User feedback analysis for mobile malware detection

Tal Hadad, Bronislav Sidik, Nir Ofek, Rami Puzis, Lior Rokach

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

With the increasing number of smartphone users, mobile malware has become a serious threat. Similar to the best practice on personal computers, the users are encouraged to install anti-virus and intrusion detection software on their mobile devices. Nevertheless, their devises are far from being fully protected. Major mobile application distributors, designated stores and marketplaces, inspect the uploaded application with state of the art malware detection tools and remove applications that turned to be malicious. Unfortunately, many malicious applications have a large window of opportunity until they are removed from the marketplace. Meanwhile users install the applications, use them, and leave comments in the respective marketplaces. Occasionally such comments trigger the interest of malware laboratories in inspecting a particular application and thus, speedup its removal from the marketplaces. In this paper, we present a new approach for mining user comments in mobile application marketplaces with a purpose of detecting malicious apps. Two computationally efficient features are suggested and evaluated using data collected from the”Amazon Appstore”. Using these two features, we show that feedback generated by the crowd is effective for detecting malicious applications without the need for downloading them.

Original languageEnglish
Title of host publicationICISSP 2017 - Proceedings of the 3rd International Conference on Information Systems Security and Privacy
EditorsPaolo Mori, Steven Furnell, Olivier Camp
PublisherSciTePress
Pages83-94
Number of pages12
ISBN (Electronic)9789897582097
DOIs
StatePublished - 1 Jan 2017
Event3rd International Conference on Information Systems Security and Privacy, ICISSP 2017 - Porto, Portugal
Duration: 19 Feb 201721 Feb 2017

Publication series

NameICISSP 2017 - Proceedings of the 3rd International Conference on Information Systems Security and Privacy
Volume2017-January

Conference

Conference3rd International Conference on Information Systems Security and Privacy, ICISSP 2017
Country/TerritoryPortugal
CityPorto
Period19/02/1721/02/17

Keywords

  • Malware Detection
  • Mobile Malware
  • Review Mining
  • Text Mining
  • User Feedback Analysis

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems
  • Safety, Risk, Reliability and Quality
  • Computer Science Applications

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