Toward detecting collusive ranking manipulation attackers in mobile app markets

Hao Chen, Daojing He, Sencun Zhu, Jingshun Yang

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

11 Scopus citations

Abstract

Incentivized by monetary gain, some app developers launch fraudulent campaigns to boost their apps' rankings in the mobile app stores. They pay some service providers for boost services, which then organize large groups of collusive attackers to take fraudulent actions such as posting high app ratings or inflating apps' downloads. If not addressed timely, such attacks will increasingly damage the healthiness of app ecosystems. In this work, we propose a novel approach to identify attackers of collusive promotion groups in an app store. Our approach exploits the unusual ranking change patterns of apps to identify promoted apps, measures their pairwise similarity, forms targeted app clusters (TACs), and finally identifies the collusive group members. Our evalu-ation based on a dataset of Apple's China App store has demonstrated that our approach is able and scalable to re- port highly suspicious apps and reviewers. App stores may use our techniques to narrow down the suspicious lists for further investigation.

Original languageEnglish (US)
Title of host publicationASIA CCS 2017 - Proceedings of the 2017 ACM Asia Conference on Computer and Communications Security
PublisherAssociation for Computing Machinery, Inc
Pages58-70
Number of pages13
ISBN (Electronic)9781450349444
DOIs
StatePublished - Apr 2 2017
Event2017 ACM Asia Conference on Computer and Communications Security, ASIA CCS 2017 - Abu Dhabi, United Arab Emirates
Duration: Apr 2 2017Apr 6 2017

Publication series

NameASIA CCS 2017 - Proceedings of the 2017 ACM Asia Conference on Computer and Communications Security

Other

Other2017 ACM Asia Conference on Computer and Communications Security, ASIA CCS 2017
CountryUnited Arab Emirates
CityAbu Dhabi
Period4/2/174/6/17

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Information Systems
  • Computer Networks and Communications
  • Software

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  • Cite this

    Chen, H., He, D., Zhu, S., & Yang, J. (2017). Toward detecting collusive ranking manipulation attackers in mobile app markets. In ASIA CCS 2017 - Proceedings of the 2017 ACM Asia Conference on Computer and Communications Security (pp. 58-70). (ASIA CCS 2017 - Proceedings of the 2017 ACM Asia Conference on Computer and Communications Security). Association for Computing Machinery, Inc. https://doi.org/10.1145/3052973.3053022