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1. An Interaction Provenance-based Trust Management Scheme For Connected Vehicles

   https://doi.org/10.1109/CCNC49033.2022.9700580  

   Hoque, Mohammad Aminul; Hasan, Ragib (January 2022, IEEE 19th Annual Consumer Communications & Networking Conference (CCNC))

   Connected vehicles (CVs) have facilitated the development of intelligent transportation system that supports critical safety information sharing with minimum latency. However, CVs are vulnerable to different external and internal attacks. Though cryptographic techniques can mitigate external attacks, preventing internal attacks imposes challenges due to authorized but malicious entities. Thwarting internal attacks require identifying the trustworthiness of the participating vehicles. This paper proposes a trust management framework for CVs using interaction provenance that ensures privacy, considers both in-vehicle and vehicular network security incidents, and supports flexible security policies. For this purpose, we present an interaction provenance recording and trust management protocol. Different events are extracted from interaction provenance, and trustworthiness is calculated using fuzzy policies based on the events. 

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2. Secure Control of Connected and Automated Vehicles Using Trust-Aware Robust Event-Triggered Control Barrier Functions

   Ahmad, Sabbir H; Sabouni, Ehsan; Dickson, Akua; Xiao, Wei; Cassandras, CG; Li, Wenchao (February 2024, Symposium on Vehicles Security and Privacy (VehicleSec) 2024)

   We address the security of a network of Connected and Automated Vehicles (CAVs) cooperating to safely navigate through a conflict area (e.g., traffic intersections, merging roadways, roundabouts). Previous studies have shown that such a network can be targeted by adversarial attacks causing traffic jams or safety violations ending in collisions. We focus on attacks targeting the V2X communication network used to share vehicle data and consider as well uncertainties due to noise in sensor measurements and communication channels. To combat these, motivated by recent work on the safe control of CAVs, we propose a trust-aware robust event-triggered decentralized control and coordination framework that can provably guarantee safety. We maintain a trust metric for each vehicle in the network computed based on their behavior and used to balance the tradeoff between conservativeness (when deeming every vehicle as untrustworthy) and guaranteed safety and security. It is important to highlight that our framework is invariant to the specific choice of the trust framework. Based on this framework, we propose an attack detection and mitigation scheme which has twofold benefits: (i) the trust framework is immune to false positives, and (ii) it provably guarantees safety against false positive cases. We use extensive simulations (in SUMO and CARLA) to validate the theoretical guarantees and demonstrate the efficacy of our proposed scheme to detect and mitigate adversarial attacks. 

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3. Hamraz: Resilient Partitioning and Replication

   https://doi.org/10.1109/SP46214  

   Li, Xiao; Houshmand, Farzin (January 2022, S&P'22 (IEEE Symposium on Security and Privacy))

   Inter-organizational systems where subsystems with partial trust need to cooperate are common in healthcare, finance and military. In the face of malicious Byzantine attacks, the ultimate goal is to assure end-to-end policies for the three aspects of trustworthiness: confidentiality, integrity and availability. In contrast to confidentiality and integrity, provision and validation of availability has been often sidestepped. This paper guarantees end-to-end policies simultaneously for all the three aspects of trustworthiness. It presents a security-typed object-based language, a partitioning transformation, an operational semantics, and an information flow type inference system for partitioned and replicated classes. The type system provably guarantees that well-typed methods enjoy noninterference for the three properties, and that their types quantify their resilience to Byzantine attacks. Given a class and the specification of its end-to-end policies, the Hamraz tool applies type inference to automatically place and replicate the fields and methods of the class on Byzantine quorum systems, and synthesize trustworthy-by-construction distributed systems. The experiments show the resiliency of the resulting systems; they can gracefully tolerate attacks that are as strong as the specified policies. 

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4. R-CAV: On-Demand Edge Computing Platform for Connected Autonomous Vehicles

   https://doi.org/10.1109/WF-IoT51360.2021.9595160  

   Hoque, Mohammad Aminul; Hasan, Raiful; Hasan, Ragib (June 2021, Proceedings of the IEEE World Forum on the Internet of Things (WF-IOT))

   Connected Autonomous Vehicles (CAVs) have achieved significant improvements in recent years. The CAVs can share sensor data to improve autonomous driving performance and enhance road safety. CAV architecture depends on roadside edge servers for latency-sensitive applications. The roadside edge servers are equipped with high-performance embedded edge computing devices that perform calculations with low power requirements. As the number of vehicles varies over different times of the day and vehicles can request for different CAV applications, the computation requirements for roadside edge computing platform can also vary. Hence, a framework for dynamic deployment of edge computing platforms can ensure CAV applications’ performance and proper usage of the devices. In this paper, we propose R-CAV – a framework for drone-based roadside edge server deployment that provides roadside units (RSUs) based on the computation requirement. Our proof of concept implementation for object detection algorithm using Nvidia Jetson nano demonstrates the proposed framework's feasibility. We posit that the framework will enhance the intelligent transport system vision by ensuring CAV applications’ quality of service. 

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5. Evaluations of Cyberattacks on Cooperative Control of Connected and Autonomous Vehicles at Bottleneck Points

   Ahmad, HM; Sabouni, Ehsan; Xiao, Wei; Cassandras, Christos G; Li, Wenchao (February 2023, Symposium on Vehicles Security and Privacy (VehicleSec) 2023)

   In this paper we analyze the effect of cyberattacks on cooperative control of connected and autonomous vehicles (CAVs) at traffic bottleneck points. We focus on three types of such bottleneck points including merging roadways, intersections and roundabouts. The coordination amongst CAVs in the network is achieved in a decentralized manner whereby each CAV formulates its own optimal control problem and solves it onboard in real time. A roadside unit is introduced to act as the coordinator that communicates and exchanges relevant data with the CAVs through wireless V2X communication. We show that this CAV setup is vulnerable to various cyberattacks such as Sybil attack, jamming attack and false data injection attack. Results from our simulation experiments call attention to the extent to which such attacks may jeopardize the coordination performance and the safety of the CAVs. 

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