Logistic Regression Based Malicious UAV Tracking in WSN

In recent years, Unmanned aerial vehicles (UAV) assisted WSNs have had a major impact on wireless communication. The sensor nodes are deployed for efficient and effective data collection by considering UAVs as mobile sinks in WSN. Due to the deployment and wide range of access, UAVs are focused on academia and industry UAV-assisted communication includes UAV-assisted relaying, dissemination, coverage extension, and data collection. UAV-based WSN permits only the cluster head to communicate with UAV. UAVs are applicable in several domains due to their attributes such as flexibility, mobility, and adaptability to different environments. For wireless communication systems, UAV offers services as aerial base stations. While compared with the traditional base stations, energy resources, reliability, and coverage are restricted. However, the UAV components are not modeled with the security approaches. Insufficient security and drone movement causes problems including excessive latency, high energy usage, and unauthorized access. In our proposed system we implemented a Linear Regression system for malicious UAV tracking in WSN.