Malware, a lethal weapon of cyber attackers, is becoming increasingly sophisticated, with
rapid deployment and self-propagation. In addition, modern malware is one of the most …

Malware is still a challenging security problem in the Android ecosystem, as malware is
often obfuscated to evade detection. In such case, semantic behavior feature extraction is …

Android malware detection (AMD) is a challenging task requiring many factors to be
considered during detection, such as feature extraction and processing, performance …

The growing Android malware is seriously threatening the privacy and property security of
Android users. However, the existing detection methods are often unable to maintain …

Federated learning (FL) is a decentralized machine learning architecture, which leverages a
large number of remote devices to learn a joint model with distributed training data …

Wearable devices based on the Android system are developing rapidly, but the research on
their application security is still lacking. Therefore, this paper designs an Android wearable …

The exponential proliferation of malware requires robust detection mechanisms for the
security of global enterprises and national infrastructures. Conventional malware …

Malware is a significant threat to the security of computer systems and networks worldwide,
and its sophistication and diversity continue to increase over time. One of the key challenges …

Machine learning (ML) has gained significant adoption in Android malware detection to
address the escalating threats posed by the rapid proliferation of malware attacks. However …

The increase in ransomware threats targeting Android devices necessitates the
development of advanced techniques to strengthen the effectiveness of detection and …