Volume 8 - Issue 1
Channel State Information-Based Detection of Sybil attacks in Wireless Networks
- Chundong Wang
Tianjin University of Technology, Tianjin 300384 China
michael3769@163.com
- Likun Zhu
Tianjin University of Technology, Tianjin 300384 China
kurtcobian4ever@163.com
- Liangyi Gong
Tianjin University of Technology, Tianjin 300384 China
gongliangyi@tjut.edu.cn
- Zhentang Zhao
Tianjin University of Technology, Tianjin 300384 China
deviltangv@163.com
- Lei Yang
Tianjin University of Technology, Tianjin 300384 China
778750188@qq.com
- Zheli Liu
Nankai University, Tianjin 300350 China
liuzheli@nankai.edu.cn
- Xiaochun Cheng
Middlesex University, London NW4 4BT UK
X.Cheng@mdx.ac.uk
Keywords: Channel State Information, Sybil attack, Spoofing Attack, Indoor localization
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%.