Detecting Rank Fraud of Applications

Author Name : Dr. P. Kanagaraju, V. Hrithikeshwar, S. Akash

ABSTRACT

It is known that every human in this world are mobile phone users in fact smart-phone users which runs in android operating system majorly. The project discovery of ranking fraud of mobile applications, develops a need to make a fraud less ,flawless results which shows correct application based on ranking, where it actually happen by searching fraud of applications. The fraud of Application is made by using bot farms and human water armies, where fraud is made by downloading application through various android devices and given fake ratings and reviews. These fake ratings and reviews affect the ranking of the application and confuse the normal user who wants to download the rightful application for their use. So, the crucial data relating particular application such as review have to be mined and other information have to be mined and place Pseudo Clique Finder(PCF) algorithm to detect fake applications  in application rank. In the existing system the fraud was detected after the fraud was done that is, the fraud was detected after the complaint of the Mobile Apps’ holder. The proposed system uses rating based evidences, ranking based evidences and review based evidences, by modelling Apps’ rating, review, and ranking behaviours. It is done through statistical hypothesis testing.