Ransomware is a malware category that exploits security mechanisms such as cryptography
in order to hijack user files and related resources and demands money in exchange for the …

Building machine learning models of malware behavior is widely accepted as a panacea
towards effective malware classification. A crucial requirement for building sustainable …

With more than two million applications, Android marketplaces require automatic and
scalable methods to efficiently vet apps for the absence of malicious threats. Recent …

The evolution of mobile malware poses a serious threat to smartphone security. Today,
sophisticated attackers can adapt by maximally sabotaging machine-learning classifiers via …

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these classifiers have an Achilles heel, concept drift: they rapidly become out of date and …

As the most widely used mobile platform, Android is also the biggest target for mobile
malware. Given the increasing number of Android malware variants, detecting malware …

Malware is a major threat to computer systems and imposes many challenges to cyber
security. Targeted threats, such as ransomware, cause millions of dollars in losses every …

Abstract Many existing Machine Learning (ML) based Android malware detection
approaches use a variety of features such as security-sensitive APIs, system calls, control …

It is well known that Android malware constantly evolves so as to evade detection. This
causes the entire malware population to be nonstationary. Contrary to this fact, most of the …

Despite the growing threat posed by Android malware, the research community is still
lacking a comprehensive view of common behaviors and trends exposed by malware …