Author
Listed:
- S. Hema Latha
- Manepalli Prasanth Kumar
Abstract
Fraudulent behaviors in Google Play, the most popular Android app market, fuel search rank abuse and malware proliferation. To identify malware, previous work has focused on app executable and permission analysis. In this paper, we introduce FairPlay, a novel system that 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 (87K apps, 2.9M reviews, and 2.4M reviewers, collected over half a year), in order to identify suspicious apps. FairPlay achieves over 95% accuracy in classifying gold standard datasets of malware, fraudulent and legitimate apps. We show that 75% of the identified malware apps engage in search rank fraud. FairPlay discovers hundreds of fraudulent apps that currently evade Google Bouncer’s detection technology. FairPlay also helped the discovery of more than 1,000 reviews, reported for 193 apps that reveal a new type of “coercive” review campaign: users are harassed into writing positive reviews, and install and review other apps.
Suggested Citation
S. Hema Latha & Manepalli Prasanth Kumar, 2018.
"Fair Play Technology Using In Search Rank Fraud and Malware Detection in Google,"
International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 4(2), pages 77-80, April.
Handle:
RePEc:jbh:ijsrcs:v4:y2018:i2:id:hcseit1833617
Note: Article URL: https://ijsrcseit.com/CSEIT1833617
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