Amdetect : Android Malware Detection Using Machine Learning

Abstract

The basic idea behind malware is to take advantage of a victim's computer resources. Recent malware evolution has made it more resilient and adaptable to accomplish a variety of objectives, including anonymity for illicit activity, sensitive data theft, and denial of service (DoS). But generally, economics is the driving force. Malware families have created a broad range of methods to get money, from straightforward blackmail via a DoS threat to sophisticated bank trojans, with the hope of eventually making some fiduciary money. Cybercriminals look for new models in this unstoppable evolution in order to make rapid money. This method works really well with digital money. In recent years, protecting Android mobile and systems against cyberattacks has become increasingly important. Even though the majority of systems today are constructed with enhanced security features, there are still a significant number of
vulnerabilities, mostly brought about by old software, unsecured protocols and systems, and human mistake. malware detection in android mobiles can take on many different forms and aim for any infrastructure, including cloud computing, Mobile and Internet of
Things (IoT) devices.