A Review on Ranking Based Fraud Detection in Android Market

Ranking fraud in the mobile App market refers to fraudulent or deceptive activities which have a purpose of bumping up the Apps in the popularity list. Indeed, it becomes more and more frequent for App developers to use shady means, such as inating their Apps sales or posting phony App ratings, to commit ranking fraud. While the importance of preventing ranking fraud has been widely recognized, there is limited understanding and research in this area. In this Paper we are reviewing various a holistic view of ranking fraud and propose a ranking fraud detection system for mobile Apps. Specically, we rst study various ranking fraud. Furthermore, we investigate different methodologies and characterised in into three types of evidences in fraud detection, i. e. , ranking based evidences, rating based evidences and review based evidences, by modelling Apps ranking, rating and review behaviours through statistical hypotheses tests. In addition, we will also propose an optimization based aggregation method to integrate all the evidences for fraud detection.