Digital Twin for Wireless Networks: Security Attacks and Solutions

Emerging applications (e.g., human-computer interaction, digital healthcare, and intelligent transportation systems) can be effectively enabled using digital twins (DTs) that combine the virtual model of a physical system with other technologies/schemes (i.e., mathematical optimization, game theory, and machine learning). Although DTs can well enable wireless systems, they will suffer from various security attacks. Therefore, this article presents an overview of security attacks and concerns in a DT-enabled wireless system. We propose a general framework that will serve as guidelines for future DT-enabled wireless systems. Additionally, we present two use cases to show the effectiveness of the proposed framework. A Stackelberg game-enabled model is provided to effectively enable anti-jamming attacks. In addition a residual-enabled reweighting aggregation scheme furnishes robust training against flawed parameters. Finally, we present an outlook on future directions.