Secure and Efficient UAV Tracking in Space-Air-Ground Integrated Network

With the development of 5G and other communication techniques, the space-air-ground integrated network (SAGIN) is regarded as a promising solution to provide wide-range, cost-effective, and real-time wireless access. Unmanned Aerial Vehicle (UAV) Tracking plays a crucial role in guaranteeing the performance of SAGIN. However, UAV tracking still faces a series of challenges in the real-world deployment, especially in the case of the presence of malicious attackers, who may launch a series of attacks (e.g., message spoofing attack, routing misbehavior attack) to disrupt the systems. In this study, to enhance the security and efficiency of SAGIN when conducting object tracking, we propose a novel and secure object tracking system named SecTracker to overcome the emerging security problems in the SAGIN. Focusing on the unmanned aerial vehicle (UAV) tracking, we design the Local Voting based Detection Module to defend the message spoofing attack and implement the Routing Evidence based Detection Module to defend the routing misbehavior attack. Besides, efficiency enhancement mechanisms (i.e., probabilistic detection algorithm and game theory based algorithm) are proposed in this paper to improve the efficiency of SecTracker. Considering the above-mentioned attacks, the overall tracking accuracy is improved from 88.16% in existing schemes to 96.64% in SecTracker, which demonstrates the effectiveness of the proposed system.