NASAM: Novel Approach to Secure Android Devices from Malware based on Apps Behaviour
Sagar Vitthal Shinde, Amrita A. Manjrekar
Android is preferred platform for mobile devices. Smartphone?s and mobile tablets are speedily indispensable in way of life. Android has been the most widespread open sources mobile OS. On the one aspect android users are increasing, but other side malicious activity also at the same time increasing. The risk of malware (Malicious apps) is sharply increasing in android platform, android mobile malware detection and prevention has become a very important research topic. Some malware attacks will build the phone partially or totally unusable, cause unwanted SMS/MMS (short message service/multimedia messaging service) charge, money, or expose personal data various applications contain wrong or incorrect info conduct code, however those don't seem to be really malicious apps. Present system categories such apps as malware apps, which may create problems in a system. The more accurate/proper system is required to classify malware apps. This NASAM system classifies android applications with the help of recent feature extraction algorithm. In this system android features are taken from feature set to detect malware on four phases package, user, application, and validation phase. The malware detection is based on behavioural and classified according to their risk (High, Medium, and Low). This is useful for the user to handle the system (Application) very smoothly & will provide more secure system.
Keywords: Android Security, Android Permissions, Android malware detection and prevention, feature extraction, behavioral base, Risk analysis
Edition: Volume 6 Issue 6, June 2017
Pages: 2792 - 2799