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Distributed machine learning algorithms play a significant role in processing massive data sets over large networks. However, the increasing reliance on machine learning on information and communication technologies makes it inherently vulnerable to cyber threats. This work aims to develop secure distributed algorithms to protect the learning from adversaries. We establish a game-theoretic framework...
With a large number of sensors and control units in networked systems, the decentralized computing algorithms play a key role in scalable and efficient data processing for detection and estimation. The well-known algorithms are vulnerable to adversaries who can modify and generate data to deceive the system to misclassify or misestimate the information from the distributed data processing. This work...
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