Application of Machine Learning on Fraud App Detection

Abstract

In today’s world, everyone is using smart phones and those are very important in our daily life. The extensive distribution of mobile devices and applications across society has helped create counterfeit apps amongst the major cyber security threats of today. There are so many fraud applications are available in the internet. Fake behavior is most popular in application stores like Google play store and apple’s application store. The growth of mobile apps was increased to 2.86 million at Google play store and makes the users in a fuzzy state while downloading the apps. There are many apps from which any app can be fraud, so the identification of true app is needed. Fraud apps basically deals with fake apps. So, our system will help the user to identify which application is true. In this paper we propose a method to detect the fraud application based on user reviews and ratings using Naive Bayes classifier. The user reviews can be collected from Google play store and classify the reviews into positive or negative by using sentimentanalysis