基于频偏分布的无线局域网Sybil攻击检测方法

Detection of Sybil Attacks Based on Frequency Offset Distribution in WLAN

针对无线局域网中的Sybil攻击问题,提出一种利用信号频偏分布特征的攻击检测方法。该方法利用不同无线设备硬件具有不同信号频偏分布的特点,首先估计每台设备发射信号的信号频偏,然后计算每台设备发射信号的频偏分布特征,在此基础上采用DBSCAN聚类方法进行聚类分析,达到检测Sybil攻击,识别伪造无线设备的目的。该方法无需事先获取每个设备的信号特征进行学习,且不受信道变化影响。基于实际硬件环境的测试表明,所提方法能够有效检测Sybil攻击,对伪造设备可以达到95.5%的识别准确率。

This paper proposes a method to detect Sybil attacks in wireless local area network(WLAN),exploiting the diversity of frequency offset distribution inherited from different wireless devices.Firstly,signal frequency offsets of each wireless device are estimated.Then,the feature of signal frequency offset distributions is extracted.Finally,forgery devices produced by the malicious attacker are identified by applying DBSCAN cluster algorithm.The proposed method does not need to be trained with signal feature of every device in advance,and is not affected by the change of wireless channel status.The performance of our Sybil attack detector is evaluated by hardware testbed in typical wireless environments.Experimental results show the proposed method achieves an accuracy of 95.5%in forgery devices detection.