Malicious applications (particularly those targeting the Android platform) pose a serious
threat to developers and end-users. Numerous research efforts have been devoted to …

Zero-day malware is malware that has never been seen before or is so new that no anti-
malware software can catch it. This novelty and the lack of existing mitigation strategies …

Graph neural networks (GNNs) have emerged as a series of competent graph learning
methods for diverse real-world scenarios, ranging from daily applications like …

Deep neural networks (DNNs) have been widely applied to various applications, including
image classification, text generation, audio recognition, and graph data analysis. However …

Abstract Application Programming Interfaces (APIs) are widely considered a useful data
source for dynamic malware analysis to understand the behavioral characteristics of …

Stealthy hardware Trojans (HTs) inserted during the fabrication of integrated circuits can
bypass the security of critical infrastructures. Although researchers have proposed many …

Existing Android malware detection methods are usually hard to simultaneously resist
various obfuscation techniques. Therefore, bytecode-based code obfuscation becomes an …

Recently, we have witnessed the success of deep reinforcement learning (DRL) in many
security applications, ranging from malware mutation to selfish blockchain mining. Like all …

The widespread adoption of the Android operating system has made malicious Android
applications an appealing target for attackers. Machine learning-based (ML-based) Android …

Reproducibility is crucial to the advancement of science; it strengthens confidence in
seemingly contradictory results and expands the boundaries of known discoveries …