GroupTie: Toward hidden collusion group discovery in app stores

Zhen Xie, Sencun Zhu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

17 Scopus citations

Abstract

The current centralized application (or app) markets provide convenient ways to distribute mobile apps. Their vendors maintain rating systems, which allow customers to leave ratings and reviews. Since positive ratings and reviews can lead to more downloads/installations and hence more monetary benefit, the rating systems have become a target of manipulation by some collusion groups hired by app developers. In this paper, we thoroughly analyze the features of hidden collusion groups and propose a novel method called GroupTie to narrow down the suspect list of collusive reviewers for further investigation by app stores. As members of a hidden collusion group have to work together more frequently and their ratings often deviate more from apps' quality, collusive actions will enhance their relation over time. We build a relation graph named tie graph and detect collusion groups by applying graph clustering. Simulation results show that the precision of GroupTie approaches to 99.70% and the recall is about 91.50%. We also apply our method to detect hidden collusion groups among the reviewers of 89 apps in Apple's China App Store. A large number of reviewers are discovered belonging to a large collusion group and several small groups.

Original languageEnglish (US)
Title of host publicationWiSec 2014 - Proceedings of the 7th ACM Conference on Security and Privacy in Wireless and Mobile Networks
PublisherAssociation for Computing Machinery
Pages153-164
Number of pages12
ISBN (Print)9781450329729
DOIs
StatePublished - 2014
Event7th ACM Conference on Security and Privacy in Wireless and Mobile Networks, WiSec 2014 - Oxford, United Kingdom
Duration: Jul 23 2014Jul 25 2014

Publication series

NameWiSec 2014 - Proceedings of the 7th ACM Conference on Security and Privacy in Wireless and Mobile Networks

Other

Other7th ACM Conference on Security and Privacy in Wireless and Mobile Networks, WiSec 2014
CountryUnited Kingdom
CityOxford
Period7/23/147/25/14

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications

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