Classification techniques can be used to analyze system behaviors, network protocols, and cryptographic primitives based on identifiable traits. While useful for defense, such classification can also be leveraged by attackers to infer system configurations, detect vulnerabilities, and tailor attacks such as denial-of-service, key recovery, or downgrade attacks. In this paper, we study the feasibility of classifying post-quantum (PQ) algorithms by analyzing implementations of key exchange and digital signatures, their use within secure protocols, and their integration into SNARK generation libraries. Unlike traditional cryptography, PQ algorithms have larger memory requirements and variable computational costs. Our research examines two post-quantum cryptography libraries, liboqs and CIRCL, evaluating TLS, SSH, QUIC, OpenVPN, and OpenID Connect (OIDC) across Windows, Ubuntu, and macOS. We also analyze pysnark and lattice_zksnark for SNARK generation and verification on Ubuntu. Experimental results show that (1) classical and PQ key exchange and signature algorithms can be distinguished with accuracies of 98% and 100%; (2) specific PQ algorithms can be identified with 97% accuracy for key exchange and 86% for signatures; (3) implementations of the same algorithm in liboqs and CIRCL are distinguishable with up to 100% accuracy; and (4) within CIRCL, PQ and hybrid key exchange implementations can be distinguished with 97% accuracy. For secure protocols, we can determine whether key exchange is classical or PQ and identify the PQ algorithm used. SNARK generation and verification in pysnark and lattice_zksnark are distinguishable with 100% accuracy. We demonstrate real-world applicability by identifying PQ-enabled TLS domains in the Tranco dataset and integrating our methods into QUARTZ, an open-source risk and threat analyzer by Cisco.

Adaptive Cruise Control (ACC) is a widely used driver assistance technology for maintaining desired speed and safe distance to the leading vehicle. This paper evaluates the security of the deep neural network (DNN) based ACC systems under runtime stealthy perception attacks that strategically inject perturbations into camera data to cause forward collisions. We present a context-aware strategy for the selection of the most critical times for triggering the attacks and a novel optimization-based method for the adaptive generation of image perturbations at runtime. We evaluate the effectiveness of the proposed attack using an actual vehicle, a publicly available driving dataset, and a realistic simulation platform with the control software from a production ACC system, a physical-world driving simulator, and interventions by the human driver and safety features such as Advanced Emergency Braking System (AEBS). Experimental results show that the proposed attack achieves 142.9 times higher success rate in causing hazards and 82.6% higher evasion rate than baselines, while being stealthy and robust to real-world factors and dynamic changes in the environment. This study highlights the role of human drivers and basic safety mechanisms in preventing attacks.

Quantum computing poses transformative opportunities and challenges, with cryptography at the forefront of its impact. The ACM CCS Workshop on Quantum-Resistant Cryptography and Security (QRSec 2025) provides a forum for researchers, practitioners, and industry leaders to explore advances in post-quantum cryptography (PQC) and its integration into secure systems. Building on the momentum of the NIST PQC standardization process and the release of the first standards in 2024, QRSec 2025 highlights theoretical foundations, algorithm design, engineering, and deployment strategies alongside emerging topics such as machine learning for cryptanalysis, quantum-resistant networks, blockchain, IoT, and cloud security. The program features keynotes from leading experts, technical paper sessions, and interactive panels bridging academia, industry, and government. By fostering dialogue across these communities, QRSec 2025 aims to advance the state of the art in quantum-resistant security and chart practical paths for migration and compliance in the post-quantum era.

Solana has emerged as a major blockchain platform providing high throughput and low fees. Like other blockchains, Solana can be attacked via so-called ''Sandwiching'' attacks, where an attacker observes a pending transaction, quickly buys the target cryptocurrency, lets the transaction go through, and then immediately sells it for a profit, skimming that profit from the user who submitted the transaction. While such attacks have been observed by users, they remain underexplored in academic literature due to technical difficulties studying Solana at scale.

Enterprises that own or handle sensitive resources rely on access control models to protect those resources. NIST has recently standardized a new access control model called Next Generation Access Control (NGAC) and provided a reference implementation. Despite the importance of properly functioning access control systems, little work has been done to verify that the software implementing NGAC properly conforms to the NGAC standard. Prior approaches for finding bugs are either designed to detect fail-stop faults, or model the protocol or software itself, which does not identify discrepancies between software and standards.

Most machine learning applications rely on centralized learning processes, opening up the risk of exposure of their training datasets. While federated learning (FL) mitigates to some extent these privacy risks, it relies on a trusted aggregation server for training a shared global model. Recently, new distributed learning architectures based on Peer-to-Peer Federated Learning (P2PFL) offer advantages in terms of both privacy and reliability. Still, their resilience to poisoning attacks during training has not been investigated. In this article, we propose new backdoor attacks for P2PFL that leverage structural graph properties to select the malicious nodes, and achieve high attack success, while remaining stealthy. We evaluate our attacks under various realistic conditions, including multiple graph topologies, limited adversarial visibility of the network, and clients with non-IID data. Finally, we show the limitations of existing defenses adapted from FL and design a new defense that successfully mitigates the backdoor attacks, without an impact on model accuracy.

The emergence of decentralized finance has transformed asset trading on the blockchain, making traditional financial instruments more accessible while also introducing a series of exploitative economic practices known as Maximal Extractable Value (MEV). Concurrently, decentralized finance has embraced rollup-based Layer-2 solutions to facilitate asset trading at reduced transaction costs compared to Layer-1 solutions such as Ethereum. However, rollups lack a public mempool like Ethereum, making the extraction of MEV more challenging.

The Lightning Network, a payment channel network with a market cap of over 192M USD, is designed to resolve Bitcoin's scalability issues through fast off-chain transactions. There are multiple Lightning Network client implementations, all of which conform to the same textual specifications known as BOLTs. Several vulnerabilities have been manually discovered, but to-date there have been few works systematically analyzing the security of the Lightning Network.

Intent-based networking (IBN) enables network administrators to express high-level goals and network policies without needing to specify low-level forwarding configurations, topologies, or protocols. Administrators can define intents that capture the overall behavior they want from the network, and an IBN controller compiles such intents into low-level configurations that get installed in the network and implement the desired behavior.

GossipSub is a new peer-to-peer communication protocol designed to counter attacks from misbehaving peers by controlling what information is sent and to whom, via a score function computed by each peer that captures positive and negative behaviors of its neighbors. The score function depends on several parameters (weights, caps, thresholds) that can be configured by applications using GossipSub. The specification for GossipSub is written in English and its resilience to attacks from misbehaving peers is supported empirically by emulation testing using an implementation in Golang.In this work we take a foundational approach to understanding the resilience of GossipSub to attacks from misbehaving peers. We build the first formal model of GossipSub, using the ACL2s theorem prover. Our model is officially endorsed by the GossipSub developers. It can simulate GossipSub networks of arbitrary size and topology, with arbitrarily configured peers, and can be used to prove and disprove theorems about the protocol. We formalize fundamental security properties stating that the score function is fair, penalizes bad behavior, and rewards good behavior. We prove that the score function is always fair, but can be configured in ways that either penalize good behavior or ignore bad behavior. Using our model, we run GossipSub with the specific configurations for two popular real-world applications: the FileCoin and Eth2.0 blockchains. We show that all properties hold for FileCoin. However, given any Eth2.0 network (of any topology and size) with any number of potentially misbehaving peers, we can synthesize attacks where these peers are able to continuously misbehave by never forwarding topic messages, while maintaining positive scores so that they are never pruned from the network by GossipSub.

Commercially-available software defined networking (SDN) technologies will play an important role in protecting the on-premises resources that remain as enterprises transition to zero trust architectures. However, existing solutions assume the entire network resides in a single geographic location, requiring organizations with multiple sites to manually ensure consistency of security policy across all sites. In this paper, we present MSNetViews, which extends a single, globally-defined and managed, enterprise network security policy to many geographically distributed sites. Each site operates independently and enforces a site-specific policy slice that is dynamically parameterized with user location as employees roam between sites. We build a prototype of MSNetViews and show that for an enterprise with globally distributed sites, the average time for policy state to settle after a user roams to a new site is well below two seconds. As such, we demonstrate that multisite organizations can efficiently protect their on-premises network-attached devices via a single global perspective.

The rise of Ethereum has lead to a flourishing decentralized marketplace that has, unfortunately, fallen victim to frontrunning and Maximal Extractable Value (MEV) activities, where savvy participants game transaction orderings within a block for profit. One popular solution to address such behavior is Flashbots, a private pool with infrastructure and design goals aimed at eliminating the negative externalities associated with MEV. While Flashbots has established laudable goals to address MEV behavior, no evidence has been provided to show that these goals are achieved in practice.

Traditional enterprise security relies on network perimeters to define and enforce network security policies. Emerging application-focused Zero Trust architectures attempt to address this long-standing challenge by moving business applications to the cloud and performing enhanced identity and access control checks within a web gateway. However, these solutions ignore the security needs of workstations, development servers, and device management interfaces. In this work, we propose Network Views (abbrev. NetViews) for least-privilege network access control where each host has a different, limited view of the other hosts and services within a network. We present an SDN-based design and demonstrate that our implementation has network latency and throughput comparable to baseline reactive forwarding. We further provide an optimization for multi-connection flows that significantly reduces both redundant access control checks and forwarding state storage in switches. As such, NetViews provides a practical primitive for removing the reliance on security perimeters within enterprise networks.

We present ShorTor, a protocol for reducing latency on the Tor network. ShorTor uses multi-hop overlay routing, a technique typically employed by content delivery networks, to influence the route Tor traffic takes across the internet. In this way, ShorTor avoids slow paths and improves the experience for end users by reducing the latency of their connections while imposing minimal bandwidth overhead. ShorTor functions as an overlay on top of onion routing—Tor’s existing routing protocol—and is run by Tor relays, making it independent of the path selection performed by Tor clients. As such, ShorTor reduces latency while preserving Tor’s existing security properties. Specifically, the routes taken in ShorTor are in no way correlated to either the Tor user or their destination, including the geographic location of either party. We analyze the security of ShorTor using the AnoA framework, showing that ShorTor maintains all of Tor’s anonymity guarantees. We augment our theoretical claims with an empirical analysis. To evaluate ShorTor’s performance, we collect a real-world dataset of over 400,000 latency measurements between the 1,000 most popular Tor relays, which collectively see the vast majority of Tor traffic. With this data, we identify pairs of relays that could benefit from ShorTor: that is, two relays where introducing an additional intermediate network hop results in lower latency than the direct route between them. We use our measurement dataset to simulate the impact on end users by applying ShorTor to two million Tor circuits chosen according to Tor’s specification. ShorTor reduces the latency for the 99thpercentile of relay pairs in Tor by 148ms. Similarly, ShorTor reduces the latency of Tor circuits by 122ms at the 99thpercentile. In practice, this translates to ShorTor truncating tail latencies for Tor which has a direct impact on page load times and, consequently, user experience on the Tor browser.

Automated attack discovery techniques, such as attacker synthesis or model-based fuzzing, provide powerful ways to ensure network protocols operate correctly and securely. Such techniques, in general, require a formal representation of the protocol, often in the form of a finite state machine (FSM). Unfortunately, many protocols are only described in English prose, and implementing even a simple network protocol as an FSM is time-consuming and prone to subtle logical errors. Automatically extracting protocol FSMs from documentation can significantly contribute to increased use of these techniques and result in more robust and secure protocol implementations.In this work we focus on attacker synthesis as a representative technique for protocol security, and on RFCs as a representative format for protocol prose description. Unlike other works that rely on rule-based approaches or use off-the-shelf NLP tools directly, we suggest a data-driven approach for extracting FSMs from RFC documents. Specifically, we use a hybrid approach consisting of three key steps: (1) large-scale word-representation learning for technical language, (2) focused zero-shot learning for mapping protocol text to a protocol-independent information language, and (3) rule-based mapping from protocol-independent information to a specific protocol FSM. We show the generalizability of our FSM extraction by using the RFCs for six different protocols: BGPv4, DCCP, LTP, PPTP, SCTP and TCP. We demonstrate how automated extraction of an FSM from an RFC can be applied to the synthesis of attacks, with TCP and DCCP as case-studies. Our approach shows that it is possible to automate attacker synthesis against protocols by using textual specifications such as RFCs.

Abstract Secure channel establishment protocols such as Transport Layer Security (TLS) are some of the most important cryptographic protocols, enabling the encryption of Internet traffic. Reducing latency (the number of interactions between parties before encrypted data can be transmitted) in such protocols has become an important design goal to improve user experience. The most important protocols addressing this goal are TLS 1.3, the latest TLS version standardized in 2018 to replace the widely deployed TLS 1.2, and Quick UDP Internet Connections (QUIC), a secure transport protocol from Google that is implemented in the Chrome browser. There have been a number of formal security analyses for TLS 1.3 and QUIC, but their security, when layered with their underlying transport protocols, cannot be easily compared. Our work is the first to thoroughly compare the security and availability properties of these protocols. Toward this goal, we develop novel security models that permit “layered” security analysis. In addition to the standard goals of server authentication and data confidentiality and integrity, we consider the goals of IP spoofing prevention, key exchange packet integrity, secure channel header integrity, and reset authentication, which capture a range of practical threats not usually taken into account by existing security models that focus mainly on the cryptographic cores of the protocols. Equipped with our new models we provide a detailed comparison of three low-latency layered protocols: TLS 1.3 over TCP Fast Open (TFO), QUIC over UDP, and QUIC[TLS] (a new design for QUIC that uses TLS 1.3 key exchange) over UDP. In particular, we show that TFO’s cookie mechanism does provably achieve the security goal of IP spoofing prevention. Additionally, we find several new availability attacks that manipulate the early key exchange packets without being detected by the communicating parties. By including packet-level attacks in our analysis, our results shed light on how the reliability, flow control, and congestion control of the above layered protocols compare, in adversarial settings. We hope that our models will help protocol designers in their future protocol analyses and that our results will help practitioners better understand the advantages and limitations of secure channel establishment protocols.

Tools and interfaces are increasingly expected to be synchronous and distributed to accommodate remote collaboration. Yet, adoption of these techniques for data visualization is low partly because development is difficult: existing collaboration software systems either do not support simultaneous interaction or require expensive redevelopment of existing visualizations. We contribute VisConnect: a web-based synchronous distributed collaborative visualization system that supports most web-based SVG data visualizations, balances system safety with responsiveness, and supports simultaneous interaction from many collaborators. VisConnect works with existing visualization implementations with little-to-no code changes by synchronizing low-level JavaScript events across clients such that visualization updates proceed transparently across clients. This is accomplished via a peer-to-peer system that establishes consensus among clients on the per-element sequence of events, and uses a lock service to grant access over elements to clients. We contribute collaborative extensions of traditional visualization interaction techniques, such as drag, brush, and lasso, and discuss different strategies for collaborative visualization interactions. To demonstrate the utility of VisConnect, we present novel examples of collaborative visualizations in the healthcare domain, remote collaboration with annotation, and show in an education case study for e-learning with 22 participants that students found the ability to remotely collaborate on class activities helpful and enjoyable for understanding concepts. A free copy of this paper and source code are available on OSF at osf.io/ut7e6 and at visconnect.us.

Grammar-based fuzzing is a technique used to find software vulnerabilities by injecting well-formed inputs generated following rules that encode application semantics. Most grammar-based fuzzers for network protocols rely on human experts to manually specify these rules. In this work we study automated learning of protocol rules from textual specifications (i.e. RFCs). We evaluate the automatically extracted protocol rules by applying them to a state-of-the-art fuzzer for transport protocols and show that it leads to a smaller number of test cases while finding the same attacks as the system that uses manually specified rules.

Home-based Internet of Things (IoT) devices have gained in popularity and many households became "smart'' by using devices such as smart sensors, locks, and voice-based assistants. Given the limitations of existing authentication techniques, we explore new opportunities for user authentication in smart home environments. Specifically, we design a novel authentication method in IoT-enabled smart homes. We perform initial experiments and a user study leveraging network traffic collected from 8 IoT devices in our university lab. Preliminary results show that our LSTM model achieves a maximum accuracy of 75% in identifying users.

Software-defined networking (SDN) continues to grow in popularity because of its programmable and extensible control plane realized through network applications (apps). However, apps introduce significant security challenges that can systemically disrupt network operations, since apps must access or modify data in a shared control plane state. If our understanding of how such data propagate within the control plane is inadequate, apps can co-opt other apps, causing them to poison the control plane's integrity. We present a class of SDN control plane integrity attacks that we call cross-app poisoning (CAP), in which an unprivileged app manipulates the shared control plane state to trick a privileged app into taking actions on its behalf. We demonstrate how role-based access control (RBAC) schemes are insufficient for preventing such attacks because they neither track information flow nor enforce information flow control (IFC). We also present a defense, ProvSDN, that uses data provenance to track information flow and serves as an online reference monitor to prevent CAP attacks. We implement ProvSDN on the ONOS SDN controller and demonstrate that information flow can be tracked with low-latency overheads.

Connected vehicle applications such as autonomous intersections and intelligent traffic signals have shown great promises in improving transportation safety and efficiency. However, security is a major concern in these systems, as vehicles and surrounding infrastructures communicate through ad-hoc networks. In this paper, we will first review security vulnerabilities in connected vehicle applications. We will then introduce and discuss some of the defense mechanisms at network and system levels, including (1) the Security Credential Management System (SCMS) proposed by the United States Department of Transportation, (2) an intrusion detection system (IDS) that we are developing and its application on collaborative adaptive cruise control, and (3) a partial consensus mechanism and its application on lane merging. These mechanisms can assist to improve the security of connected vehicle applications.

As machine learning becomes widely used for automated decisions, attackers have strong incentives to manipulate the results and models generated by machine learning algorithms. In this paper, we perform the first systematic study of poisoning attacks and their countermeasures for linear regression models. In poisoning attacks, attackers deliberately influence the training data to manipulate the results of a predictive model. We propose a theoretically-grounded optimization framework specifically designed for linear regression and demonstrate its effectiveness on a range of datasets and models. We also introduce a fast statistical attack that requires limited knowledge of the training process. Finally, we design a new principled defense method that is highly resilient against all poisoning attacks. We provide formal guarantees about its convergence and an upper bound on the effect of poisoning attacks when the defense is deployed. We evaluate extensively our attacks and defenses on three realistic datasets from health care, loan assessment, and real estate domains.

We study collaborative adaptive cruise control as a representative application for safety services provided by autonomous cars. We provide a detailed analysis of attacks that can be conducted by a motivated attacker targeting the collaborative adaptive cruise control algorithm, by influencing the acceleration reported by another car, or the local LIDAR and RADAR sensors. The attacks have a strong impact on passenger comfort, efficiency and safety, with two of such attacks being able to cause crashes. We also present two detection methods rooted in physical-based constraints and machine learning algorithms. We show the effectiveness of these solutions through simulations and discuss their limitations.

Network protocol implementations must comply with their specifications that include properties describing the correct operational behavior of the protocol in response to different temporal orderings of network events. Due to inconsistent interpretations of the specification, developers can unknowingly introduce semantic bugs, which cause the implementations to violate the respective properties. Detecting such bugs in stateful protocols becomes significantly difficult as their operations depend on their internal state machines and the complex interactions between the protocol logic. In this paper, we present an automated tool to help developers analyze their protocol implementations and detect semantic bugs violating the temporal properties of the protocols. Given an implementation, our tool (1) extracts the implemented finite state machine (FSM) of the protocol from the source code by symbolically exploring the code and (2) determines whether the extracted FSM violates given temporal properties by using an off-the-shelf model checker. We demonstrated the efficacy of our tool by applying it on 6 protocol implementations. We detected 11 semantic bugs (2 with security implications) when we analyzed these implementations against properties obtained from their publicly available specifications.

Google's QUIC protocol, which implements TCP-like properties at the application layer atop a UDP transport, is now used by the vast majority of Chrome clients accessing Google properties but has no formal state machine specification, limited analysis, and ad-hoc evaluations based on snapshots of the protocol implementation in a small number of environments. Further frustrating attempts to evaluate QUIC is the fact that the protocol is under rapid development, with extensive rewriting of the protocol occurring over the scale of months, making individual studies of the protocol obsolete before publication.

Android has become the most popular mobile OS, as it enables device manufacturers to introduce customizations to compete with value-added services. However, customizations make the OS less dependable and secure, since they can introduce software flaws. Such flaws can be found by using fuzzing, a popular testing technique among security researchers.This paper presents Chizpurfle, a novel "gray-box" fuzzing tool for vendor-specific Android services. Testing these services is challenging for existing tools, since vendors do not provide source code and the services cannot be run on a device emulator. Chizpurfle has been designed to run on an unmodified Android OS on an actual device. The tool automatically discovers, fuzzes, and profiles proprietary services. This work evaluates the applicability and performance of Chizpurfle on the Samsung Galaxy S6 Edge, and discusses software bugs found in privileged vendor services.

The X.509 Public-Key Infrastructure has long been used in the SSL/TLS protocol to achieve authentication. A recent trend of Internet-of-Things (IoT) systems employing small footprint SSL/TLS libraries for secure communication has further propelled its prominence. The security guarantees provided by X.509 hinge on the assumption that the underlying implementation rigorously scrutinizes X.509 certificate chains, and accepts only the valid ones. Noncompliant implementations of X.509 can potentially lead to attacks and/or interoperability issues. In the literature, black-box fuzzing has been used to find flaws in X.509 validation implementations, fuzzing, however, cannot guarantee coverage and thus severe flaws may remain undetected. To thoroughly analyze X.509 implementations in small footprint SSL/TLS libraries, this paper takes the complementary approach of using symbolic execution. We observe that symbolic execution, a technique proven to be effective in finding software implementation flaws, can also be leveraged to expose noncompliance in X.509 implementations. Directly applying an off-the-shelf symbolic execution engine on SSL/TLS libraries is, however, not practical due to the problem of path explosion. To this end, we propose the use of SymCerts, which are X.509 certificate chains carefully constructed with a mixture of symbolic and concrete values. Utilizing SymCerts and some domain-specific optimizations, we symbolically execute the certificate chain validation code of each library and extract path constraints describing its accepting and rejecting certificate universes. These path constraints help us identify missing checks in different libraries. For exposing subtle but intricate noncompliance with X.509 standard, we cross-validate the constraints extracted from different libraries to find further implementation flaws. Our analysis of 9 small footprint X.509 implementations has uncovered 48 instances of noncompliance. Findings and suggestions provided by us have already been incorporated by developers into newer versions of their libraries.

As the Internet becomes an important part of the infrastructure our society depends on, it is crucial to construct networks that are able to work even when part of the network is compromised. This paper presents the first practical intrusion-tolerant network service, targeting high-value applications such as monitoring and control of global clouds and management of critical infrastructure for the power grid. We use an overlay approach to leverage the existing IP infrastructure while providing the required resiliency and timeliness. Our solution overcomes malicious attacks and compromises in both the underlying network infrastructure and in the overlay itself. We deploy and evaluate the intrusion-tolerant overlay implementation on a global cloud spanning East Asia, North America, and Europe, and make it publicly available.

Numerous routing protocols have been designed and subjected to model checking and simulations. However, model checking the design or testing the simulator-based prototype of a protocol does not guarantee that the implementation is free of bugs and vulnerabilities. Testing implementations beyond their basic functionality (also known as adversarial testing) can increase protocol robustness. We focus on automated adversarial testing of real-world implementations of wireless routing protocols. In our previous work we created Turret, a platform that uses a network emulator and virtualization to test unmodified binaries of general distributed systems. Based on Turret, we create Turret-W designed specifically for wireless routing protocols. Turret-W includes new functionalities such as differentiating routing messages from data messages to enable evaluation of attacks on the control plane and the data plane separately, support for several additional protocols (e.g., those that use homogeneous/heterogenous packet formats, those that run on geographic forwarding (not just IP), those that operate at the data link layer instead of the network layer), support for several additional attacks (e.g., replay attacks) and for establishment of adversarial side-channels that allow for collusion. Turret-W can test not only general routing attacks, but also wireless specific attacks such as wormhole. Using Turret-W on publicly available implementations of five representative routing protocols, we (re-)discovered 37 attacks and 3 bugs. All these bugs and 5 of the total attacks were not previously reported to the best of our knowledge.

Notwithstanding the latest buzzwords (grid, cloud, utility computing, SaaS, etc.), large-scale computing and cloud-like deployment are the fastest growing computing infrastructures today. How exactly they will look like tomorrow is still for the markets to decide, yet one thing has already been identified: clouds have new, untested deployment, associated adversarial models and vulnerabilities and hence a very different threat landscape. It is essential that our community becomes involved in shaping the future security of cloud computing. The CCSW workshop aims to bring together researchers and practitioners in all security and privacy aspects of cloud-centric and outsourced computing.

We present a new method for finding attacks in unmodified transport protocol implementations using the specification of the protocol state machine to reduce the search space of possible attacks. Such reduction is obtained by appling malicious actions to all packets of the same type observed in the same state instead of applying them to individual packets. Our method requires knowledge of the packet formats and protocol state machine. We demonstrate our approach by developing SNAKE, a tool that automatically finds performance and resource exhaustion attacks on unmodified transport protocol implementations. SNAKE utilizes virtualization to run unmodified implementations in their intended environments and network emulation to create the network topology. SNAKE was able to find 9 attacks on 2 transport protocols, 5 of which we believe to be unknown in the literature.

QUIC is a secure transport protocol developed by Google and implemented in Chrome in 2013, currently representing one of the most promising solutions to decreasing latency while intending to provide security properties similar with TLS. In this work we shed some light on QUIC's strengths and weaknesses in terms of its provable security and performance guarantees in the presence of attackers. We first introduce a security model for analyzing performance-driven protocols like QUIC and prove that QUIC satisfies our definition under reasonable assumptions on the protocol's building blocks. However, we find that QUIC does not satisfy the traditional notion of forward secrecy that is provided by some modes of TLS, e.g., TLS-DHE. Our analyses also reveal that with simple bit-flipping and replay attacks on some public parameters exchanged during the handshake, an adversary could easily prevent QUIC from achieving minimal latency advantages either by having it fall back to TCP or by causing the client and server to have an inconsistent view of their handshake leading to a failure to complete the connection. We have implemented these attacks and demonstrated that they are practical. Our results suggest that QUIC's security weaknesses are introduced by the very mechanisms used to reduce latency, which highlights the seemingly inherent trade off between minimizing latency and providing "good" security guarantees.

We introduce ConfSeer, an automated system that detects potential configuration issues or deviations from identified best practices by leveraging a knowledge base (KB) of technical solutions. The intuition is that these KB articles describe the configuration problems and their fixes so if the system can accurately understand them, it can automatically pinpoint both the errors and their resolution. Unfortunately, finding an accurate match is difficult because (a) the KB articles are written in natural language text, and (b) configuration files typically contain a large number of parameters with a high value range. Thus, expert-driven manual troubleshooting is not scalable. While there are several state-of-the-art techniques proposed for individual tasks such as keyword matching, concept determination and entity resolution, none offer a practical end-to-end solution to detect problems in machine configurations. In this paper, we describe our experiences building ConfSeer using a novel combinations of ideas from natural language processing, information retrieval and interactive learning. ConfSeer powers the recommendation engine behind Microsoft Operations Management Suite that proposes fixes for software configuration errors. The system has been running in production for about a year to proactively find misconfigurations on tens of thousands of servers. Our evaluation of ConfSeer against an expert-defined rule-based commercial system, an expert survey and web search engines shows that it achieves 80%-97.5% accuracy and incurs low runtime overheads.

Networks with homogeneous routing nodes are constantly at risk as any vulnerability found against a node could be used to compromise all nodes. Introducing diversity among nodes can be used to address this problem. With few variants, the choice of assignment of variants to nodes is critical to the overall network resiliency. We present the Diversity Assignment Problem (DAP), the assignment of variants to nodes in a network, and we show how to compute the optimal solution in medium-size networks. We also present a greedy approximation to DAP that scales well to large networks. Our solution shows that a high level of overall network resiliency can be obtained even from variants that are weak on their own. We provide a variation of our problem that matches the specific communication requirements of applications run over the network (e.g., Paxos and BFT). Also, we analyze the loss in resiliency when optimally assigning variants based on inaccurate information about compromises.

In this article, we propose Gatling, a framework that automatically finds performance attacks caused by insider attackers in large-scale message-passing distributed systems. In performance attacks, malicious nodes deviate from the protocol when sending or creating messages, with the goal of degrading system performance. We identify a representative set of basic malicious message delivery and lying actions and design a greedy search algorithm that finds effective attacks consisting of a subset of these actions. Although lying malicious actions are protocol dependent, requiring the format and meaning of messages, Gatling captures them without needing to modify the target system by using a type-aware compiler. We have implemented and used Gatling on nine systems, a virtual coordinate system, a distributed hash table lookup service and application, two multicast systems and one file sharing application, and three secure systems designed specifically to tolerate insiders, two based on virtual coordinates and one using Outlier Detection, one invariant derived from physical laws, and the last one a Byzantine resilient replication system. We found a total of 48 attacks, with the time needed to find each attack ranging from a few minutes to a few hours.

Security and performance are critical goals for distributed systems. The increased design complexity, incomplete expertise of developers, and limited functionality of existing testing tools often result in bugs and vulnerabilities that prevent implementations from achieving their design goals in practice. Many of these bugs, vulnerabilities, and misconfigurations manifest after the code has already been deployed making the debugging process difficult and costly. In this paper, we present Turret, a platform for automatically finding performance attacks in unmodified implementations of distributed systems. Turret does not require the user to provide any information about vulnerabilities and runs the implementation in the same operating system setup as the deployment, with an emulated network. Turret uses a new attack finding algorithm and several optimizations that allow it to find attacks in a matter of minutes. We ran Turret on 5 different distributed system implementations specifically designed to tolerate insider attacks, and found 30 performance attacks, 24 of which were not previously reported to the best of our knowledge.

One of Android's main defense mechanisms against malicious apps is a risk communication mechanism which, before a user installs an app, warns the user about the permissions the app requires, trusting that the user will make the right decision. This approach has been shown to be ineffective as it presents the risk information of each app in a “stand-alone” fashion and in a way that requires too much technical knowledge and time to distill useful information. We discuss the desired properties of risk signals and relative risk scores for Android apps in order to generate another metric that users can utilize when choosing apps. We present a wide range of techniques to generate both risk signals and risk scores that are based on heuristics as well as principled machine learning techniques. Experimental results conducted using real-world data sets show that these methods can effectively identify malware as very risky, are simple to understand, and easy to use.

Virtual coordinate systems (VCSs) provide accurate estimations of latency between arbitrary hosts on a network, while conducting a small amount of actual measurements and relying on node cooperation. While these systems have good accuracy under benign settings, they suffer a severe decrease of their effectiveness when under attack by compromised nodes acting as insider attackers. Previous defenses mitigate such attacks by using machine learning techniques to differentiate good behavior (learned over time) from bad behavior. However, these defense schemes have been shown to be vulnerable to advanced attacks that make the schemes learn malicious behavior as good behavior. We present Newton, a decentralized VCS that is robust to a wide class of insider attacks. Newton uses an abstraction of a real-life physical system, similar to that of Vivaldi, but in addition uses safety invariants derived from Newton's laws of motion. As a result, Newton does not need to learn good behavior and can tolerate a significantly higher percentage of malicious nodes. We show through simulations and real-world experiments on the PlanetLab testbed that Newton is able to mitigate all known attacks against VCSs while providing better accuracy than Vivaldi, even in benign settings. Finally, we show how to design a VCS that better matches a real physical system, thus allowing for more intuitive and tighter system parameters that are even more difficult to exploit by attackers.

Networks with homogeneous routing nodes are constantly at risk as any vulnerability found against a node could be used to compromise all nodes. Introducing diversity among nodes can be used to address this problem. With few variants, the choice of assignment of variants to nodes is critical to the overall network resiliency. We present the Diversity Assignment Problem (DAP), the assignment of variants to nodes in a network, and we show how to compute the optimal solution in medium-size networks. We also present a greedy approximation to DAP that scales well to large networks. Our solution shows that a high level of overall network resiliency can be obtained even from variants that are weak on their own. For real-world systems that grow incrementally over time, we provide an online version of our solution. Lastly, we provide a variation of our solution that is tunable for specific applications (e.g., BFT).

We focus on automated adversarial testing of real-world implementations of wireless routing protocols. We extend an existing platform, Turret, designed for general distributed systems, to address the specifics of wireless routing protocols. Specifically, we add functionality to differentiate routing messages from data messages and support wireless specific attacks such as blackhole and wormhole, or routing attacks such as replay attacks. The extended platform, Turret-W, uses a network emulator to create reproducible network conditions and virtualization to run unmodified binaries of wireless protocol implementations. Using the platform on publicly available implementations of two representative routing protocols we (re-)discovered 14 attacks and 3 bugs.

Wireless mesh networks (WMNs) have emerged as a flexible and low-cost network infrastructure, where heterogeneous mesh routers managed by different users collaborate to extend network coverage. This paper proposes a novel routing metric, Expected Forwarded Counter (EFW), and two further variants, to cope with the problem of selfish behavior (i.e., packet dropping) of mesh routers in a WMN. EFW combines, in a cross-layer fashion, routing-layer observations of forwarding behavior with MAC-layer measurements of wireless link quality to select the most reliable and high-performance path. We evaluate the proposed metrics both through simulations and real-life deployments on two different wireless testbeds, performing a comparative analysis with On-Demand Secure Byzantine Resilient Routing (ODSBR) Protocol and Expected Transmission Counter (ETX). The results show that our cross-layer metrics accurately capture the path reliability and considerably increase the WMN performance, even when a high percentage of network nodes misbehave.

One of Android's main defense mechanisms against malicious apps is a risk communication mechanism which, before a user installs an app, warns the user about the permissions the app requires, trusting that the user will make the right decision. This approach has been shown to be ineffective as it presents the risk information of each app in a "tand-alone" ashion and in a way that requires too much technical knowledge and time to distill useful information.

Virtual coordinate systems (VCS) provide accurate estimations of latency between arbitrary hosts on a network, while conducting a small amount of actual measurements and relying on node cooperation. While these systems have good accuracy under benign settings, they suffer a severe decrease of their effectiveness when under attack by compromised nodes acting as insider attackers. Previous defenses mitigate such attacks by using machine learning techniques to differentiate good behavior (learned over time) from bad behavior. However, these defense schemes have been shown to be vulnerable to advanced attacks that make the schemes learn malicious behavior as good behavior. We present Newton, a decentralized VCS that is robust to a wide class of insider attacks. Newton uses an abstraction of a real-life physical system, similar to that of Vivaldi, but in addition uses safety invariants derived from Newton's laws of motion. As a result, Newton does not need to learn good behavior and can tolerate a significantly higher percentage of malicious nodes. We show through simulations and real-world experiments on the Planet Lab test bed that Newton is able to mitigate all known attacks against VCS while providing better accuracy than Vivaldi, even in benign settings.

The openness of the Android operating system increased the number of applications developed, but it also introduced a new propagation vector for mobile malware. We model the propagation of mobile malware using epidemiology theory and study the problem as a function of the underlying mobility models. We define the optimal approach to heal an infected system with the help of a set of static healers that distribute patches, as the T-COVER problem and show that it is NP-HARD. We then propose two families of healer protocols that trade-off time recovery and energy consumed by sending patches. The first one uses randomization to ensure a small recovery time but may result in healers sending more patches than needed. The second one uses system feedback to optimize energy consumed by sending patches, but it may result in a larger recovery time. We show through simulations using the NS-3 simulator that despite lacking knowledge of the future, our protocols obtain a recovery time within a 10x bound of the oracle solution that knows the arrival time of the infected nodes.

The phenomenal growth of the Android platform in the past few years has made it a lucrative target of malicious application (app) developers. There are numerous instances of malware apps that send premium rate SMS messages, track users' private data, or apps that, even if not characterized as malware, conduct questionable actions affecting the user's privacy or costing them money. In this paper, we investigate the feasibility of using both the permissions an app requests, the category of the app, and what permissions are requested by other apps in the same category to better inform users whether the risks of installing an app is commensurate with its expected benefit. Existing approaches consider only the risks of the permissions requested by an app and ignore both the benefits and what permissions are requested by other apps, thus having a limited effect. We propose several risk signals that and evaluate them using two datasets, one consists of 158,062 Android apps from the Android Market, and another consists of 121 malicious apps. We demonstrate the effectiveness of our proposal through extensive data analysis.

Recent work in defending against pollution attacks for intra-flow network coding systems proposed a null spaces based algebraic approach which has a smaller computation cost than previous pollution defenses. The approach requires the source to distribute keys periodically, but in order to scale involves forwarder nodes in the creation of new keys and their distribution. As a result the key distribution is secure only in specific network topologies such as those created by large-scale peer to peer systems, and is not secure in wireless networks where such topologies do not exist. We propose Split Null Keys, which splits the keys such that only a small portion of the key is updated periodically. The small updates allow for a scalable key distribution scheme that does not involve forwarder nodes in creating keys and thus does not rely its security on constraints imposed on the network topology. We prove that our scheme is secure despite splitting the key and we show that when compared with existing defenses our scheme imposes lower communication and computation overhead, is resilient to colluding adversaries, and does not require time synchronization.

Multihop wireless networks gain higher performance by using network coding. However, using network coding also introduces new attacks such as the well-studied pollution attacks and less-studied entropy attacks. Unlike in pollution attacks where an attacker injects polluted packets (i.e., packets that are not linear combinations of the packets sent by the source), in entropy attacks an attacker creates non-innovative packets (i.e., packets that contain information already known by the system). In both cases the result is a severe degradation of the system performance. In this paper, we identify two variants of entropy attacks (local and global) and show that while they share some characteristics with pollution attacks and selective forwarding, none of the techniques proposed to defend against such attacks are applicable to entropy attacks because the packets look legitimate and the packet forwarding is stealthy in nature. We propose and evaluate several defenses that vary in detection capabilities and overhead.

We study data pollution attacks in wireless interflow network coding systems. Although several defenses for these attacks are known for intraflow network coding systems, none of them are applicable to interflow coding systems. We formulate a model for interflow network coding that encompasses all the existing systems, and use it to analyze the impact of pollution attacks. Our analysis shows that the effects of pollution attacks depend not only on the network topology, but also on the location and strategy of the attacker nodes. We propose CodeGuard, a reactive attestation-based defense mechanism that uses efficient bit-level traceback and a novel cross-examination technique to unequivocally identify attacker nodes. We analyze the security of CodeGuard and prove that it is always able to identify and isolate at least one attacker node on every occurrence of a pollution attack. We analyze the overhead of CodeGuard and show that the storage, computation, and communication overhead are practical. We experimentally demonstrate that CodeGuard is able to identify attacker nodes quickly (within 500 ms) and restore system throughput to a high level, even in the presence of many attackers, thus preserving the performance of the underlying network coding system.

We conduct a detailed simulation study to examine how localizing P2P traffic within network boundaries impacts the profitability of an ISP. A distinguishing aspect of our work is the focus on Internet-wide implications, i.e., how adoption of localization within an ISP affects both itself and other ISPs. Our simulations are based on detailed models that estimate inter-autonomous-system (AS) P2P traffic and inter-AS routing, localization models that predict the extent to which P2P traffic is reduced, and pricing models that predict the impact of changes in traffic on the profit of an ISP. We evaluate our models by using a large-scale crawl of BitTorrent containing over 138 million users sharing 2.75 million files. Our results show that the benefits of localization must not be taken for granted. Some of our key findings include: 1) residential ISPs can actually lose money when localization is employed, and some of them will not see increased profitability until other ISPs employ localization; 2) the reduction in costs due to localization will be limited for small ISPs and tends to grow only logarithmically with client population; and 3) some ISPs can better increase profitability through alternate strategies to localization by taking advantage of the business relationships they have with other ISPs.

Virtual coordinate systems provide an accurate and efficient service that allows hosts on the Internet to determine latency to arbitrary hosts based on information provided by a subset of participating nodes. Unfortunately, the accuracy of the service can be severely impacted by compromised nodes providing misleading information. We define and use a game theory framework in order to identify the best attack and defense strategies assuming that the attacker is aware of the defense mechanisms. Our approach leverages concepts derived from the Nash equilibrium to model more powerful adversaries. We consider attacks that target the latency estimation (inflation, deflation, oscillation) and defense mechanisms that combine outlier detection with control theory to deter adaptive adversaries. We apply the game theory framework to demonstrate the impact and efficiency of these attack and defense strategies using a well-known virtual coordinate system and real-life Internet data sets.

Wireless mesh networks (WMNs) have emerged as a flexible and low-cost network infrastructure, where heterogeneous mesh routers managed by different users collaborate to extend network coverage. Several routing protocols have been proposed to improve the packet delivery rate based on enhanced metrics that capture the wireless link quality. However, these metrics do not take into account that some participants can exhibit selfish behavior by selectively dropping packets sent by other mesh routers in order to prioritize their own traffic and increase their network utilization. This paper proposes a novel routing metric to cope with the problem of selfish behavior (i.e., packet dropping) of mesh routers in a WMN. Our solution combines, in a cross-layer fashion, routing-layer observations of forwarding behavior with MAC-layer measurements of wireless link quality to select the most reliable and high-performance path. We integrated the proposed metric with a well-known routing protocol for wireless mesh networks, OLSR, and evaluated it using the NS2 simulator. The results show that our cross-layer metric accurately captures the path reliability, even when a high percentage of network nodes misbehave, thus considerably increasing the WMN performance.

The proliferation of peer-to-peer systems has led to the increasing deployment of dynamic, adaptive overlay networks that are designed to preserve application performance goals. While such networks provide increased performance and resiliency to benign faults, they are susceptible to attacks conducted by compromised overlay nodes, especially those targeting the adaptation mechanisms. In this work, we propose a lightweight, general solution to increase the resiliency of adaptive overlay networks. By locally aggregating and correlating network topology with system performance metrics such as latency and bandwidth, each node can check the consistency of the reported information and constrain the attacker's ability to lie about system metrics. As a result, each node can make better adaptation decisions. We demonstrate the susceptibility of adaptation mechanisms to malicious attacks and the utility of our solution through real-life deployments of mature, adaptive overlay-based systems.

Recent studies have shown that network coding can provide significant benefits to network protocols, such as increased throughput, reduced network congestion, higher reliability, and lower power consumption. The core principle of network coding is that intermediate nodes actively mix input packets to produce output packets. This mixing subjects network coding systems to a severe security threat, known as a pollution attack , where attacker nodes inject corrupted packets into the network. Corrupted packets propagate in an epidemic manner, depleting network resources and significantly decreasing throughput. Pollution attacks are particularly dangerous in wireless networks, where attackers can easily inject packets or compromise devices due to the increased network vulnerability. In this article, we address pollution attacks against network coding systems in wireless mesh networks. We demonstrate that previous solutions are impractical in wireless networks, incurring an unacceptable high degradation of throughput. We propose a lightweight scheme, DART, that uses time-based authentication in combination with random linear transformations to defend against pollution attacks. We further improve system performance and propose EDART, which enhances DART with an optimistic forwarding scheme. We also propose efficient attacker identification schemes for both DART and EDART that enable quick attacker isolation and the selection of attacker-free paths, achieving additional performance improvement. A detailed security analysis shows that the probability of a polluted packet passing our verification procedure is very low (less than 0.002% in typical settings). Performance results using the well-known MORE protocol and realistic link quality measurements from the Roofnet experimental testbed show that our schemes improve system performance over 20 times compared with previous solutions.

Recent work in multicast routing for wireless mesh networks has focused on metrics that estimate link quality to maximize throughput. Nodes must collaborate in order to compute the path metric and forward data. The assumption that all nodes are honest and behave correctly during metric computation, propagation, and aggregation, as well as during data forwarding, leads to unexpected consequences in adversarial networks where compromised nodes act maliciously. In this work, we identify novel attacks against high-throughput multicast protocols in wireless mesh networks. The attacks exploit the local estimation and global aggregation of the metric to allow attackers to attract a large amount of traffic. We show that these attacks are very effective against multicast protocols based on high-throughput metrics. We conclude that aggressive path selection is a double-edged sword: While it maximizes throughput, it also increases attack effectiveness in the absence of defense mechanisms. Our approach to defend against the identified attacks combines measurement-based detection and accusation-based reaction techniques. The solution accommodates transient network variations and is resilient against attempts to exploit the defense mechanism itself. A detailed security analysis of our defense scheme establishes bounds on the impact of attacks. We demonstrate both the attacks and our defense using ODMRP, a representative multicast protocol for wireless mesh networks, and SPP, an adaptation of the well-known ETX unicast metric to the multicast setting.

Online Social Networks (OSNs) such as Facebook have become ubiquitous in the past few years, counting hundreds of millions of people as members. OSNs allow users to form friendship relationships, join groups, communicate and share information with friends. The tremendous popularity of OSNs has naturally made them an appealing target for privacy compromising attacks. In this abstract we propose a novel attack against tightly knit OSN communities. Such (artificial) communities consist of users that know well each other and that are reluctant to accept other users as friends. Becoming a member of such a community may be only a first milestone for the attacker. Harvesting private information of members of such communities and following up with offline attacks may be the longer term benefit.

In the context of wireless mesh networks (WMNs), we ask the question whether a high level of security can be achieved while providing good communication performance. To answer this question, we examine two techniques designed and shown to improve throughput performance in WMNs: high-throughput routing and network coding. Although the advantages of using these techniques hold in a benign setting, it is not clear whether they can be preserved under an adversarial setting. We analyze these techniques and reveal a wide range of security vulnerabilities. We then investigate whether alternative schemes can be designed to be secure and still preserve most of the advantages achieved in benign settings.

This paper presents the first hierarchical byzantine fault-tolerant replication architecture suitable to systems that span multiple wide-area sites. The architecture confines the effects of any malicious replica to its local site, reduces message complexity of wide-area communication, and allows read-only queries to be performed locally within a site for the price of additional standard hardware. We present proofs that our algorithm provides safety and liveness properties. A prototype implementation is evaluated over several network topologies and is compared with a flat byzantine fault-tolerant approach. The experimental results show considerable improvement over flat byzantine replication algorithms, bringing the performance of byzantine replication closer to existing benign fault-tolerant replication techniques over wide area networks.

Virtual coordinate systems provide an accurate and efficient service that allows hosts on the Internet to determine the latency to arbitrary hosts without actively monitoring all of the nodes in the network. Many of the proposed systems were designed with the assumption that all of the nodes are altruistic. However, this assumption may be violated by compromised nodes acting maliciously to degrade the accuracy of the coordinate system. As numerous peer-to-peer applications come to rely on virtual coordinate systems to achieve good performance, it is critical to address the security of such systems. In this work, we demonstrate the vulnerability of decentralized virtual coordinate systems to insider (or Byzantine) attacks. We propose techniques to make the coordinate assignment robust to malicious attackers without increasing the communication cost. We use both spatial and temporal correlations to perform context-sensitive outlier analysis to reject malicious updates and prevent unnecessary and erroneous adaptations. We demonstrate the attacks and mitigation techniques in the context of a well-known virtual coordinate system using simulations based on three representative, real-life Internet topologies of hosts and corresponding Round Trip Times (RTT). We show the effects of the attacks and the utility of the mitigation techniques on the virtual coordinate system as seen by higher-level applications, elucidating the utility of deploying robust virtual coordinate systems as network services.

Virtual Coordinate System (VCS)-based routing provides a practical, efficient, and scalable means for point-to-point routing in wireless sensor networks. Several VCS-based routing protocols have been proposed in the last few years, all assuming that nodes behave correctly. However, many applications require deploying sensor networks in adversarial environments, making VCS-based routing protocols vulnerable to numerous attacks. In this article, we study the security of VCS-based routing protocols, with a focus on the unique component of VCS-based routing protocols, the virtual coordinate system. We first identify the security requirements of a correctly functioning VCS-based routing protocol and a set of novel attacks that can result in the violation of each of the identified requirements. The attacks target the underlying virtual coordinate system and can be mounted with low resources. However, they are epidemic in nature and are highly destructive to system performance. We then propose lightweight defense mechanisms designed specifically for resource-constrained sensor networks against each of the identified attacks. The proposed techniques require only local information on sensor nodes and take into account the unreliable nature of wireless links and network churn. Finally, we evaluate experimentally the impact of the attacks and the effectiveness of our defense mechanisms using a well-known VCS-based routing protocol, BVR. Our experiments show that the proposed techniques successfully mitigate all the identified attacks under a realistic link model and even at a high level of network churn.

Recent studies show that network coding can provide significant benefits to network protocols, such as increased throughput, reduced network congestion, higher reliability, and lower power consumption. The core principle of network coding is that intermediate nodes actively mix input packets to produce output packets. This mixing subjects network coding systems to a severe security threat, known as a \emph{pollution attack}, where attacker nodes inject corrupted packets into the network. Corrupted packets propagate in an epidemic manner, depleting network resources and significantly decreasing throughput. Pollution attacks are particularly dangerous in wireless networks, where attackers can easily inject packets or compromise devices due to the increased network vulnerability.

Hybrid networks consisting of cellular and Wi-Fi networks were proposed as a high-throughput architecture for cellular services. In such networks, devices equipped with cellular and Wi-Fi network cards access Internet services through the cellular base station. The Wi-Fi interface is used to provide a better service to clients that are far away from the base station, via multihop ad hoc paths. The modified trust model of hybrid networks generates a set of new security challenges as clients rely on intermediate nodes to participate effectively in the resource reservation process and data forwarding. In this paper, we introduce JANUS, a framework for scalable, secure, and efficient routing for hybrid cellular and Wi-Fi networks. JANUS uses a scalable routing algorithm with multiple channel access, for improved network throughput. In addition, it provides protection against selfish nodes through a secure crediting protocol and protection against malicious nodes through secure route establishment and data forwarding mechanisms. We evaluate JANUS experimentally and show that its performance is 85 percent of the optimum algorithm, improving with a factor greater than 50 percent over previous work. We evaluate the security overhead of JANUS against two types of attacks: less aggressive, but sufficient for some applications, selfish attacks and purely malicious attacks.

Multihop wireless networks rely on node cooperation to provide multicast services. The multihop communication offers increased coverage for such services but also makes them more vulnerable to insider (or Byzantine) attacks coming from compromised nodes that behave arbitrarily to disrupt the network. In this work, we identify vulnerabilities of on-demand multicast routing protocols for multihop wireless networks and discuss the challenges encountered in designing mechanisms to defend against them. We propose BSMR, a novel secure multicast routing protocol designed to withstand insider attacks from colluding adversaries. Our protocol is a software-based solution and does not require additional or specialized hardware. We present simulation results that demonstrate that BSMR effectively mitigates the identified attacks.

We compare two representative streaming systems using mesh-based and multiple tree-based overlay routing through deployments on the PlanetLab wide-area experimentation platform. To the best of our knowledge, this is the first study to compare streaming overlay architectures in real Internet settings, considering not only intuitive aspects such as scalability and performance under churn, but also less studied factors such as bandwidth and latency heterogeneity of overlay participants. Overall, our study indicates that mesh-based systems are superior for nodes with high bandwidth capabilities and low round trip times, while multi-tree based systems currently cope better with stringent real time deadlines under heterogeneous conditions.

Recent work in multicast routing for wireless mesh networks has focused on metrics that estimate link quality to maximize throughput. Nodes must collaborate in order to compute the path metric and forward data. The assumption that all nodes are honest and behave correctly during metric computation, propagation, and aggregation, as well as during data forwarding, leads to unexpected consequences in adversarial networks where compromised nodes act maliciously. In this work we identify novel attacks against high-throughput multicast protocols in wireless mesh networks. The attacks exploit the local estimation and global aggregation of the metric to allow attackers to attract a large amount of traffic. We show that these attacks are very effective against multicast protocols based on high-throughput metrics. This leads us to conclude that aggressive path selection is a double-edged sword: it maximizes throughput, but in the absence of protection mechanisms it also increases attack effectiveness. Our approach to mitigate the identified attacks combines measurement-based detection and accusation- based reaction techniques. The solution also accommodates transient network variations and is resilient against attempts to exploit the defense mechanism itself. We demonstrate the attacks and our defense using ODMRP, a representative multicast protocol for wireless mesh networks, and SPP, an adaptation of the well- known ETX unicast metric to the multicast setting.

Virtual coordinate system (VCS) based routing provides a practical, efficient and scalable means for point-to-point routing in wireless sensor networks. Several VCS-based routing protocols have been proposed in the last few years, all assuming that nodes behave correctly. However, many applications require deploying sensor networks in adversarial environments, making VCS-based routing protocols vulnerable to numerous attacks.

Wireless mesh networks (WMNs) have emerged as a promising technology that offers low-cost community wireless services. Security is critical for the deployment of these services. Previous work focused primarily on MAC and routing protocol security, while application-level security has received relatively little attention. In this paper we focus on providing data confidentiality for group communications in WMNs. We propose a new protocol framework, Secure Group Overlay Multicast (SeGrOM), that employs decentralized group membership, promotes localized communication, and exploits the wireless broadcast nature to achieve efficient and secure group communication. We analyze the performance and discuss the security properties of our protocols. We demonstrate through simulations that our protocols provide good performance and incur a significantly smaller overhead than a baseline centralized protocol optimized for WMNs.

Ah hoc networks offer increased coverage by using multihop communication. This architecture makes services more vulnerable to internal attacks coming from compromised nodes that behave arbitrarily to disrupt the network, also referred to as Byzantine attacks. In this work, we examine the impact of several Byzantine attacks performed by individual or colluding attackers. We propose ODSBR, the first on-demand routing protocol for ad hoc wireless networks that provides resilience to Byzantine attacks caused by individual or colluding nodes. The protocol uses an adaptive probing technique that detects a malicious link after log n faults have occurred, where n is the length of the path. Problematic links are avoided by using a route discovery mechanism that relies on a new metric that captures adversarial behavior. Our protocol never partitions the network and bounds the amount of damage caused by attackers. We demonstrate through simulations ODSBR's effectiveness in mitigating Byzantine attacks. Our analysis of the impact of these attacks versus the adversary's effort gives insights into their relative strengths, their interaction, and their importance when designing multihop wireless routing protocols.

Virtual coordinate systems provide an accurate and efficient service that allows hosts on the Internet to determine the latency to arbitrary hosts without actively monitoring all nodes in the network. Many of the proposed virtual coordinate systems were designed with the assumption that all of the nodes in the system are altruistic. However, this assumption may be violated by compromised nodes acting maliciously to degrade the accuracy of the coordinate system. As numerous peer-to-peer applications rely on virtual coordinate systems to achieve good performance, it is critical to address the security of such systems. In this work, we demonstrate the vulnerability of decentralized virtual coordinate systems to insider (or Byzantine) attacks. We propose techniques to make the coordinate assignment robust to malicious attackers without increasing the communication cost. We demonstrate the attacks and mitigation techniques in the context of a well-known distributed virtual coordinate system using simulations based on three representative, real-life Internet topologies of hosts and corresponding round trip times (RTT).

Most prior work on the use of key management algorithms to enable confidentiality of video delivery has been conducted in the context of IP Multicast. In this paper, we consider the unique challenges and opportunities of integrating key management algorithms in an overlay multicast system. We conduct a systematic and extensive performance evaluation of strategies for key dissemination in the context of an operational overlay broadcasting system on the Planetlab testbed using real traces of join/leave dynamics. We show that leveraging TCP in each hop of the overlay dissemination structure can significantly simplify reliable key dissemination. The performance can be further enhanced if convergence properties of overlays are considered. We show that using two specialized dissemination structures, one for data and one for keys, potentially achieves low overhead for key dissemination without sacrificing application performance. To our knowledge, this is the first paper to study key management schemes in an overlay context using real implementation and Internet experiments and the first to consider issues in resilient key dissemination with overlays.

In this paper we report on our experience of teaching a multi-expertise application-driven course in which upper-level undergraduate and entry-level graduate students from computer science, computer graphics technology, and educational science worked together to design, develop and evaluate a distance learning system. We describe the activities pursued in the class, the interactions between the various groups of students, as well as the challenges and advantages ensuing from the great variety of student backgrounds. The success of the course is measured in two ways. First, the class achieved the goal of building a distance learning system that surpasses the state of the art by improving the integration of the remote students into regular on-campus learning. Second, a survey conducted at the end of the course indicates that the application-driven, collaborative, and multi-expertise structure of the class provided a uniquely effective learning experience.

In this paper, we present an extensive study of key dissemination schemes in an overlay multicast context, and the first to involve actual implementation, real traces, and performance in Internet environments. Given that rekey traffic has stronger resilience requirements and is burstier than data traffic, we consider whether data and keys must be distributed using the same overlay or using two separate dissemination structures. Our key findings are: (i) a coupled architecture is effective in achieving resilient key dissemination. Using TCP in each hop of the dissemination structure (an opportunity unique to overlays) is effective in achieving resiliency in end-to-end key delivery. The performance can be further enhanced if convergence properties of overlays are considered; and (ii) a coupled architecture optimized for data delivery has high overheads, while a coupled architecture optimized for key delivery may not honor access bandwidth constraints of nodes. Distributing data and keys using separate overlays achieves low overhead for key dissemination while honoring access bandwidth constraints of nodes.

This paper presents the first hierarchical Byzantine fault-tolerant replication architecture suitable to systems that span multiple wide area sites. The architecture confines the effects of any malicious replica to its local site, reduces message complexity of wide area communication, and allows read-only queries to be performed locally within a site for the price of additional hardware. A prototype implementation is evaluated over several network topologies and is compared with a flat Byzantine fault-tolerant approach

Many multicast overlay networks maintain application-specific performance goals such as bandwidth, latency, jitter and loss rate by dynamically changing the overlay structure using measurement-based adaptation mechanisms. This results in an unstructured overlay where no neighbor selection constraints are imposed. Although such networks provide resilience to benign failures, they are susceptible to attacks conducted by adversaries that compromise overlay nodes. Previous defense solutions proposed to address attacks against overlay networks rely on strong organizational constraints and are not effective for unstructured overlays. In this work, we identify, demonstrate and mitigate insider attacks against measurement-based adaptation mechanisms in unstructured multicast overlay networks. The attacks target the overlay network construction, maintenance, and availability and allow malicious nodes to control significant traffic in the network, facilitating selective forwarding, traffic analysis, and overlay partitioning. We propose techniques to decrease the number of incorrect or unnecessary adaptations by using outlier detection. We demonstrate the attacks and mitigation techniques in the context of a mature, operationally deployed overlay multicast system, ESM, through real-life deployments and emulations conducted on the PlanetLab and DETER testbeds, respectively.

We propose Po/sup 2/V, a lightweight, network layer position verification scheme for distributed position services in multi-hop wireless networks. Our scheme uses adaptive transmitting power and multi-path polling to improve verification accuracy. We study different attacks against the verification scheme and propose corresponding mitigation techniques. Our analysis shows that while less expensive because no advanced techniques are required in the physical layer, Po/sup 2/V achieves a verification accuracy that meets the needs of many applications such as region-based access services, sensor monitoring, or ad hoc geocasting.

Survivable routing protocols are able to provide service in the presence of attacks and failures. The strongest attacks that protocols can experience are attacks where adversaries have full control of a number of authenticated nodes that behave arbitrarily to disrupt the network, also referred to as Byzantine attacks. This work examines the survivability of ad hoc wireless routing protocols in the presence of several Byzantine attacks: black holes, flood rushing, wormholes and overlay network wormholes. Traditional secure routing protocols that assume authenticated nodes can always be trusted, fail to defend against such attacks. Our protocol, ODSBR, is an on-demand wireless routing protocol able to provide correct service in the presence of failures and Byzantine attacks. We demonstrate through simulation its effectiveness in mitigating such attacks. Our analysis of the impact of these attacks versus the adversary’s effort gives insights into their relative strengths, their interaction and their importance when designing wireless routing protocols.

Sensor networks enable a wide range of applications in both military and civilian domains. However, the deployment scenarios, the functionality requirements, and the limited capabilities of these networks expose them to a wide-range of attacks against control traffic (such as wormholes, Sybil attacks, rushing attacks, etc). In this paper we propose a lightweight protocol called DICAS that mitigates these attacks by detecting, diagnosing, and isolating the malicious nodes. DICAS uses as a fundamental building block the ability of a node to oversee its neighboring nodes’ communication. On top of DICAS, we build a secure routing protocol, LSR, which in addition supports multiple node-disjoint paths. We analyze the security guarantees of DICAS and use ns-2 simulations to show its effectiveness against three representative attacks. Overhead analysis is conducted to prove the lightweight nature of DICAS.

In this paper we analyze the security vulnerabilities of positionbased routing protocols and virtual home region (VHR)-based distributed position service systems. We propose methods to protect the position information from both external and internal attackers. We then discuss and propose several mitigation mechanisms against position abuse by internal attackers that exploit the position service to trace their targets. Finally, we propose a position verification mechanism that allows the position service to verify that the positions reported by nodes are correct.

Adaptivity is an important mechanism used to handle the dynamic characteristics of the Internet infrastructure. It is commonly employed to allow distributed applications to monitor and subsequently respond to the ephemeral faults and variable performance that have characterized the Internet since its conception [1]. More recently, adaptation mechanisms were integrated into overlay networks, a technology proposed to improve on the perceived limitations of end-to-end communication using the existing Internet routing infrastructure.

We present DST, a dynamic spanning tree based algorithm, as a routing protocol for hybrid networks. It is scalable with the network size and achieves high throughput by taking advantage of multiple channels. DST maintains a close to optimal spanning tree of the network by using distributed topology trees. DST is fully dynamic and generates only O(log n) messages per update operation. We show experimentally that DST scales well with network size, making it ideal for metropolitan environment hybrid networks.

Group communication systems are high-availability distributed systems providing reliable and ordered message delivery, as well as a membership service, to group-oriented applications. Many such systems are built using a distributed client-server architecture where a relatively small set of servers provide service to numerous clients. In this work, we show how group communication systems can be enhanced with security services without sacrificing robustness and performance. More specifically, we propose several integrated security architectures for distributed client-server group communication systems. In an integrated architecture, security services are implemented in servers, in contrast to a layered architecture, where the same services are implemented in clients. We discuss performance and accompanying trust issues of each proposed architecture and present experimental results that demonstrate the superior scalability of an integrated architecture.

Group key agreement is a fundamental building block for secure peer group communication systems. Several group key management techniques were proposed in the last decade, all assuming the existence of an underlying group communication infrastructure to provide reliable and ordered message delivery as well as group membership information. Despite analysis, implementation, and deployment of some of these techniques, the actual costs associated with group key management have been poorly understood so far. This resulted in an undesirable tendency: on the one hand, adopting suboptimal security for reliable group communication, while, on the other hand, constructing excessively costly group key management protocols.This paper presents a thorough performance evaluation of five notable distributed key management techniques (for collaborative peer groups) integrated with a reliable group communication system. An in-depth comparison and analysis of the five techniques is presented based on experimental results obtained in actual local- and wide-area networks. The extensive performance measurement experiments conducted for all methods offer insights into their scalability and practicality. Furthermore, our analysis of the experimental results highlights several observations that are not obvious from the theoretical analysis.

Contributory group key agreement protocols generate group keys based on contributions of all group members. Particularly appropriate for relatively small collaborative peer groups, these protocols are resilient to many types of attacks. Unlike most group key distribution protocols, contributory group key agreement protocols offer strong security properties such as key independence and perfect forward secrecy. We present the first robust contributory key agreement protocol resilient to any sequence of group changes. The protocol, based on the Group Diffie-Hellman contributory key agreement, uses the services of a group communication system supporting virtual synchrony semantics. We prove that it provides both virtual synchrony and the security properties of Group Diffie-Hellman, in the presence of any sequence of (potentially cascading) node failures, recoveries, network partitions, and heals. We implemented a secure group communication service, Secure Spread, based on our robust key agreement protocol and Spread group communication system. To illustrate its practicality, we compare the costs of establishing a secure group with the proposed protocol and a protocol based on centralized group key management, adapted to offer equivalent security properties.

Group key agreement (GKA) is a fundamental building block for securing peer group communication systems (GCS). Several group key agreement protocols were proposed in the past, all assuming an underlying group communication infrastructure. This paper presents a performance evaluation of 5 notable GKA protocols integrated with a reliable group communication system (Spread). They are: centralized group key distribution (CKD), Burmester-Desmedt (BD), Steer et al. (STR), group Diffie-Hellman GDH) and tree-based group Diffie-Hellman (TGDH).. We present concrete results obtained in experiments on local- and wide-area networks. Our analysis of these results offers insights into their relative scalability and practicality.

Secure group communication is crucial for building distributed applications that work in dynamic environments and communicate over unsecured networks (e.g. the Internet). Key agreement is a critical part of providing security services for group communication systems. Most of the current contributory key agreement protocols are not designed to tolerate failures and membership changes during execution. In particular, nested or cascaded group membership events (such as partitions) are not accommodated. We present the first robust contributory key agreement protocols, resilient to any sequence of events while preserving the group communication membership and ordering guarantees.

The increasing popularity and diversity of collaborative applications prompts a need for highly secure and reliable communication platforms for dynamic peer groups. Security mechanisms for such groups tend to be both expensive and complex and their integration with reliable group communication services presents a formidable challenge, This paper discusses some important integration issues, reports on our implementation experience and provides experimental results. Our approach utilizes distributed group key management developed by the Cliques project. We enhance it to handle processor and network faults (under a fail-stop or crash-and-recover model) and asynchronous membership events (such as joins, leaves, merges and network partitions). Our approach leverages the strong properties provided by the Spread group communication system, such as message ordering, clean failure semantics and a membership service. The result of this work is a secure group communications layer and an API that provide the application programmer with both standard group communication services and flexible security services.