Unleash the power for tensor: A hybrid malware detection system using ensemble classifiers

Jieqiong Hou, Minhui Xue, Haifeng Qian

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

1 Scopus citations

Abstract

The extensive growth of smartphones has spawned the propagation of malicious applications. Due to the increasing use of polymorphic malware, detection is becoming more difficult. To this end, ensemble learning has been proposed to improve accuracy in malware detection, without severely sacrificing time complexity. In this paper, we propose a hybrid detection system, TFBOOST, which incorporates the tensor filter algorithm into boosting ensemble generalization architecture, in order to improve detection efficacy. TFBOOST uses a static analysis to extract features and a level-by-level boosting structure with re-sampling process to diversify base learners. Experimental results show that TFBOOST generally outperforms state-of-The-Art ensemble algorithms with higher detection precision and lower false positive rates. Finally, we visually interpret the high-level results of TFBOOST and conjecture that repackaged malware is the mainstay of potential malware.

Original languageEnglish
Title of host publicationProceedings - 15th IEEE International Symposium on Parallel and Distributed Processing with Applications and 16th IEEE International Conference on Ubiquitous Computing and Communications, ISPA/IUCC 2017
EditorsGregorio Martinez, Richard Hill, Geoffrey Fox, Peter Mueller, Guojun Wang
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1130-1137
Number of pages8
ISBN (Electronic)9781538637906
DOIs
StatePublished - 25 May 2018
Event15th IEEE International Symposium on Parallel and Distributed Processing with Applications and 16th IEEE International Conference on Ubiquitous Computing and Communications, ISPA/IUCC 2017 - Guangzhou, China
Duration: 12 Dec 201715 Dec 2017

Publication series

NameProceedings - 15th IEEE International Symposium on Parallel and Distributed Processing with Applications and 16th IEEE International Conference on Ubiquitous Computing and Communications, ISPA/IUCC 2017

Conference

Conference15th IEEE International Symposium on Parallel and Distributed Processing with Applications and 16th IEEE International Conference on Ubiquitous Computing and Communications, ISPA/IUCC 2017
Country/TerritoryChina
CityGuangzhou
Period12/12/1715/12/17

Keywords

  • Boosting generalization
  • Ensemble learning
  • Malware detection
  • TFBOOST
  • Tensor decomposition

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