Detecting Fraud in the Mobile App using 3-R Evidence Aggregation
||International Journal of P2P Network Trends and Technology (IJPTT)||
|© 2017 by IJPTT Journal|
|Volume - 7 Issue - 2
|Year of Publication : 2017|
|Authors : K.Devi, M.Menaka|
K.Devi, M.Menaka "Detecting Fraud in the Mobile App using 3-R Evidence Aggregation". International Journal of P2P Network Trends and Technology (IJPTT), V7(2):7-10 Mar - Apr 2017, ISSN:2249-2615, www.ijpttjournal.org, Published by Seventh Sense Research Group.
Mobile applications (apps) are software developed for use on mobile devices and made available through app stores. App stores are highly competitive markets where developers need to cater to a large number of users spanning multiple countries. This work hypothesizes that there exist country differences in mobile app user behavior and conducts one of the largest surveys to date of app users across the world, in order to identify the precise nature of those differences. And the country wise fraud detection in the mobile app is detected using ranking, rating, review of an app and the fraud in the mobile app is done by the fraudulent with the help of bot farms and the main characteristics of fraud app duplication of data, gathering information without user knowledge and app ranking algorithm is used to detect Fraud in the mobile apps.
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Requirements/specifications, market-driven software engineering, mobile application development, survey research, app user behavior, fraud detection , ranking, rating review and app ranking algorithm.