Abstract
Mobile phones are mastering our day to day scheduling, entertainment, information and almost every aspect of life. With the increasing human dependence on smart phones, threats against these devices have also increased exponentially. Almost all the mobile apps are playing with the mobile user's privacy besides the targeted actions by the malicious apps. Android applications use permissions to use different features and resources of mobile device along with the intents to launch different activities. Various aspects of permission framework have been studied but sufficient attention has not been given to the intent framework. This work is first of its kind which is investigating the combined effects of permissions and intent filters to distinguish between the malware and benign apps. This paper proposes a novel approach to identify the malicious apps by analyzing the permission and intent patterns of android apps. This approach is supplemented with the machine learning algorithms for further classification of apps. Performance of proposed approach has been validated by applying the technique to the available malicious and benign samples collected from a number of sources.