A Privacy-Preserving Misbehavior Detection System in Vehicular Communication Networks
A Privacy-Preserving Misbehavior Detection System in Vehicular Communication Networks
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DOI：
10.1109/tvt.2021.3079385
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发表时间：
2021-06
影响因子：
6.8
通讯作者：
Sohan Gyawali;Y. Qian;R. Hu
中科院分区：
文献类型：
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作者：
Sohan Gyawali;Y. Qian;R. Hu
基于5G的车载通信网络支持各种交通安全和信息娱乐用例，并依赖于定期的信息交换。然而，这些消息容易受到几种攻击，可以使用不当行为检测系统（MDS）检测到。MDS利用信任分数、反馈分数等评价方案来识别车辆的异常行为。然而，MDS中使用的信任和反馈分数可能会侵犯车辆的位置、轨迹或身份隐私。在本文中，我们提出了一个隐私保护的不当行为检测系统，可以检测或识别不当行为，而不侵犯隐私的车辆。在所提出的方法中，从车辆发送的加密加权反馈结合使用添加剂同态属性，而不侵犯信息的隐私。聚合反馈的解密在可信机构处安全地完成，可信机构根据解密的聚合反馈分数更新车辆的信誉分数。我们还进行了全面的安全性分析，并显示了所提出的计划对各种攻击的正确性和弹性。此外，我们已经做了广泛的性能分析，并已表明，该计划的计算成本是更好的现有计划相比。
5 G based vehicular communication networks support various traffic safety and infotainment use cases and rely on the periodic exchange of information. However, these messages are susceptible to several attacks which can be detected using misbehavior detection systems (MDS). MDS utilizes trust score, feedback score and other evaluation schemes to identify abnormal behavior of the vehicles. However, the trust and feedback scores used in MDS may violate the location, trajectory, or identity privacy of the vehicle. In this paper, we propose a privacy-preserving misbehavior detection system that can detect or identify misbehavior without violating the privacy of the vehicle. In the proposed method, encrypted weighted feedbacks sent from vehicles are combined using additive homomorphic properties without violating the privacy of the information. The decryption of the aggregate feedback is done securely at the trusted authority which updates the reputation score of the vehicle according to the decrypted aggregate feedback score. We have also performed comprehensive security analysis and have shown the correctness and resilience of the proposed schemes against various attacks. In addition, we have done extensive performance analysis and have shown that the computation cost of the proposed scheme is better compared to the existing schemes.