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Channel State Information-Based
Detection of Sybil Attacks in Wireless Networks and Xiaochun
Cheng3
1Tianjin
University of Technology, Tianjin 300384 China {michael3769,
kurtcobian4ever}@163.com, gongliangyi@tjut.edu.cn, deviltangv@163.com, 778750188@qq.com 2Nankai
University, Tianjin 300350 China liuzheli@nankai.edu.cn 3Middlesex
University, London NW4 4BT UK X.Cheng@mdx.ac.uk
Abstract Single authentication mechanisms and broadcast
characteristics of wireless networks make the Access Point (AP) vulnerable to
spoofing attacks and Sybil attacks. However, Sybil attacks seriously affect
network performance. Sybil nodes act with different identity, and prevent the
normal clients from transmission. In this paper, a self-adaptive MUSIC
algorithm is proposed, which improves the accuracy of the angle of the indoor
wireless device by eliminating the phase offset in channel state information
(CSI), and designs different types’ detection algorithm of Sybil attacks and
spoofing attacks based on different Sybil attack models. And we experiment on
mobile and commercial WiFi devices. The average
detection error of angle is below 6.3°. After combining analysis of received
signal strength indicator (RSSI), our detection algorithm can effectively
detect whether the nodes launched by Sybil attacks, and the identity of other
clients disguised by spoofing attacks. According to the experimental results,
the scheme can distinguish the Sybil clients and the normal clients
accurately, and the average success rate of the Sybil attack detection system
is 98.5%. Keywords: Channel State Information, Sybil
Attack, Spoofing Attack, Indoor localization +: Corresponding author: Likun
Zhu Journal
of Internet Services and Information Security
(JISIS), 8(1): 2-17,
February 2018 |