Wang Chundong, Zhu Likun, Gong Liangyi, Zhao Zhentang, Yang Lei, Liu Zheli, Cheng Xiaochun
Key Laboratory of Computer Vision and System, Ministry of Education, Tianjin University of Technology, Tianjin 300384, China.
Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology, Ministry of Education, Tianjin University of Technology, Tianjin 300384, China.
Sensors (Basel). 2018 Mar 15;18(3):878. doi: 10.3390/s18030878.
With the development of the Internet-of-Things (IoT), wireless network security has more and more attention paid to it. The Sybil attack is one of the famous wireless attacks that can forge wireless devices to steal information from clients. These forged devices may constantly attack target access points to crush the wireless network. In this paper, we propose a novel Sybil attack detection based on Channel State Information (CSI). This detection algorithm can tell whether the static devices are Sybil attackers by combining a self-adaptive multiple signal classification algorithm with the Received Signal Strength Indicator (RSSI). Moreover, we develop a novel tracing scheme to cluster the channel characteristics of mobile devices and detect dynamic attackers that change their channel characteristics in an error area. Finally, we experiment on mobile and commercial WiFi devices. Our algorithm can effectively distinguish the Sybil devices. The experimental results show that our Sybil attack detection system achieves high accuracy for both static and dynamic scenarios. Therefore, combining the phase and similarity of channel features, the multi-dimensional analysis of CSI can effectively detect Sybil nodes and improve the security of wireless networks.
随着物联网（IoT）的发展，无线网络安全越来越受到关注。Sybil攻击是一种著名的无线攻击，它可以伪造无线设备从客户端窃取信息。这些伪造的设备可能会不断攻击目标接入点，以破坏无线网络。在本文中，我们提出了一种基于信道状态信息（CSI）的新型Sybil攻击检测方法。该检测算法通过将自适应多重信号分类算法与接收信号强度指示（RSSI）相结合，能够判断静态设备是否为Sybil攻击者。此外，我们开发了一种新颖的追踪方案，用于聚类移动设备的信道特征，并检测在误差区域内改变其信道特征的动态攻击者。最后，我们在移动和商用WiFi设备上进行了实验。我们的算法能够有效区分Sybil设备。实验结果表明，我们的Sybil攻击检测系统在静态和动态场景下均能达到高精度。因此，结合信道特征的相位和相似性，对CSI进行多维度分析能够有效检测Sybil节点，提高无线网络的安全性。
