On the privacy and security for e-health services in the metaverse: An overview

Abstract

Metaverse-enabled healthcare systems are expected to efficiently utilize an unprecedented amount of health-related data without disclosing sensitive or private information of individuals during data collection, communications, and learning-based processing. In this paper, we study the privacy and security of the metaverse healthcare from different aspects. Specifically, we first investigate the security of data collection and communications in the access layer of the metaverse. We then go through the privacy and security issues inside the metaverse, by addressing the privacy and security threats of utilizing clinical machine learning for intelligent e-health. From a human-centric perspective, privacy of social interactions among patients in a metaverse-enabled healthcare platform is also studied. We try to provide a holistic and less-investigated approach to help metaverse-as-a-health service providers facilitate the realization of secure and private e-health services from different aspects, ranging from the access layer to the social interactions among clients. Future vision and directions are also discussed to bring further insights for the network designers in the metaverse era.