DISCOVERY OFRANKINGFRAUD FOR MOBILE APPS

Authors

  • NAVEEN IJERI Department of CSE,KLS Gogte Institute Of Technology,Belagavi
  • PREETIGANAGI Department of CSE,KLS Gogte Institute Of Technology,Belagavi
  • PRIYANKA RAMBAN Department of CSE,KLS Gogte Institute Of Technology,Belagavi

Keywords:

Mobile Apps, Ranking Fraud Detection, Evidence Aggregation, Recommendation app

Abstract

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. 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. In this project, we provide a holistic view of ranking fraud and propose a ranking fraud detection system for mobile Apps. We investigate two types of evidences i.e. ranking based evidences, rating based evidences by modelling Apps’ ranking and rating behaviours through statistical hypotheses tests. We evaluate the proposed system with real-world App data collected from the App Store for a long time period. In the experiments we validate the effectiveness of the proposed system and show the scalability of the detection algorithm as well as some regularity of ranking fraud activities

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Published

2021-03-27

Issue

Vol. 4 No. 6 (2017): IJIERT

Section

Articles

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