• KRUSHNA BHALKE
• SHRINIVAS BODKE
• ALMAN MOMIN
• VAISHNAV NARSINGKARPATIL
• MRS.PADMA NIMBHORE

Most of us use android and IOS Mobiles these days and also uses the play store or app store capability normally. Both the stores provide great number of application but unluckily few of those applications are fraud. Such applications dose damage to phone and also may be data thefts. Hence, such applications must be marked, so that they will be identifiable for store users. So we are proposing a web application which will process the information, comments and the review of the application. So it will be easier to decide which application is fraud or not. Multiple application can be processed at a time with the web application. Also User cannot always get correct or true reviews about the product on internet. So rating/comments will be judged by the admin and it would be easy for admin to predict the application as Genuine or Fraud.

Sentiment Analysis, Reviews Records, Mobile Fraud detection, Machine learning, Supervised Learning

"ONDISCOVERY OF RANKING FRAUD FOR MOBILE APPS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 4, page no.1912-1916, April-2020, Available :http://www.jetir.org/papers/JETIR2004463.pdf

"ONDISCOVERY OF RANKING FRAUD FOR MOBILE APPS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 4, page no. pp1912-1916, April-2020, Available at : http://www.jetir.org/papers/JETIR2004463.pdf