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A Secure Distributed Information Sharing Algorithm Based on Attack Detection in Multi-Task Networks
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DOI：10.1109/TCSI.2020.2997677.png)
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Abstract
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Recently there were research works on multi-task estimation. However, there exists an issue that nodes may suffer from malicious attacks when sending data in the adversarial multi-task network environment. To address this issue, we propose a secure distributed information sharing algorithm based on attack detection. In our work, via determining an adaptive threshold, a distributed detection algorithm based on the correlation between tasks and a safe multi-task diffusion least mean square (SM-DLMS) algorithm are proposed, which not only reduce communication costs but also effectively decrease the impact of attacks. We also theoretically analyze the stability performance of the proposed SM-DLMS algorithm. Meanwhile, the robustness and effectiveness of the proposed algorithm under network-attacks are illustrated through numerical simulations.
Keywords:
Signal processing algorithms
Task analysis
Estimation
Security
Clustering algorithms
Information management
Correlation
Distributed estimation
attack detection
adaptive signal processing
multi-task networks
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