4 papers with code • 0 benchmarks • 1 datasets
These leaderboards are used to track progress in Mobile Security
AndroShield: Automated Android Applications Vulnerability Detection, a Hybrid Static and Dynamic Analysis Approach
The security of mobile applications has become a major research field which is associated with a lot of challenges.
Deep learning has shown its power in many applications, including object detection in images, natural-language understanding, and speech recognition.
In this paper, we conducted a systematic literature review to search and analyze how deep learning approaches have been applied in the context of malware defenses in the Android environment.
heterogeneous temporal graph transformer: an intelligent system for evolving android malware detection
To capture malware evolution, we further consider the temporal dependence and introduce a heterogeneous temporal graph to jointly model malware propagation and evolution by considering heterogeneous spatial dependencies with temporal dimensions.