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Distributed estimation of a deterministic mean-shift parameter in additive zero-mean noise is studied when using quantized data in the presence of Byzantine attacks. Several subsets of sensors are assumed to be tampered with by adversaries using different attacks such that the compromised sensors transmit fictitious data. First, we consider the task of identifying and categorizing the attacked sensors...
Distributed estimation using quantized data in the presence of Byzantine attacks is considered. Several subsets of sensors are assumed to be tampered with by different adversaries. Under the control of adversaries, the compromised sensors transmit fictitious data to the fusion center (FC) in order to undermine the estimation performance of the sensor network. First, we show that it is possible to...
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