Security vulnerabilities of connected vehicle streams and their impact on cooperative driving

Amoozadeh, Mani; Raghuramu, Arun; Chuah, Chen‐Nee; Ghosal, Dipak; Zhang, H. Michael; Rowe, Jeff; Levitt, Karl N.

doi:10.1109/mcom.2015.7120028

Cited by 339 publications

(196 citation statements)

References 15 publications

(18 reference statements)

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“…According to Petit and Shladover (2015), global navigation satellite systems (GNSS) spoofing and injection of fake messages into the communication between vehicles are the two most likely and most severe attacks for vehicle automation. Amoozadeh et al (2015) simulated message falsification and radio jamming attacks in a CACC vehicle stream, influencing the vehicles' acceleration and space gap, respectively. These researchers showed that security attacks could compromise traffic safety, causing stream instability and rear-end collisions.…”

Section: Literature Resultsmentioning

confidence: 99%

Policy and society related implications of automated driving: A review of literature and directions for future research

Milakis

Arem

Wee

2017

Journal of Intelligent Transportation Systems

700

383

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KEYWORDSautomated driving; first, second, and third order impacts; policy and societal implications; ripple effect ABSTRACTIn this paper, the potential effects of automated driving that are relevant to policy and society are explored, findings discussed in literature about those effects are reviewed and areas for future research are identified. The structure of our review is based on the ripple effect concept, which represents the implications of automated vehicles at three different stages: first-order (traffic, travel cost, and travel choices), second-order (vehicle ownership and sharing, location choices and land use, and transport infrastructure), and third-order (energy consumption, air pollution, safety, social equity, economy, and public health). Our review shows that first-order impacts on road capacity, fuel efficiency, emissions, and accidents risk are expected to be beneficial. The magnitude of these benefits will likely increase with the level of automation and cooperation and with the penetration rate of these systems. The synergistic effects between vehicle automation, sharing, and electrification can multiply these benefits. However, studies confirm that automated vehicles can induce additional travel demand because of more and longer vehicle trips. Potential land use changes have not been included in these estimations about excessive travel demand. Other third-order benefits on safety, economy, public health and social equity still remain unclear. Therefore, the balance between the short-term benefits and long-term impacts of vehicle automation remains an open question.

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Section: Literature Resultsmentioning

confidence: 99%

Policy and society related implications of automated driving: A review of literature and directions for future research

Milakis

Arem

Wee

2017

Journal of Intelligent Transportation Systems

700

383

View full text Add to dashboard Cite

show abstract

“…Similar to our work, previous work also identifies data spoofing as a realistic attack vector in the CV environment. Amoozadeh et al studied the V2V-based automated vehicle platoon system, and found that spoofed attacks can cause rear-end collision or significant instability [17]. A more recent work summarizes a comprehensive list of data spoofing attack sources including not only DSRC but also other sensors such as GPS [23].…”

Section: Related Workmentioning

confidence: 99%

Exposing Congestion Attack on Emerging Connected Vehicle based Traffic Signal Control

Chen

Yu-cheng²,

Feng

et al. 2018

Proceedings 2018 Network and Distributed System Security Symposium

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Abstract-Connected vehicle (CV) technology will soon transform today's transportation systems by connecting vehicles and the transportation infrastructure through wireless communication. Having demonstrated the potential to greatly improve transportation mobility efficiency, such dramatically increased connectivity also opens a new door for cyber attacks. In this work, we perform the first detailed security analysis of the nextgeneration CV-based transportation systems. As a first step, we target the USDOT (U.S. Department of Transportation) sponsored CV-based traffic control system, which has been tested and shown high effectiveness in real road intersections. In the analysis, we target a realistic threat, namely CV data spoofing from one single attack vehicle, with the attack goal of creating traffic congestion.We first analyze the system design and identify data spoofing strategies that can potentially influence the traffic control. Based on the strategies, we perform vulnerability analysis by exhaustively trying all the data spoofing options for these strategies to understand the upper bound of the attack effectiveness. For the highly effective cases, we analyze the causes and find that the current signal control algorithm design and implementation choices are highly vulnerable to data spoofing attacks from even a single attack vehicle. These vulnerabilities can be exploited to completely reverse the benefit of the CV-based signal control system by causing the traffic mobility to be 23.4% worse than that without adopting such system. We then construct practical exploits and evaluate them under real-world intersection settings. The evaluation results are consistent with our vulnerability analysis, and we find that the attacks can even cause a blocking effect to jam an entire approach. In the jamming period, 22% of the vehicles need to spend over 7 minutes for an original halfminute trip, which is 14 times higher. We also discuss defense directions leveraging the insights from our analysis.

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“…() evaluated the impact of cyberattacks on freeway traffic using the optimal control and multiobjective optimization strategies; Amoozadeh et al. () investigated the effects of security attacks on the connected vehicle platoon by using VEhicular NeTwork Open Simulator (VENTOS) framework; and Dadras et al. () demonstrated that an attacker can cause the platoon to be unstable and even serious injury or death.…”

Section: Literature Reviewmentioning

confidence: 99%

Spreading Patterns of Malicious Information on Single‐Lane Platooned Traffic in a Connected Environment

Wang

et al. 2018

Computer aided Civil Eng

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The connected vehicle can be easily attacked by cyber threats due to its communication through the wireless network in an open‐access environment. But very few studies have paid attention to the spreading of malicious information such as denial of service, message delay/replay, and eavesdropping generated by cyberattacks. To this end, this article introduces an analytical model, named vehicular malicious information propagation (VMIP), which integrates a classical epidemic model through two‐layer system structure, in which the upper layer describes the malicious information spreading and the lower describes the traffic flow dynamics. The proposed VMIP model is designated for platooned (one‐lane, particularly) traffic. Numerical experiments show the proposed model can efficiently describe the interactions between traffic dynamics and malicious information spreading; and the information propagation highly depends on traffic flow patterns. This article is expected to contribute to a better understanding of the impacts of cyberattacks on traffic and lays a foundation for future development of control strategies on mitigating the disastrous effects of cyberattacks.

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Security vulnerabilities of connected vehicle streams and their impact on cooperative driving

Cited by 339 publications

References 15 publications

Policy and society related implications of automated driving: A review of literature and directions for future research

Policy and society related implications of automated driving: A review of literature and directions for future research

Exposing Congestion Attack on Emerging Connected Vehicle based Traffic Signal Control

Spreading Patterns of Malicious Information on Single‐Lane Platooned Traffic in a Connected Environment

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