基于流行病理论的无线认知传感网抗攻击模型

An Epidemic Theoretic Model Against Data Falsification Attacks for Wireless Cognitive Sensor Networks

大量无线通信设备在ISM频段工作致使免许可频段频谱资源稀缺,促使认知无线电和无线传感器网络(WSN)融合,形成无线认知传感器网络(WCSN)。文章研究了无线认知传感器网络中的数据伪造攻击,即恶意次用户通过向其他次用户发送伪造的频谱感知数据,导致控制中心做出错误的频谱分配决策。基于流行病理论,文章对数据伪造攻击中的信息传播过程进行了建模和分析,找出了决定无线认知传感器网络中潜在流行病爆发的关键因素。最后,通过仿真实验,对模型进行了验证,并对系统动态特性进行了研究。

A large amount of wireless communication equipments operating in ISM band result in spectrum scarcity in the unlicensed band, leading to the confluence of cognitive radio into Wireless sensor networks （WSN）, which we refer to as Wireless Cognitive Sensor Network （WCSN）. In this paper, we study the data falsification attacks to WCSN, where intruders send false local spectrum sensing data resulting in incorrect spectrum allocation by control centers. Based on epidemic theory, we model and analyze the information spreading process in data falsification attacks and identify key factors determining potential epidemic outbreaks in WCSN. The analytical results will provide deep insights in designing potential defense schemes against Byzantine attacks. In conclusion, through simulation experiments, we validate our models and perform investigations on the system dynamics.