A Review on Android Ransomware Detection Using Deep Learning Techniques

In the past few years Android becomes prominent operating systems attracting many people. It is not only attracting users but also attackers to implement and spread malicious data onto our phones or tablets. Android Ransomware is one of the most spreading attacks through all the globe which is a class of malware that aims to prevent the users from accessing the operating system, and encrypts important data stored on their device. This kind of attacks are constantly being renewed to produce a new family and it becomes difficult for traditional machine learning techniques to discover them and thus prevent them from penetrating users' devices. There are few recent studies on the subject of android ransomwares detection using deep learning methods. This paper for most part focuses on two targets: the first is to provide an overview of ransomware and deep learning techniques and the second is to conduct a comprehensive review on more than 20 papers related to detecting android ransomware using deep learning methods. In addition, this study compared between the most relevant reviewed papers -a total of 8- including their limitations in addition to listing a significant challenges and open issues.