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Detecting Promotion Attacks in the App Market Using Neural Networks

  • Daojing He*
  • , Kai Hong
  • , Yao Cheng
  • , Zongli Tang
  • , Mohsen Guizani
  • *Corresponding author for this work
  • East China Normal University
  • Jiangxi University of Science and Technology
  • Agency for Science, Technology and Research, Singapore
  • Qatar University

Research output: Contribution to journalArticlepeer-review

Abstract

App markets play an important role in distributing various apps to mobile users. The app market vendors provide reputation systems to assist users in finding useful and reputable apps by ranking them. Unfortunately, there are signs that an app's ranking can be easily manipulated, which causes unfair competition for those highly ranked ones. Here we propose a novel approach based on deep learning to detect such malicious ranking manipulations. The proposed neural network has a novel architecture that is able to incorporate a variety of features designed from the publicly available application information in the app market. We have conducted extensive experiments as well as individual case analysis and the results demonstrate the effectiveness of our proposed approach.

Original languageEnglish
Article number8685774
Pages (from-to)110-116
Number of pages7
JournalIEEE Wireless Communications
Volume26
Issue number4
DOIs
StatePublished - Aug 2019
Externally publishedYes

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