一种车载自组网模糊奖惩方案

IF 0.7 Q3 COMPUTER SCIENCE, THEORY & METHODS
Rezvi Shahariar, C. Phillips
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引用次数: 0

摘要

信任管理是成功实现车载自组织网络(vanet)的重要安全方法。信任模型评估消息以分配奖励或惩罚。这可以用来影响司机未来的行为。在作者之前的工作中,开发了一个基于发送端的信任管理框架,避免了接收方对消息的评估。但是,这并不能保证受信任的驱动程序不会说谎。这些“不真实的攻击”由rsu使用协作来裁决争议,提供固定数量的奖励和惩罚来解决。本文通过一种新的模糊RSU控制器来解决复杂性不足的问题,该控制器考虑了事件的严重性、驾驶员过去的行为和RSU置信度来确定冲突驾驶员的奖励或惩罚。尽管任何司机在任何情况下都可能说谎,但值得信赖的司机更有可能继续说谎,反之亦然。这种行为在发送者和报告者司机的马尔可夫链模型中被捕获,其中他们的撒谎特征取决于信任得分和信任状态。每个信任状态使用不同的概率分布来定义驾驶员说谎的可能性。在仿真系统中,通过改变所有或部分驾驶员的初始信任分数,对马尔可夫链驾驶员行为模型进行了广泛的仿真,以评价模糊评价的性能。比较了模糊RSU和固定RSU评价方案,结果表明模糊评价方案能激励驾驶员改进其行为。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Fuzzy Reward and Punishment Scheme for Vehicular Ad Hoc Networks
—Trust management is an important security approach for the successful implementation of Vehicular Ad Hoc Networks (VANETs). Trust models evaluate messages to assign reward or punishment. This can be used to influence a driver’s future behaviour. In the author’s previous work, a sender-side based trust management framework is developed which avoids the receiver evaluation of messages. However, this does not guarantee that a trusted driver will not lie. These “untrue attacks” are resolved by the RSUs using collaboration to rule on a dispute, providing a fixed amount of reward and punishment. The lack of sophistication is addressed in this paper with a novel fuzzy RSU controller considering the severity of incident, driver past behaviour, and RSU confidence to determine the reward or punishment for the conflicted drivers. Although any driver can lie in any situation, it is expected that trustworthy drivers are more likely to remain so, and vice versa. This behaviour is captured in a Markov chain model for sender and reporter drivers where their lying characteristics depend on trust score and trust state. Each trust state defines the driver’s likelihood of lying using different probability distribution. An extensive simulation is performed to evaluate the performance of the fuzzy assessment and examine the Markov chain driver behaviour model with changing the initial trust score of all or some drivers in Veins simulator. The fuzzy and the fixed RSU assessment schemes are compared, and the result shows that the fuzzy scheme can encourage drivers to improve their behaviour.
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来源期刊
CiteScore
2.30
自引率
22.20%
发文量
519
期刊介绍: IJACSA is a scholarly computer science journal representing the best in research. Its mission is to provide an outlet for quality research to be publicised and published to a global audience. The journal aims to publish papers selected through rigorous double-blind peer review to ensure originality, timeliness, relevance, and readability. In sync with the Journal''s vision "to be a respected publication that publishes peer reviewed research articles, as well as review and survey papers contributed by International community of Authors", we have drawn reviewers and editors from Institutions and Universities across the globe. A double blind peer review process is conducted to ensure that we retain high standards. At IJACSA, we stand strong because we know that global challenges make way for new innovations, new ways and new talent. International Journal of Advanced Computer Science and Applications publishes carefully refereed research, review and survey papers which offer a significant contribution to the computer science literature, and which are of interest to a wide audience. Coverage extends to all main-stream branches of computer science and related applications
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