Anomaly Network Based Malware Detection System Using Hybrid Techniques

Abstract

Android OS is one of the widely used mobile operating systems. There is a huge increment in malware applications in android phones.  Smart android malware detection system (SAMDS) is an effort gear towards detecting malware application or malicious activities. This paper proposes a technique that can detect any malware application in android phone using anomaly based. It analyzes system calls' logs and also the conduct of an app and afterward produces signatures for malware conduct .This paper adopted the object oriented analysis and design method (OOADM), and uses the approach to model real world processes, operations and data in a more flexibly, efficiently and realistically manner. The paper goal is to raise user awareness of the permission-based system of Android phones and the threat it pose and provide counter measure system for more secured operations.