Stalkerware Detection Using Static and Dynamic Analysis
S K Mithun, N Abhinand, Vipin Pavithran, Saranya Chandran · 2023
Stalkerware, a pervasive and invasive form of spy-ware, poses severe privacy and security threats by clandestinely collecting personal information and monitoring victims. This research paper presents an automated framework that combines static and dynamic analysis to detect stalkerware applications with high precision. The static analysis component employs an API-based scoring system to identify critical functions, while the dynamic analysis examines network traffic for suspicious connections to stalkerware domains. Evaluations demonstrate the framework’s superiority over existing antivirus software, achieving an impressive accuracy rate of 95.9percent. The proposed framework addresses limitations in stalkerware detection and offers potential for future enhancements in combating this growing menace.