PROVIDE SECURITY ABOUT RISK SCORE IN MOBILE APPLICATION’S

Bhambare Monali S, Kapse Poonam M, Gangurde Kirti S, Dane Tanuja S

Abstract: Now days as the use of mobile devices is increasing rapidly day by day, huge number of mobile apps are coming into the market. These apps ask the user access to various kinds of permissions, and also many of these perform the same task. The user comes at risk with presence of some malicious app due to access of permission it will get, as android provides a stand –alone defense mechanism with respect to malicious apps. Where it warns the user about the permissions the app requires, trusting that the user will make proper decision, which requires the user to have the technical knowledge and time, which is not user friendly for each user. Also classification of these apps can be useful in understanding the user preferences and can motivate the intelligent personalized services. But to effectively classify the app is a nontrivial task as limited contextual information is available. To address these two issues an approach is proposed where the apps will be classified first using the enriched contextual information from web search engine, then with the contextual features from the context-rich device logs of mobile users and calculating the risk score for the app in order to generate a user friendly metric for the user to use when choosing the app. This will help us to get effective classification of the mobile apps and protect the user’s mobile devices from malicious apps.

Keywords: Mobile apps classification, risk, malware, web knowledge, enriched contextual information.

DOI: https://doi.org/10.15623/ijret.2015.0409058