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 …

With smart phones being indispensable in people's everyday life, Android malware has
posed serious threats to their security, making its detection of utmost concern. To protect …

To cope with the increasing variability and sophistication of modern attacks, machine
learning has been widely adopted as a statistically-sound tool for malware detection …

The increasing proliferation of Androidbased devices, which currently dominate the market
with a staggering 72% global market share, has made them a prime target for attackers …

Year after year, mobile malware attacks grow in both sophistication and diffusion. As the
open source Android platform continues to dominate the market, malware writers consider it …

Machine Learning-based malware detection is a promis-ing scalable method for identifying
suspicious applica-tions. In particular, in today's mobile computing realm where thousands …

Machine learning-based solutions have been successfully employed for the automatic
detection of malware on Android. However, machine learning models lack robustness to …

Classification using machine learning has been a major class of defense solutions against
malware. Yet in the presence of a large and growing number of learning-based malware …

As Android is a popular a mobile operating system, Android malware is on the rise, which
poses a great threat to user privacy and security. Considering the poor detection effects of …

Machine learning methods can detect Android malware with very high accuracy. However,
these classifiers have an Achilles heel, concept drift: they rapidly become out of date and …