Abstract

Vehicle-to-everything (V2X) communication promises a wide range of benefits for society. Within future V2X-enabled intelligent transportation systems, vehicle-to-vehicle (V2V) communication will allow vehicles to directly exchange messages, improving their situational awareness and allowing drivers or (semi-)autonomous vehicles to avoid collisions, particularly in non-line-of-sight scenarios. Thus, V2V has the potential to reduce annual vehicular crashes and fatalities by hundreds of thousands. Cellular Vehicle-to-Everything (C-V2X) is rapidly supplanting older V2V protocols and will play a critical role in achieving these outcomes. As extremely low latency is required to facilitate split-second collision avoidance maneuvers, ensuring the availability of C-V2X is imperative for safe and secure intelligent transportation systems. However, little work has analyzed the physical- (PHY) and MAC-layer resilience of C-V2X against intelligent, protocol-aware denial-of-service (DoS) attacks by stealthy adversaries. In this thesis, we expose fundamental security vulnerabilities in the PHY- and MAC-layer designs of C-V2X and demonstrate how they can be exploited to devastating effect by devising two novel, intelligent DoS attacks against C-V2X: targeted sidelink jamming and sidelink resource exhaustion. Our attacks demonstrate different ways an intelligent adversary can dramatically degrade the availability of C-V2X for one or many vehicles, increasing the likelihood of fatal vehicle collisions. Through hardware experiments with software-defined radios (SDRs) and state-of-the-art C-V2X devices in combination with extensive MATLAB simulation, we demonstrate the viability and effectiveness of our attacks. We show that targeted sidelink jamming can reduce a targeted vehicle's packet delivery ratio by 90% in a matter of seconds, while sidelink resource exhaustion can reduce C-V2X channel throughput by up to 50% in similarly short order. We further provide and validate detection techniques for each attack based on cluster and regression analysis techniques and propose promising, preliminary approaches to mitigate the underlying vulnerabilities that we expose in the PHY/MAC layers of C-V2X.

Publication Date

7-30-2021

Document Type

Thesis

Student Type

Graduate

Degree Name

Computing Security (MS)

Department, Program, or Center

Department of Computing Security (GCCIS)

Advisor

Hanif Rahbari

Advisor/Committee Member

Sumita Mishra

Advisor/Committee Member

Amlan Ganguly

Campus

RIT – Main Campus

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