Mining permission patterns for contrasting clean and malicious android applications

Veelasha Moonsamy, Jia Rong, Shaowu Liu

Research output: Contribution to journalArticleResearchpeer-review

69 Citations (Scopus)

Abstract

An Android application uses a permission system to regulate the access to system resources and users' privacy-relevant information. Existing works have demonstrated several techniques to study the required permissions declared by the developers, but little attention has been paid towards used permissions. Besides, no specific permission combination is identified to be effective for malware detection. To fill these gaps, we have proposed a novel pattern mining algorithm to identify a set of contrast permission patterns that aim to detect the difference between clean and malicious applications. A benchmark malware dataset and a dataset of 1227 clean applications has been collected by us to evaluate the performance of the proposed algorithm. Valuable findings are obtained by analyzing the returned contrast permission patterns.

Original languageEnglish
Pages (from-to)122-132
Number of pages11
JournalFuture Generation Computer Systems
Volume36
DOIs
Publication statusPublished - 2013
Externally publishedYes

Keywords

  • Android permission
  • Biclustering
  • Contrast mining
  • Data mining
  • Permission pattern

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