基于信任的VANET协同入侵检测系统

Tarak Nandy, R. M. Noor, Mohd Yamani Idna Bin Idris, Sananda Bhattacharyya
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引用次数: 14

摘要

随着智能交通系统(ITS)的发展,安全问题变得越来越重要。车辆自组织网络(VANET)安全研究在该领域取得了巨大的进展。其中,入侵检测系统(IDS)的吸引力最大。此外,一种多学科研究的方式已经证明了IDS比VANET的重要性。本文提出了一种基于信任的协同入侵检测系统(T-BICDS)。其中,每辆车维护网络中其他汽车的计分表,以识别它们之前的网络行为模式。此外,车辆采集的实时网络流量可以基于本地IDS代理进行分析,该代理配备了k近邻kNN非线性分类器。此外,车辆可以与相邻车辆协作,更新计分表,实时识别入侵者,并利用计分表进行未来预测。最后,我们总结了这项工作的潜在未来工作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
T-BCIDS: Trust-Based Collaborative Intrusion Detection System for VANET
With the development of an intelligent transport system (ITS), security becomes an increasingly important issue. The Vehicle ad-hoc network (VANET) security researchers have shown enormous development on the field. Among all, the intrusion detection system (IDS) is creating the highest attraction. Additionally, a way of multidisciplinary researches has proved the importance of IDS over VANET. In this paper, a trust-based collaborative intrusion detection system (T-BICDS) is proposed. In which, each car maintains a score table of other cars in the network to identify their previous pattern of network behavior. Additionally, the vehicles gather real-time network traffic can analysis based on local IDS agent, which is equipped with k-nearest neighbors kNN nonlinear classifier. Besides, a vehicle can collaborate with other neighboring vehicles and update the score table to identify intruders in real-time as well as use the table for future prediction. Finally, we have concluded with potential future works out of this effort.
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