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Eviction of Misbehaving and Faulty Nodes in Vehicular Networks
Open accessAbstract
Vehicular networks (VNs) are emerging, among civilian applications, as a convincing instantiation of the mobile networking technology. However, security is a critical factor and a significant challenge to be met. Misbehaving or faulty network nodes have to be detected and prevented from disrupting network operation, a problem particularly hard to address in the life-critical VN environment. Existing networks rely mainly on node certificate revocation for attacker eviction, but the lack of an omnipresent infrastructure in VNs may unacceptably delay the retrieval of the most recent and relevant revocation information; this will especially be the case in the early deployment stages of such a highly volatile and large-scale system. In this paper, we address this specific problem. We propose protocols, as components of a framework, for the identification and local containment of misbehaving or faulty nodes, and then for their eviction from the system. We tailor our design to the VN characteristics and analyze our system. Our results show that the distributed approach to contain nodes and contribute to their eviction is efficiently feasible and achieves a sufficient level of robustness.
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Cited by
A Security and Privacy Review of VANETs
Qu, F., Wu, Z., Wang, F., & Cho, W. (2015) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2015.2439292 · Cited by 478
Sedjelmaci, H., Senouci, S. M., & Ansari, N. (2018) · IEEE Transactions on Systems, Man, and Cybernetics: Systems · doi:10.1109/tsmc.2017.2681698 · Cited by 282
Securing Vehicle-to-Everything (V2X) Communication Platforms
Hasan, M., Mohan, S., Shimizu, T., & Lu, H. (2020) · IEEE Transactions on Intelligent Vehicles · doi:10.1109/tiv.2020.2987430 · Cited by 275
A Blockchain-SDN-Enabled Internet of Vehicles Environment for Fog Computing and 5G Networks
Gao, J., Obour Agyekum, K. O.-B., Sifah, E. B., Acheampong, K. N., Xia, Q., Du, X., Guizani, M., & Xia, H. (2020) · IEEE Internet of Things Journal · doi:10.1109/jiot.2019.2956241 · Cited by 209
Misbehavior Detection using Machine Learning in Vehicular Communication Networks
Gyawali, S., & Qian, Y. (2019) · ICC 2019 - 2019 IEEE International Conference on Communications (ICC) · doi:10.1109/icc.2019.8761300 · Cited by 130
Metadata
- Authors
- Raya, M., Papadimitratos, P., Aad, I., Jungels, D., & Hubaux, J.-P.
- Venue
- IEEE Journal on Selected Areas in Communications
- Published
- 2007-10
- Volume
- 25
- Issue
- 8
- Pages
- 1557-1568
- ISSN
- 0733-8716 (ISSN-L)
- OpenAlex
- W2123830234
- Cited by
- 406
- References
- 0
- FWCI
- 23.31
- Type
- journal article
- Language
- en
- Open access
- green
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- Raya, M., Papadimitratos, P., Aad, I., Jungels, D., & Hubaux, J.-P. (2007). Eviction of Misbehaving and Faulty Nodes in Vehicular Networks. IEEE Journal on Selected Areas in Communications. https://doi.org/10.1109/jsac.2007.071006
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