Voiceprint: A Novel Sybil Attack Detection Method Based on RSSI for VANETs

Yuan Yao, Bin Xiao, Gaofei Wu, Xue Liu, Zhiwen Yu, Kailong Zhang, Xingshe Zhou

科研成果: 书/报告/会议事项章节会议稿件同行评审

44 引用 (Scopus)

摘要

Vehicular Ad Hoc Networks (VANETs) enable vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications that bring many benefits and conveniences to improve the road safety and drive comfort in future transportation systems. Sybil attack is considered one of the most risky threats in VANETs since a Sybil attacker can generate multiple fake identities with false messages to severely impair the normal functions of safety-related applications. In this paper, we propose a novel Sybil attack detection method based on Received Signal Strength Indicator (RSSI), Voiceprint, to conduct a widely applicable, lightweight and full-distributed detection for VANETs. To avoid the inaccurate position estimation according to predefined radio propagation models in previous RSSI-based detection methods, Voiceprint adopts the RSSI time series as the vehicular speech and compares the similarity among all received time series. Voiceprint does not rely on any predefined radio propagation model, and conducts independent detection without the support of the centralized infrastructure. It has more accurate detection rate in different dynamic environments. Extensive simulations and real-world experiments demonstrate that the proposed Voiceprint is an effective method considering the cost, complexity and performance.

源语言英语
主期刊名Proceedings - 47th Annual IEEE/IFIP International Conference on Dependable Systems and Networks, DSN 2017
出版商Institute of Electrical and Electronics Engineers Inc.
591-602
页数12
ISBN(电子版)9781538605417
DOI
出版状态已出版 - 30 8月 2017
活动47th Annual IEEE/IFIP International Conference on Dependable Systems and Networks, DSN 2017 - Denver, 美国
期限: 26 6月 201729 6月 2017

出版系列

姓名Proceedings - 47th Annual IEEE/IFIP International Conference on Dependable Systems and Networks, DSN 2017

会议

会议47th Annual IEEE/IFIP International Conference on Dependable Systems and Networks, DSN 2017
国家/地区美国
Denver
时期26/06/1729/06/17

指纹

探究 'Voiceprint: A Novel Sybil Attack Detection Method Based on RSSI for VANETs' 的科研主题。它们共同构成独一无二的指纹。

引用此