A Survey on Cyber-Security of Connected and Autonomous Vehicles (CAVs)

Sun, Xiaoqiang; Yu, F. Richard; Zhang, Peng

doi:10.1109/tits.2021.3085297

Cited by 163 publications

(73 citation statements)

References 120 publications

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“…CAN [52], [50], [51], [26] Eavesdropping, DoS attack, replay attack and unauthorized data transmission, bus fuzzing/frame falsifying/injection attack Confidentiality/authenticity/privacy of CAN messages, Intrusion Detection System (IDS) based defense techniques, securing telematics ECUs, cryptography, clock skew estimation of CAN messages, network segmentation. LiDAR [50], [53], [54] Spoofing, jamming, random modulation, signals counterfeiting Dynamic watermarking, reduction of signal-receiving angle, pulses transmission in random directions, and pulses' waveforms randomization, device fingerprinting, data authentication.…”

Section: Ec-cav Subsystemsmentioning

confidence: 99%

“…Radar [50], [53] Spoofing, jamming, signals counterfeiting Signal filtering, Spatio-Temporal Challenge-Response (STCR). GPS [50], [52], [54] Location trailing, spoofing, signals counterfeiting Receiver autonomous integrity monitoring (RAIM), receiver-autonomous angle-of-arrival spoofing countermeasure, signal filtering. Image sensors [50], [53], [55], [54] Camera blinding, adversarial images injection Deploy multiple cameras (redundancy), near-infrared-cut filter, special optics.…”

Section: Ec-cav Subsystemsmentioning

confidence: 99%

“…Replay attacks can be used to manipulate the vehicle locations by re-transmitting the previous messages [79]. The adversary can target LiDAR [80], CAN bus [50], keyless entry systems [54], authorization and key agreement protocols [52], or communication between CAVs and RSU [26] in EC-CAVs that can further lead to unauthorized data transmission, Eavesdropping, or Sniffing. Table V presents a synopsis of defenses against replay attacks.…”

Section: Defenses Against Replay Attackmentioning

confidence: 99%

See 2 more Smart Citations

An investigation of cyber-attacks and security mechanisms for connected and autonomous vehicles

Gupta¹,

Maple²

2023

Preprint

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<p>Edge Computing-based Connected Autonomous Vehicles (EC-CAVs) can fulfill the emerging demand for smart transportation on a global scale. Such innovations to transportation ecosystems can bring manyfold benefits from fully autonomous driving services to proactive vehicle monitoring and traffic management. Given the complexity involved in the deployment of EC-CAVs, zero-tolerance safety and security measures must be incorporated to avert vehicle immobilization, road accidents, disclosure of sensitive data, or any potential threats. This paper presents a reference architecture of EC-CAVs to investigate existing and emerging cyber-threats for deriving a common attack taxonomy for the EC-CAVs ecosystem. Subsequently, a comprehensive survey of security mechanisms is presented that can ensure safe and secure transportation of passengers from one destination to another using an EC-CAVs ecosystem.</p>

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Section: Ec-cav Subsystemsmentioning

confidence: 99%

Section: Ec-cav Subsystemsmentioning

confidence: 99%

Section: Defenses Against Replay Attackmentioning

confidence: 99%

See 1 more Smart Citation

An investigation of cyber-attacks and security mechanisms for connected and autonomous vehicles

Gupta¹,

Maple²

2023

Preprint

View full text Add to dashboard Cite

show abstract

“…El‐Rewini et al (2020) describe vehicular cybersecurity challenges using a hierarchical framework to isolate threats and attacks in three layers; sensing, communication, and control. Considering a broad scope of attack vectors against inter‐ and intravehicular communication, Sun et al (2021) discuss cybersecurity vulnerabilities related to autonomous cars. Similarly, in the maritime domain, Silverajan et al (2018) describe relevant attack surfaces for unmanned smart ships.…”

Section: Introductionmentioning

confidence: 99%

Hijacking of unmanned surface vehicles: A demonstration of attacks and countermeasures in the field

Solnør

Volden

Gryte

et al. 2022

Journal of Field Robotics

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Driven by advances in information and communication technologies, an increasing number of industries embrace unmanned and autonomous vehicles for services, such as public transportation, shipping, mapping, and remote surveillance. Unfortunately, these vehicles are vulnerable to passive and active cyber-physical attacks that can be used for industrial espionage and hijacking attempts. Since attackers can use hijacked vehicles as weapons in terrorist attacks, ensuring the secure operation of such vehicles is critical to prevent the attacks from causing dire financial consequences, or worse, the loss of human lives. This study is motivated by the observation that most cybersecurity studies provide superficial, high-level descriptions of vulnerabilities and attacks, and the true impact of the described attacks remains unclear. To address this problem, we demonstrate advanced manipulation attacks against an underactuated Unmanned Surface Vehicle (USV) which results in successful hijackings. Using state-of-the-art cryptography, we also show how the signal transmission can be secured to avoid hijacking attempts actively steering the vehicle off course. Through field experiments, we demonstrate how the attacks affect the closed-loop guidance, navigation, and control system and how the proposed countermeasures prevent these attacks from being successful. Our study is unique in that we provide a complete description of the attacked USV and give a detailed analysis of how spoofed navigation estimates affect the closed-loop behavior of the underactuated USV.

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“…There has been an increasing interest in security vulnerabilities for connected and autonomous vehicle (CAV) coordination [8], [9], [10], [11], [12], [13]. In particular, jamming attack is one of the main forms of Denial-of-Service (DOS) attacks in DSRC.…”

Section: Introductionmentioning

confidence: 99%

Securing Signal-free Intersections against Strategic Jamming Attacks: A Macroscopic Approach

Bai¹,

Amin²,

Wang³

et al. 2022

Preprint

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We consider the security-by-design of a signal-free intersection for connected and autonomous vehicles in the face of strategic jamming attacks. We use a fluid model to characterize macroscopic traffic flow through the intersection, where the saturation rate is derived from a vehicle coordination algorithm. We model jamming attacks as sudden increase in communication latency induced on vehicle-to-infrastructure connectivity; such latency triggers the safety mode for vehicle coordination and thus reduces the intersection saturation rate. A strategic attacker selects the attacking rate, while a system operator selects key design parameters, either the saturation rate or the recovery rate. Both players' actions induce technological costs and jointly determine the mean travel delay. By analyzing the equilibrium of the security game, we study the preferable level of investment in the intersection's nominal discharging capability or recovery capability, for balance between hardware/infrastructure cost and security-by-design.

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A Survey on Cyber-Security of Connected and Autonomous Vehicles (CAVs)

Cited by 163 publications

References 120 publications

An investigation of cyber-attacks and security mechanisms for connected and autonomous vehicles

An investigation of cyber-attacks and security mechanisms for connected and autonomous vehicles

Hijacking of unmanned surface vehicles: A demonstration of attacks and countermeasures in the field

Securing Signal-free Intersections against Strategic Jamming Attacks: A Macroscopic Approach

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