Short paper: Establishing trust in a vehicular network

Machado, Raquel G.; Venkatasubramanian, Krishna K.

doi:10.1109/vnc.2013.6737611

Cited by 8 publications

(3 citation statements)

References 7 publications

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“…Obviously, the information being exchanged between the vehicles can be extended with more details about position, speed and various other sensor data readings. Moreover, while our framework allows a vehicle to explicitly trust one or more neighbouring vehicles, it would be interesting to allow multiple trust levels [17] that can be based on historical interactions.…”

Section: Discussionmentioning

confidence: 99%

Model-Based Membership Verification in Vehicular Platoons

Asplund

2015

2015 IEEE International Conference on Dependable Systems and Networks Workshops

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Abstract-Cooperative vehicular systems have the potential to significantly increase traffic efficiency and safety. However, they also raise the question of to what extent information that is received from other vehicles can be trusted. In this paper we present a novel approach for increasing the trustworthiness of cooperative driving through a model-based approach for verifying membership views in vehicular platoons. We define a formal model for platoon membership, cooperative awareness claims, and membership verification mechanisms. With the help of a satisfiability solver, we are able to quantitatively analyse the impact of different system parameters on the verifiability of received information. Our results demonstrate the importance of cross validating received messages, as well as the surprising difficulty in establishing correct membership views despite powerful verification mechanisms.

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Section: Discussionmentioning

confidence: 99%

Model-Based Membership Verification in Vehicular Platoons

Asplund

2015

2015 IEEE International Conference on Dependable Systems and Networks Workshops

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“…Their method therefore makes contributions to building centralized trust management system. Machado and Venkatasubramanian [15] aim to aggregate advantages of both centralized and distributed trust computation. The authors categorize the messages exchanged in VANET into alerts and reports; alerts are time-critical in response to an incident while reports are evidence to evaluate quality of alerts.…”

Section: Related Workmentioning

confidence: 99%

Anomaly Detection for Internet of Vehicles: A Trust Management Scheme with Affinity Propagation

Yang

Liu

et al. 2016

Mobile Information Systems

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Anomaly detection is critical for intelligent vehicle (IV) collaboration. Forming clusters/platoons, IVs can work together to accomplish complex jobs that they are unable to perform individually. To improve security and efficiency of Internet of Vehicles, IVs’ anomaly detection has been extensively studied and a number of trust-based approaches have been proposed. However, most of these proposals either pay little attention to leader-based detection algorithm or ignore the utility of networked Roadside-Units (RSUs). In this paper, we introduce a trust-based anomaly detection scheme for IVs, where some malicious or incapable vehicles are existing on roads. The proposed scheme works by allowing IVs to detect abnormal vehicles, communicate with each other, and finally converge to some trustworthy cluster heads (CHs). Periodically, the CHs take responsibility for intracluster trust management. Moreover, the scheme is enhanced with a distributed supervising mechanism and a central reputation arbitrator to assure robustness and fairness in detecting process. The simulation results show that our scheme can achieve a low detection failure rate below 1%, demonstrating its ability to detect and filter the abnormal vehicles.

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“…Road-Side Units) into consideration when making decisions regarding content plausibility. [18], [22] and [28] all propose reputation-based systems to pinpoint the attackers that inject bogus information to the network. These systems defend against the use of blatantly wrong or implausible values, which led our bots to carefully craft their fake congestion information sent.…”

Section: Related Workmentioning

confidence: 99%

Congestion Attacks to Autonomous Cars Using Vehicular Botnets

Garip¹,

Gürsoy²,

Reiher³

et al. 2015

Proceedings 2015 Workshop on Security of Emerging Networking Technologies

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The increasing popularity and acceptance of VANETs will make the deployment of autonomous vehicles easier and faster since the VANET will reduce dependence on expensive sensors. However, these benefits are counterbalanced by possible security attacks. We demonstrate a VANET-based botnet attack in an autonomous vehicle scenario that can cause serious congestion by targeting hot spot road segments. We show via simulation that the attack can increase the trip times of the cars in the targeted area by orders of magnitude. After 5 minutes, the targeted road becomes completely unusable. More importantly, the effect of such an attack is not confined to a specific hotspot; the congestion can spread to multiple roads and significantly affect the entire urban grid. We show that current countermeasures are not effective, and point to new possible defenses. Permission to freely reproduce all or part of this paper for noncommercial purposes is granted provided that copies bear this notice and the full citation on the first page. Reproduction for commercial purposes is strictly prohibited without the prior written consent of the Internet Society, the first-named author (for reproduction of an entire paper only), and the author's employer if the paper was prepared within the scope of employment.

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Short paper: Establishing trust in a vehicular network

Cited by 8 publications

References 7 publications

Model-Based Membership Verification in Vehicular Platoons

Model-Based Membership Verification in Vehicular Platoons

Anomaly Detection for Internet of Vehicles: A Trust Management Scheme with Affinity Propagation

Congestion Attacks to Autonomous Cars Using Vehicular Botnets

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