Byzantine-Resilient Locally Optimum Detection Using Collaborative Autonomous Networks

TL;DR

This paper introduces a decentralized, Byzantine-resilient detection scheme for weak radioactive sources using autonomous sensor networks, leveraging ADMM for efficient, robust, and scalable performance in low SNR conditions.

Contribution

It presents a novel decentralized detection algorithm based on ADMM that is resilient to Byzantine data falsification attacks, with performance close to centralized methods.

Findings

Performance approaches centralized clairvoyant detection in low SNR

Algorithm exhibits fast convergence and scalability

Robustness to data falsification attacks demonstrated

Abstract

In this paper, we propose a locally optimum detection (LOD) scheme for detecting a weak radioactive source buried in background clutter. We develop a decentralized algorithm, based on alternating direction method of multipliers (ADMM), for implementing the proposed scheme in autonomous sensor networks. Results show that algorithm performance approaches the centralized clairvoyant detection algorithm in the low SNR regime, and exhibits excellent convergence rate and scaling behavior (w.r.t. number of nodes). We also devise a low-overhead, robust ADMM algorithm for Byzantine-resilient detection, and demonstrate its robustness to data falsification attacks.