GOOGLE PLAY STORE BASED APPLICATIONS FOR SEARCH RANK FRAUD AND MALWARE DETECTION

Abstract

Google play store contains million of apps and thousands of applications are published on every day. To promote the app and make the users to download is becoming complicated; the published try to increase the visibility of the app on the search console. Also it becomes difficult for the users to identify the malware app and download the good one. Few publishers on the play store try to increase their apps rank with fraud and black hat methods. The publishers increase their ranking by create fake bot reviews; provide fake rating through fake accounts. This misleads the users to download the malware apps from the store. In the proposed model, we try to identify the fair reviews and fake reviews by mining the reviewer profile, their rating patterns. With help of fair play detection we also identify that most of the malware apps use fraud ranking strategies to improve their downloads.