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Consider a fleet of autonomous vehicles traversing an adversarial terrain that includes obstacles and mines. The goal of the fleet is to ensure that they can complete their mission safely (with minimal casualty) and efficiently (as quickly as possible). In Distributed Coordinated Fleet Management (DCFM), fleet members coordinate with one another while traversing the terrain, e.g., a vehicle encountering an obstacle at a location l can inform other agents so that they can recompute their route to avoid l. In this paper, we consider the problem of cyber-resilient DCFM, i.e., DCFM in an en- vironment where the adversary can additionally tamper with the cyber-communication performed by the fleet members. Our framework, DRIFT, enables fleet members to coordinate in the presence of such adversaries. Our extensive evaluations demonstrate that DRIFT can achieve a high degree of safety and efficiency against a large spectrum of communication adversaries. 

Modern autonomous vehicles are increasingly infused with sensors, electronics, and software software. One consequence is that they are getting increasingly susceptible to cyber-attacks. However, awareness of cybersecurity challenges for automotive systems remains low. In this paper, we consider the problem of developing a virtual reality (VR) infrastructure that can enable users who are not necessarily experts in automotive security to explore vulnerabilities arising from compromised ranging sensors. A key requirement for such platforms is to develop natural, intuitive scenarios that enable the user to experience security challenges and impact. We discuss the challenges in developing such scenarios, and develop a solution that enables exploration of jamming and spoong attacks. Our solution is integrated into a VR platform for automotive se- curity exploration called IVE (Immersive Virtual Environment). It combines realistic driving with a rst-person view, user interaction, and sound eects to provide all the benets of a real-life simulation without the consequences. 

We consider the cybersecurity challenges arising from communications between autonomous vehicles and smart infrastructures. In particular, we consider coordination between vehicles and Reduced Speed Work Zones (RSWZ). Malicious or tampered communica- tions between these entities can have catastrophic consequences. We discuss methods for the analysis of such attacks. In particular, we show how to generate congurable, eective vehicular trajecto- ries for exploring such attacks and how to utilize such trajectories in identifying impactful attacks and evaluating defenses. 

Security is a critical challenge in emergent autonomous vehicles. However, the security challenges in automotive systems are not widely understood even in the cybersecurity community. To address this problem, we develop an adaptable exploration platform for automotive security. This platform enables users to gain hands-on experience and insights into security vulnerabilities. We discuss specic challenges and prerequisites involved in designing such an exploration tool. We demonstrate the platform’s capabilities by exploring automotive ranging sensor attacks. 

A critical requirement for robust, optimized, and secure design of vehicular systems is the ability to do system-level exploration, i.e., comprehend the interactions involved among ECUs, sensors, and communication interfaces in realizing systemlevel use cases and the impact of various design choices on these interactions. This must be done early in the system design to enable the designer to make optimal design choices without requiring a cost-prohibitive design overhaul. In this paper, we develop a virtual prototyping environment for the modeling and simulation of vehicular systems. Our solution, VIVE, is modular and configurable, allowing the user to conveniently introduce new system-level use cases. Unlike other related simulation environments, our platform emphasizes coordination and communication among various vehicular components and just the abstraction of the necessary computation of each electronic control unit. We discuss the ability of VIVE to explore the interactions between a number of realistic use cases in the automotive domain. We demonstrate the utility of the platform, in particular, to create real-time in-vehicle communication optimizers for various optimization targets. We also show how to use such a prototyping environment to explore vehicular security compromises. Furthermore, we showcase the experimental integration and validation of the platform with a hardware setup in a real-time scenario. 

A modern automobile system is a safety-critical distributed embedded system that incorporates more than a hundred Electronic Control Units, a wide range of sensors, and actuators, all connected with several in-vehicle networks. Obviously, integration of these heterogeneous components can lead to subtle errors that can be possibly exploited by malicious entities in the field, resulting in catastrophic consequences. We develop a prototyping platform to enable the functional safety and security exploration of automotive systems. The platform realizes a unique, extensible virtualization environment for the exploration of vehicular systems. The platform includes a CAN simulator that mimics the vehicular CAN bus to interact with various ECUs, together with sensory and actuation capabilities. We show how to explore these capabilities in the safety and security exploration through the analysis of a representative vehicular use case interaction.