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Stochastic Geometry Analysis of Reference Signal Spoofing Attack in Wireless Cellular Networks

机译:无线蜂窝网络中参考信号欺骗攻击的随机几何分析

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Cell association is a critical aspect of cellular network operation wherein mobile terminals (MTs) connect to optimal base stations before commencing data transmission and reception. This paper investigates a novel physical layer security problem wherein malicious base stations (MBSs) seek to subvert the cell association process by spoofing the common reference signals of legitimate base stations (LBSs). Since these signals are used by MTs to measure signal strength, the MBSs thus attempt to increase the likelihood of MT radio link failure (RLF). A stochastic geometry approach using a Poisson point process (PPP) to model the random locations of LBSs and MBSs is used to analyze the impact of this attack. We analytically derive the conditional probability of the RLF given a suboptimal association triggered by MBSs and verify the theoretical results using simulations. This paper also presents insights on the appropriate ranges of thresholds for MTs seeking association with LBSs and claiming RLF using the conditional RLF probability triggered by MBS attacks.
机译:小区关联是蜂窝网络操作的关键方面,其中移动终端(MT)在开始数据发送和接收之前连接到最佳基站。本文研究了一种新颖的物理层安全性问题,其中恶意基站(MBS)通过欺骗合法基站(LBS)的公共参考信号来寻求颠覆小区关联过程。由于MT会使用这些信号来测量信号强度,因此MBS会尝试增加MT无线电链路故障(RLF)的可能性。使用泊松点过程(PPP)对LBS和MBS的随机位置进行建模的随机几何方法用于分析此攻击的影响。我们给出了由MBS触发的次优关联,通过分析得出RLF的条件概率,并使用仿真验证了理论结果。本文还提供了有关MT寻求与LBS关联并使用MBS攻击触发的条件RLF概率主张RLF的阈值的适当范围的见解。

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