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Can cyberattacks on adaptive cruise control vehicles be effectively detected? | IEEE Conference Publication | IEEE Xplore

Can cyberattacks on adaptive cruise control vehicles be effectively detected?


Abstract:

Automated Vehicles (AVs), particularly those with Adaptive Cruise Control (ACC), are increasingly integral to intelligent transportation systems, but they bring new cyber...Show More

Abstract:

Automated Vehicles (AVs), particularly those with Adaptive Cruise Control (ACC), are increasingly integral to intelligent transportation systems, but they bring new cybersecurity challenges. This study explores the subtleties of cyberattacks targeting ACC vehicles, specifically through false data injection, and assesses their impact on traffic dynamics. We innovatively adapt and implement strategically designed cyberattacks in simulations, providing a realistic evaluation of their effects on traffic. Our approach not only synthesizes these attacks but also rigorously tests their detectability against state-of-the-art detection algorithms. The findings reveal the intrinsic difficulty in detecting such stealthily designed attacks, highlighting a significant gap in current cybersecurity measures. Despite the precision of our detection methods, the low recall rates emphasize the stealthiness of these attacks. The open-sourced experiment code is made available at https://github.com/tianyi17/simulations_IV24. This research accentuates the urgent need for more sophisticated detection and defense strategies to protect ACC vehicles against evolving cyber threats, ensuring the reliability and safety of future transportation systems.
Date of Conference: 02-05 June 2024
Date Added to IEEE Xplore: 15 July 2024
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ISSN Information:

Conference Location: Jeju Island, Korea, Republic of

I. Introduction

Automated vehicles (AVs), with advancements like improved traffic flow [1] and reduced energy consumption [2], face new cybersecurity challenges [3]. Adaptive Cruise Control (ACC) vehicles, the first generation of AVs, are particularly vulnerable to cyberattacks that subtly alter driving behavior, leading to significant disruptions in traffic efficiency [4], [5]. These cyberattacks, often involving false data injection to sensor systems or control commands [6] – [10], can have widespread impacts. Even minor manipulations can escalate to greater traffic congestion and increased fuel consumption. In mixed traffic systems, comprising both ACC vehicles and human-driven vehicles, the ripple effects of such attacks magnify, resulting in decreased traffic throughput and heightened energy usage [6]. These emergent threats highlight the necessity for enhanced cybersecurity in AVs. Ensuring the security of these vehicles is pivotal in maintaining the anticipated benefits and operational efficiency of future transportation systems. A detailed examination of potential cyberattack strategies on AVs is available in [4].

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