Survey: Fraud Detection and Discovery of Mobile Apps

Now a days everyone is using smart phones. There is need of various applications to be installed on smart phone. To download application smart phone user has to visit play store such as Google Play Store. Mobile App is a very popular and well known concept due to the rapid advertisement in the mobile technology and mobile devices. When user go to the play store then he is see the various application lists. This list is built on the basis of advertisement. Usually user doesnt have enough information about the application (i. e. which applications are useful or not). Then user see that list and downloads the applications. But sometimes that the downloaded application not useful. That means it is fraud in mobile application list. To avoid this fraud, we provide a holistic view of ranking fraud and propose a ranking fraud detection system for mobile Apps. We first propose to accurately locate the ranking fraud by mining the active periods, namely leading sessions, of mobile Apps. Then we investigate five types of evidences, i. e. , ranking based evidences, rating based evidences, review based evidences, recommendation based fraud detection, enhancing the algorithm of fraud detection, by modeling Apps ranking, rating and review behaviors through statistical hypotheses tests. Using these five evidences finally we are calculating aggregation. We evaluate our application with real world data collected form play store for long time period