基于阈值自适应控制的VANET智能恶意和自私节点检测

C. A. Kerrache, Abderrahmane Lakas, N. Lagraa
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引用次数: 22

摘要

检测恶意和自私节点是车载自组网(vanet)中的重要任务。与基于密码学的解决方案相比,信任管理在计算延迟和移动性适应方面的成本更低,因此各种建议采用信任管理作为替代解决方案。然而,现有的解决方案通常假设攻击者总是有不诚实的行为,并持续一段时间。这种假设可能具有误导性,因为攻击者可以通过智能行为来避免被检测到。本文提出了一种基于自适应检测阈值的智能恶意行为检测新方案。除了检测恶意节点外,我们的解决方案还可以激发攻击者的良好行为,因为任何恶意行为都会立即被检测到,这得益于自适应检测阈值。我们给出的仿真结果表明,我们的方案在保证检测和数据包传输的高比率方面具有很高的效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Detection of intelligent malicious and selfish nodes in VANET using threshold adaptive control
Detecting malicious and selfish nodes is an important task in Vehicular Adhoc NETworks (VANETs). Various proposals adopted trust management as an alternative solution for it is less costly in terms of computation delay and mobility adaptation, compared to the cryptography-based solutions. However, the existing solutions assume that in general the attackers have always a dishonest behavior that persists over time. This assumption may be misleading, as the attackers can behave intelligently to avoid being detected. In this paper we propose a new solution for the detection of intelligent malicious behaviors based on the adaptive detection threshold. In addition to the detection of malicious nodes, our solution incite attackers to behave well since any malicious behavior will be immediately detected thanks to the adaptive detection threshold. We present simulations results which show the high efficiency of our proposal at ensuring high ratios for both detection and packet delivery.
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