A novel and efficient aggregation method for ranking Fraud detection in mobile apps

VUPPU.SRAVANTHI , Dr.M.SADANANDAM

Mobile Apps, ranking fraud detection, aggregation method, data ranking records, rating and review.

Present mobile technology is more popular due to mobile apps usage very high in the market world. Large numbers of mobile apps are uploaded daily in Google play store from different companies. So Mobile users are downloading apps based on review and rating of the app. so some companies to improve sales and increase usage of users of their apps they are giving fake ranking to their app to attract the users for downloading. Present we have big key challenge is ranking fraud in market world. In this paper we implement novel mechanism to fake ranking detection system for mobile users. And we differentiate three types of data collected from data records. Those are based on ranking, rating g and review by the users to that particular app .By using aggregation method we can aggregated this proofs of data. In this research paper we proposing two types of implementations like first one is exact scores and ratings of the app and, the fake rating and feedbacks by a similar user for approaching up that app on the leader board are controlled.To avoid frauding we approach two ways one is single users should give rating only once based on user login and another one is based on ip address that restricted the no of logins per day, our proposed system can analysed with real world app data from app store in long time.

Published Paper   E-Certificate

"A novel and efficient aggregation method for ranking Fraud detection in mobile apps", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.3, Issue 9, page no.61 - 63, September-2018, Available :https://ijsdr.org/papers/IJSDR1809009.pdf

Volume 3 Issue 9, September-2018

Pages : 61 - 63

Paper Reg. ID: IJSDR_180625

Published Paper Id: IJSDR1809009

Downloads: 000346998

Research Area: Engineering

Country: -, -, -

Published Paper PDF: https://ijsdr.org/papers/IJSDR1809009

Published Paper URL: https://ijsdr.org/viewpaperforall?paper=IJSDR1809009

ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJSDR(IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition