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Get Free AccessIn 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.
Bhavya Kailkhura, Priyadip Ray, Deepak Rajan, Anton Yen, Peter J Barnes, Ryan Goldhahn (2018). Byzantine-Resilient Locally Optimum Detection Using Collaborative Autonomous Networks. , DOI: https://doi.org/10.48550/arxiv.1803.01221.
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Type
Preprint
Year
2018
Authors
6
Datasets
0
Total Files
0
Language
en
DOI
https://doi.org/10.48550/arxiv.1803.01221
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