Hierarchical Federated Learning With Social Context Clustering-Based Participant Selection for Internet of Medical Things Applications

The proliferation in embedded and communication technologies made the concept of the Internet of Medical Things (IoMT) a reality. Individuals’ physical and physiological status can be constantly monitored, and numerous data can be collected through wearable and mobile devices. However, the silo of individual data brings limitations to existing machine learning approaches to correctly identify a user’s health status. Distributed machine learning paradigms, such as federated learning, offer a potential solution for privacy-preserving knowledge sharing without sending raw personal data. However, federated learning is vulnerable to harmful participants that can degrade the overall model quality by sharing…

• Q
  QuakeCoRE
• HP
  Hunan Provincial Innovation Foundation for Postgraduate

  Award: CX20211102