Distributed joint spoofing attack identification and estimation in sensor networks
Distributed joint spoofing attack identification and estimation in sensor networks
复制标题
传感器网络中分布式联合欺骗攻击识别与估计
DOI：
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发表时间：
2015
期刊：
影响因子：
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通讯作者：
Rick S. Blum
中科院分区：
文献类型：
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作者：
Jiangfan Zhang;Rick S. Blum
分布式估计的一个确定性的标量参数，通过使用量化的数据在欺骗攻击，修改的物理现象的统计模型的存在，被认为是。本文开发了一种有效的启发式方法，以联合检测攻击和估计欺骗攻击是无法检测到的传统方法，依赖于注意到数据是不符合预期的家庭的分布。数值结果表明，该方法能够正确识别出具有大量时间观测值的被攻击传感器，并且在已知被攻击传感器集合的假设下，该方法的估计性能能够渐近达到期望参数的Genie Cramer-Rao界（CRB）.
Distributed estimation of a deterministic scalar parameter by using quantized data in the presence of spoofing attacks, which modify the statistical model of the physical phenomenon, is considered. The paper develops an efficient heuristic approach to jointly detect attacks and estimate under spoofing attacks that are undetectable by a traditional approach that relies on noticing the data is not consistent with an expected family of distributions. Numerical results show that the proposed approach can correctly identify the attacked sensors with a large number of time observations, and moreover, the estimation performance of the proposed approach can asymptotically achieve the genie Cramer-Rao bound (CRB) for the desired parameter, which is the CRB under the assumption that the set of attacked sensors is known.