Malicious software (malware) is a major cyber threat that has to be tackled with Machine
Learning (ML) techniques because millions of new malware examples are injected into …

Malware remains a big threat to cyber security, calling for machine learning based malware
detection. While promising, such detectors are known to be vulnerable to evasion attacks …

While the usage of Artificial Intelligence and Machine Learning Software (AI/MLS) in
defensive cybersecurity has received considerable attention, there remains a noticeable …

Android malware poses a serious security threat to ordinary mobile users. However, the
obfuscation technology can generate malware variants, which can bypass existing detection …

Machine learning (ML) has been widely used for malware detection on different operating
systems, including Android. To keep up with malware's evolution, the detection models …

Android malware is a major cyber threat to the popular Android platform which may
influence millions of end users. To battle against Android malware, a large number of …

Machine Learning (ML) techniques can facilitate the automation of mal icious soft ware
(malware for short) detection, but suffer from evasion attacks. Many studies counter such …

Machine learning has shown promise for improving the accuracy of Android malware
detection in the literature. However, it is challenging to (1) stay robust towards real-world …

The evolution of malware has long plagued machine learning-based detection systems, as
malware authors develop innovative strategies to evade detection and chase profits. This …

The Internet of Things (IoT) has grown rapidly due to artificial intelligence driven edge
computing. While enabling many new functions, edge computing devices expand the …