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arXiv · 1905.10118

On the Performance Analysis of Binary Hypothesis Testing with Byzantine Sensors

Yuqing Ni·Kemi Ding·Yong Yang·Ling Shi
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Abstract

We investigate the impact of Byzantine attacks in distributed detection under binary hypothesis testing. It is assumed that a fraction of the transmitted sensor measurements are compromised by the injected data from a Byzantine attacker, whose purpose is to confuse the decision maker at the fusion center. From the perspective of a Byzantine attacker, under the injection energy constraint, an optimization problem is formulated to maximize the asymptotic missed detection error probability, which is based on the Kullback-Leibler divergence. The properties of the optimal attack strategy are analyzed by convex optimization and parametric optimization methods. Based on the derived theoretic results, a coordinate descent algorithm is proposed to search the optimal attack solution. Simulation examples are provided to illustrate the effectiveness of the obtained attack strategy.

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Yuqing Ni, Kemi Ding, Yong Yang, Ling Shi. 2019-05-24. On the Performance Analysis of Binary Hypothesis Testing with Byzantine Sensors. https://arxiv.org/abs/1905.10118

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