The use of mobile devices is rising daily in this technological era. A continuous and
increasing number of mobile applications are constantly offered on mobile marketplaces to …

The Java platform provides various cryptographic APIs to facilitate secure coding. However,
correctly using these APIs is challenging for developers who lack cybersecurity training …

Despite the continued research and progress in building secure systems, Android
applications continue to be ridden with vulnerabilities, necessitating effective detection …

Malware detection at scale in the Android realm is often carried out using machine learning
techniques. State-of-the-art approaches such as DREBIN and MaMaDroid are reported to …

Machine learning (ML)-based Android malware detection has been one of the most popular
research topics in the mobile security community. An increasing number of research studies …

It is critical for research to have an open, well-curated, representative set of apps for
analysis. We present a collection of open-source Android apps collected from several …

Android is nowadays the most popular operating system in the world, not only in the realm of
mobile devices, but also when considering desktop and laptop computers. Such a popularity …

Abstract System call sequences representing the runtime behavior of an application is
particularly useful for anomaly detection in mobile applications. However, one of the main …

As APIs become the backbone of modern digital ecosystems, ensuring their security against
evolving cyber threats is critical. Traditional security measures often fall short in detecting …

Android developers heavily use reflection in their apps for legitimate reasons. However,
reflection is also significantly used for hiding malicious actions. Unfortunately, current state …