Android Stalkerware Detection Techniques: A Survey Study

Mobile stalkerware system refers to a type of software that is specifically designed to be installed on a person's mobile device without their knowledge or consent. Once installed, it allows someone else to track the device's location, monitor calls and text messages, and access other personal information. Mobile stalkerware poses several risks to individuals whose devices have been compromised. Most notably, the violation of user privacy. Several techniques proposed to detect stalkerware on a device. This research aims to provide a survey on the different mechanisms proposed to detect stalkerware applications on smartphones. This research includes a summary of the research that has been published about stalkerware applications, their capabilities, and the differences between them in terms of complexity and functionality. As a result, several classifications are used to detect these systems, the most prominent of which are Signature-based, Heuristic-based, Behavioral-based, Machine learning-based, and Sandboxing approaches. It was found that the efficiency of the different detection methods depends on the nature of the stalkerware design, and no particular method can be considered the most efficient. After reviewing the published research, it was found that the efficiency of these applications in terms of functionality is measured by several criteria, the most important of which is their ability to hide and the amount of information they leak about the victim's phone.