Search Rank Fraud and Malware Detection in Google Play Application
Author(s):
NISHA .R, DR. R. SUBHA, V. BALAMURUGAN
Keywords:
Graph Mining, Co-Review Mining, Clustering, FairPlay, Security, Clique detection.
Abstract
The survey of FairPlay and a novel system discovers and leverages traces left behind by fraudsters, to detect both malware and apps subjected to search rank fraud. FairPlay correlates review activities and uniquely combines detected review relations with linguistic and behavioral signals gleaned from Google Play app data in order to identify suspicious apps. Adversaries can have chances to launch attacks by gathering victim’s information continuously. This survey describe that an adversary can successfully infer a victim’s vertex identity and community identity by the knowledge of degrees within a time period. The survey also recommend to a new supervised clustering algorithm to find groups of data cluster. It directly incorporates the information of sample categories into the fraud clustering process.
Article Details
Unique Paper ID: 148112

Publication Volume & Issue: Volume 5, Issue 12

Page(s): 413 - 419
Article Preview & Download


Share This Article

Join our RMS

Conference Alert

NCSEM 2024

National Conference on Sustainable Engineering and Management - 2024

Last Date: 15th March 2024

Call For Paper

Volume 10 Issue 10

Last Date for paper submitting for March Issue is 25 June 2024

About Us

IJIRT.org enables door in research by providing high quality research articles in open access market.

Send us any query related to your research on editor@ijirt.org

Social Media

Google Verified Reviews