Privacy and Security Issues for Human Digital Twins

Digital Twin (DT) technology has recently attracted researchers' and industries' interest, becoming popular in many domains thanks to its capability to improve systems performance. This technology comprises a virtual model representing a physical entity. The physical and the virtual twins are connected to allow data sharing, aiming to provide real-time monitoring and decision processes. Human Digital Twins (HDTs) are a particular type of DTs in which the virtual twin models a human being. HDTs are applied, for instance, in healthcare to constantly monitor a patient, allowing medical staff to determine the best treatment on the DT. Although the benefits of DT and HDT are manifold, they suffer from cybersecurity risks that have only recently started to be considered. Moreover, the massive usage of HDTs poses serious privacy issues since HDTs leverage personal information that might be sensitive. In this paper, we aim to illustrate the threats affecting DTs. Then, we focus on specific threats affecting HDTs with a vision towards future research directions.