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Try to Avoid Attacks: A Federated Data Sanitization Defense for Healthcare IoMT Systems. (arXiv:2211.01592v1 [cs.CR])
Nov. 4, 2022, 1:20 a.m. | Chong Chen, Ying Gao, Leyu Shi, Siquan Huang
cs.CR updates on arXiv.org arxiv.org
Healthcare IoMT systems are becoming intelligent, miniaturized, and more
integrated into daily life. As for the distributed devices in the IoMT,
federated learning has become a topical area with cloud-based training
procedures when meeting data security. However, the distribution of IoMT has
the risk of protection from data poisoning attacks. Poisoned data can be
fabricated by falsifying medical data, which urges a security defense to IoMT
systems. Due to the lack of specific labels, the filtering of malicious data is …
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