Searching Grade Scheme and Malware Recognition Within Google Play Application

Authors

  • Karthika. A  ME Scholar, Computer Science and Engineering, Velalar College of Engineering and Technology, Erode, Tamilnadu, India

DOI:

https://doi.org//10.32628/IJSRST196177

Keywords:

Fair Play, Dataset, Google Play, Malware, Google Bouncer, Proliferation.

Abstract

To introduce FairPlay, a work of fiction system that discover and leverages traces left behind by fraudsters, to distinguish both malware and apps subjected to investigate status fraud. FairPlay associate review behavior and distinctively combine detect review associations with linguistic and behavioral signals gleaned from Google Play app records (87 K apps, 2.9 M reviews, and 2.4M reviewers, unruffled over half a year), in order to organize suspicious apps. FairPlay achieves over 95 percent accuracy in classify gold regular datasets of malware, counterfeit and legitimate apps. Deceptive behaviors in Google Play, the most trendy Android app market, fuel Search rank abuse and malware proliferation. To make out malware, preceding work has paying attention on app executable and acquiescence analysis. It will show that 75 percent of the acknowledged malware apps engage in hunt rank fraud. FairPlay discover hundreds of fraudulent apps that presently evade Google Bouncer

References

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Published

2019-03-30

Issue

Section

Research Articles

How to Cite

[1]
Karthika. A, " Searching Grade Scheme and Malware Recognition Within Google Play Application, International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011, Volume 6, Issue 2, pp.08-12, March-April-2019. Available at doi : https://doi.org/10.32628/IJSRST196177