of the secondary memory system. Special attention is paid to transient program behaviour and the effects of the time necessary for the processor to control the disk activities of page fetch. The results of a large set of measurement experiments are used to validate the analytical model and acquire significant indications concerning the extent of the simplifying assumptions made in the theoretical analysis. The discussion of the relation to previous work makes special reference to two classes of algorithms that received much attention in the past, aggressive prefetching and informed prefetching.

We present a secure and available voting system suitable for a large-scale distributed system such as the Internet. The proposed service is based on replication and tolerates both benign and fully arbitrary failures of servers. If enough servers are correct, service availability and security are ensured despite the presence of faulty servers and any number of faulty voters. A voter that suffers a crash failure can vote after recovery. The proposed service satisfies common voting requirements including voter eligibility and privacy, and tally accuracy. In addition, the service satisfies a further important requirement, namely tally verifiability without any intervention of voters. Anyone, including an external observer can easily be convinced that the election outcome is fairly computed from the ballots that were correctly cast. It follows that the proposed voting scheme strengthens the security properties of the electronic voting procedure, and simplifies the interaction of voters with the electronic voting system.

Abstract In this paper, we propose a practical and secure electronic voting scheme suitable for large‐scale distributed systems such as the Internet. As in most of the voting systems in the literature, the proposed voting scheme allows only eligible voters to vote once, protects the voters' privacy, and ensures the accuracy of the tally. In addition, the proposed scheme satisfies further important criteria, namely, it tolerates abstention and does not require voters to control whether their votes have been correctly processed. If a subset of voters does not vote, the elections cannot be disrupted. Furthermore, anyone, including an external observer, can easily be convinced that the election is fair, that is, that the published final tally is fairly computed from the ballots that were correctly cast. It follows that the proposed voting scheme strengthens the security properties of the electronic voting procedure, simplifies the interaction of voters with the electronic voting system, and contributes to increased voter confidence in the degree of security of the electronic voting procedure. © 2001 John Wiley & Sons, Inc.

With reference to a distributed context consisting of computers connected by a local area network, we present the organization of a memory management system giving physical support to a uniform, persistent vision of storage according to a single address space paradigm. Our system implements a two-layer storage hierarchy in which the distributed secondary memory stores the valid data items and the primary memory supports a form of data caching, for fast processor access. The proposed system defines a small, powerful set of operations that allow application programs to exert explicit control over the memory management activities at the levels of physical storage allocation, data migration across the network, and the data movements between the secondary memory and the primary memory. The system, that has been implemented in prototype form, is assessed from a number of viewpoints. We show that the storage requirements of the information for memory management are negligible. Moreover, the number of messages necessary to determine the network location of a given data item is low and independent of both the network size and the past movements of this data item in the distributed storage.Copyright © 2000 John Wiley & Sons, Ltd.

Distributed systems constructed using off-the-shelf communication infrastructures are becoming common vehicles for doing business in many important application domains. Large geographic extent due to increased globalization, increased probability of failures, and highly dynamic loads all contribute toward a partitionable and asynchronous characterization for these systems. In this paper, we consider the problem of developing reliable applications to be deployed in partitionable asynchronous distributed systems. What makes this task difficult is guaranteeing the consistency of shared state despite asynchrony, failures, and recoveries, including the formation and merging of partitions. While view synchrony within process groups is a powerful paradigm that can significantly simplify reasoning about asynchrony and failures, it is insufficient for coping with recoveries and merging of partitions after repairs. We first give an abstract characterization for shared state management in partitionable asynchronous distributed systems and then show how views can be enriched to convey structural and historical information relevant to the group's activity. The resulting, paradigm, called enriched view synchrony, can be implemented efficiently and leads to a simple programming methodology for solving shared state management in the presence of partitions.

View synchrony has been proposed as a programming paradigm for developing reliable distributed applications. The paradigm is particularly attractive when the underlying computing system is asynchronous and prone to complex failure scenarios including partitions. View synchrony encourages a programming style where groups of processes cooperate closely in order to maintain some form of shared state among them. In this paper we examine the technical problems that arise in shared state management when programming applications using view synchrony. We identify three classes of problems corresponding to state transfer upon group joins, state recreation after total failures and state merging after partition unions. We argue that shared state problems are inherent to any implementation, and without explicit support, attempts to solve them may easily obscure much of the simplicity and elegance of view synchrony. Finally, we propose an extension to the traditional view synchrony model based on the notion of subviews that addresses the problems raised by shared state management.