New framework enhances IoMT security with AI and privacy preservation

A new framework has been proposed to enhance the security and privacy of Internet of Medical Things (IoMT) systems. This framework utilizes Artificial Neural Networks for intrusion detection and incorporates Federated Learning to preserve user privacy. Additionally, it integrates eXplainable Artificial Intelligence (XAI) methods to improve model interpretability. Evaluations demonstrate that the Federated Learning approach performs comparably to centralized methods while effectively safeguarding privacy and providing model explanations. AI

IMPACT This framework could lead to more secure and trustworthy medical devices, improving patient safety and data confidentiality.

RANK_REASON The cluster contains an academic paper detailing a new framework for security and privacy in IoMT systems. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

• Ayoub Si-Ahmed Mr
• Federated Learning
• Internet-of-Medical-Things
• machine learning

• paper
• safety
• product

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