At present, smartphones running the Android operating system have occupied the leading
market share. However, due to the Android operating system's open-source nature, Android …

The increasing popularity of Android apps attracted widespread attention from malware
authors. Traditional malware detection systems suffer from some shortcomings; …

In recent years, the number of malware on the Android platform has been increasing, and
with the widespread use of code obfuscation technology, the accuracy of antivirus software …

Machine Learning (ML) algorithms, specifically supervised learning, are widely used in
modern real-world applications, which utilize Computational Intelligence (CI) as their core …

Obfuscapk is an open-source automatic obfuscation tool for Android apps that works in a
black-box fashion (ie, it does not need the app source code). Obfuscapk supports advanced …

Machine learning–based classification dominates current malware detection approaches for
Android. However, due to the evolution of both the Android platform and its user apps …

The Android operating system has gained popularity and evolved rapidly since the previous
decade. Traditional approaches such as static and dynamic malware identification …

We present DANdroid, a novel Android malware detection model using a deep learning
Discriminative Adversarial Network (DAN) that classifies both obfuscated and unobfuscated …

In recent years, everything has been more and more systematic, and it would generate many
cyber security issues. One of the most important of these is the malware. Modern malware …

Modern commercial antivirus systems increasingly rely on machine learning to keep up with
the rampant inflation of new malware. However, it is well-known that machine learning …