An intelligent multi-agent based detection framework for classification of Android malware

Abstract

Android is currently the most popular operating system for smartphone devices with over 900 million installations until 2013. It is also the most vulnerable platform due to allowing of software downloads from 3rd party sites, loading additional code at runtime, and lack of frequent updates to known vulnerabilities. Securing such devices from malware that targets users is paramount. In this paper, we present a Jade agent based framework targeted towards protecting Android devices. We also focus on scenarios of use where such agents can be dynamically launched. We believe, a detection technique has to be intelligent due to limited battery constraints of these devices. Moreover, battery utilization might become secondary in certain settings where detection accuracy is given a higher preference. In this framework, the expensive analysis components utilizing machine-learning algorithms are pushed to server side, while agents on the Android client are used mainly for intelligent feature gathering. © 2014 Springer International Publishing.