Android applications are develo** rapidly across the mobile ecosystem, but Android
malware is also emerging in an endless stream. Many researchers have studied the …

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 …

With the widespread use of smartphones, the number of malware has been increasing
exponentially. Among smart devices, android devices are the most targeted devices by …

Machine learning (ML) classifiers have been widely deployed to detect Android malware,
but at the same time the application of ML classifiers also faces an emerging problem. The …

It is estimated that around 70% of mobile phone users have an Android device. Due to this
popularity, the Android operating system attracts a lot of malware attacks. The sensitive …

Malware poses a severe threat to cyber security. Attackers use malware to achieve their
malicious purposes, such as unauthorized access, stealing confidential data, blackmailing …

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these classifiers have an Achilles heel, concept drift: they rapidly become out of date and …

Oblique aerial images offer views of both building roofs and façades, and thus have been
recognized as a potential source to detect severe building damages caused by destructive …

Android malware evolution has been neglected by the available data sets, thus providing a
static snapshot of a non-stationary phenomenon. The impact of the time variable has not had …

Given the frequent changes in the Android framework and the continuous evolution of
Android malware, it is challenging to detect malware over time in an effective and scalable …