The various application markets are facing an exponential growth of Android malware. Every
day, thousands of new Android malware applications emerge. Android malware hackers …

This paper introduces and tests a novel machine learning approach to detect Android
malware. The proposed approach is composed of Support Vector Machine (SVM) classifier …

The vast body of machine learning based Android malware detection research, reporting
high-performance metrics using a wide variety of proposed solutions, enables the logical …

Smart phones are becoming essential in our lives, and Android is one of the most popular
operating systems. Android OS is wide-ranging in the mobile industry today because of its …

Malicious software (“malware”) has become one of the serious cybersecurity issues in
Android ecosystem. Given the fast evolution of Android malware releases, it is practically not …

The large body of Android malware research has demonstrated that machine learning
methods can provide high performance for detecting Android malware. However, the vast …

Malicious apps specifically aimed at the Android platform have increased in tandem with the
proliferation of mobile devices. Malware is now so carefully written that it is difficult to detect …

The proliferation of malware in recent years has posed a significant threat to the security of
computers and mobile devices. Detecting malware, especially on the Android platform, has …

The dramatic increase in Android-based smart devices has brought technological revolution
to improve the overall quality of life and thus making it worth a billion-dollar market. Despite …

It is critical to successfully identify, mitigate, and fight against Android malware assaults,
since Android malware has long been a significant threat to the security of Android …