The widespread use of Android-based smartphones made it an important target for
malicious applications' developers. So, a large number of frameworks have been proposed …

Android has become the most widely used mobile operating system (OS) in recent years.
There is much research on methods for detecting malicious Android applications. Dynamic …

The goal of this research is to review the researcher's different attempts with respect to new
and emerging technology in malware detection techniques based on machine learning …

Recently, security incidents such as sensitive data leakage and video/audio hardware
control caused by Android malware have raised severe security issues that threaten Android …

Due to the exponential rise of mobile technology, a slew of new mobile security concerns
has surfaced recently. To address the hazards connected with malware, many approaches …

Dynamic analysis of Android malware suffers from techniques that identify the analysis
environment and prevent the malicious behavior from being observed. While there are many …

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 …

The ever increasing number of Android malware has always been a concern for
cybersecurity professionals. Even though plenty of anti-malware solutions exist, we …

The rapid growing trend of mobile devices continues to soar causing massive increase in
cyber security threats. Most pervasive threats include ransom-ware, banking malware …

The number of prominent ransomware attacks has increased recently. In this research, we
detect ransomware by analyzing network traffic by using machine learning algorithms and …