1. Byzantine-Resilient Locally Optimum Detection Using Collaborative Autonomous Networks
- Author
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Kailkhura, Bhavya, Ray, Priyadip, Rajan, Deepak, Yen, Anton, Barnes, Peter, and Goldhahn, Ryan
- Subjects
Computer Science - Systems and Control ,Statistics - Other Statistics - 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., Comment: Proceedings of the 2017 IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP 2017), 10.-13. December 2017, Curacao, Dutch Antilles
- Published
- 2018