Suguna Marappan

Abstract The integration of privacy protection in smart healthcare systems has revolutionized disease detection and patient monitoring, but privacy concerns arise from the collection and analysis of sensitive health data. Federated learning (FL) offers data privacy to diverse clients, but a single global model fails. Personalized FL addresses privacy concerns, focusing on individual needs.

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1. Introduction The relevance of cybersecurity has grown significantly as a result of the increased reliance on computer systems, the Internet, wireless networks, and the expansion of smart devices that make up the IoT. The term “cybersecurity” [1] describes the process of defending our computer networks and systems against unauthorized access, theft, and damage to electronic data, hardware, or software, as well as against service interruption or rerouting.