Mal-ONE: A unified framework for fast and efficient malware detection

Charles Lim, Kalamullah Ramli

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

7 Citations (Scopus)

Abstract

With continuous increase rate of malware growth, detecting malware using conventional, signature-based method has failed to detect new or unknown malware. The new proposed framework is able to detect evasive malware and integrate key static and dynamic features to detect malware more accurately and efficiently. Our early experiments, based on 1603 malware samples, showed that the proposed system can analyze malware with the rate of about 144 seconds per binary code analyzed. Mal-One framework exhibits comparable overall time taken to detect and analyze the binary code to determine whether a binary code is malware or benign.

Original languageEnglish
Title of host publicationProceedings of 2014 2nd International Conference on Technology, Informatics, Management, Engineering and Environment, TIME-E 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-6
Number of pages6
ISBN (Electronic)9781479948055
DOIs
Publication statusPublished - 15 Jan 2015
Event2014 2nd International Conference on Technology, Informatics, Management, Engineering and Environment, TIME-E 2014 - Bandung, Indonesia
Duration: 19 Aug 201421 Aug 2014

Publication series

NameProceedings of 2014 2nd International Conference on Technology, Informatics, Management, Engineering and Environment, TIME-E 2014

Conference

Conference2014 2nd International Conference on Technology, Informatics, Management, Engineering and Environment, TIME-E 2014
CountryIndonesia
CityBandung
Period19/08/1421/08/14

Keywords

  • malware
  • malware analysis
  • malware detection
  • unified framework

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