Asymptotic Optimality in Byzantine Distributed Quickest Change Detection
Yu-Chih Huang, Yu-Jui Huang, Shih-Chun Lin

TL;DR
This paper characterizes the asymptotic optimality of Byzantine distributed quickest change detection, demonstrating that minimal communication links suffice for optimality and proposing bandwidth-efficient detection rules.
Contribution
It provides the first tight asymptotic performance bounds for binary and multi-hypothesis BDQCD, and introduces new detection rules and a leader-follower game framework.
Findings
Optimal asymptotic detection delay characterized for binary BDQCD.
Minimal 1-bit links suffice for asymptotic optimality even with compromised sensors.
Proposed detection rules achieve bounds under bandwidth constraints.
Abstract
The Byzantine distributed quickest change detection (BDQCD) is studied, where a fusion center monitors the occurrence of an abrupt event through a bunch of distributed sensors that may be compromised. We first consider the binary hypothesis case where there is only one post-change hypothesis and prove a novel converse to the first-order asymptotic detection delay in the large mean time to a false alarm regime. This converse is tight in that it coincides with the currently best achievability shown by Fellouris et al.; hence, the optimal asymptotic performance of binary BDQCD is characterized. An important implication of this result is that, even with compromised sensors, a 1-bit link between each sensor and the fusion center suffices to achieve asymptotic optimality. To accommodate multiple post-change hypotheses, we then formulate the multi-hypothesis BDQCD problem and again investigate…
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Taxonomy
TopicsAdvanced Statistical Process Monitoring · Distributed Sensor Networks and Detection Algorithms · Statistical Methods and Inference
