Discovery of Ranking Fraud for Mobile Applications

Discovery of Ranking Fraud for Mobile Applications

G Siva Manikanta, Shrija Madhu

G Siva Manikanta, Shrija Madhu "Discovery of Ranking Fraud for Mobile Applications" Published in International Journal of Trend in Research and Development (IJTRD), ISSN: 2394-9333, Special Issue | NCETC-17 , April 2017, URL:

Ranking fraud in the mobile App market refers to fraudulent or misleading tricks which have a purpose of bumping up the Apps in the status list. Indeed, it becomes more and more frequent for App developers to use shady means, such as inflating 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. To this end, in this paper, this provides a holistic view of ranking fraud and proposes a ranking fraud detection system for mobile Apps. Expressly, we first propose to accurately locate the ranking fraud by mining the active periods, namely leading sessions, of mobile Apps. Such leading sessions can be leveraged for detecting the local anomaly instead of global anomaly of App rankings. Furthermore, this investigate three types of evidences, i.e., ranking based evidences, rating based evidences and review based evidences, by modeling Apps’ ranking, rating and review behaviors through statistical hypotheses tests. In addition, In this propose an optimization based aggregation method to integrate all the evidences for fraud detection. Finally, we evaluate the proposed system with real-world App data collected from the IOS App Store for a long time period. In the experiments, can validate the success of the planned system, and show the scalability of the detection algorithm as well as some regularity of ranking fraud activities.

Mobile Apps, ranking fraud detection, evidence aggregation, historical ranking records, rating and review.

Special Issue | NCETC-17 , April 2017


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