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ESCAPE: entropy score analysis of packed executable

Published: 25 October 2012 Publication History

Abstract

Malware developers hide the malicious payload of malware binary by employing various obfuscation techniques. One such technique commonly applied is packing. Packer transforms the original bytes so it is difficult to recognize the behaviour of any executable. Although the contents of a file is changed, some byte patterns may be preserved across different packed executables. Malware detectors need to apply unpacking mechanism prior to any detection or analysis to every sample under consideration. In this paper, we have proposed a method that discriminate packed binaries from the native files to minimize the processing time of AV scanners. We have used the blockwise entropy score of byte features of the executable. Experimental results show that the proposed method is capable of identifying packed and native executable which are packed using different malware packers.

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Cited By

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  • (2024)Identifying Malware Packers through Multilayer Feature Engineering in Static AnalysisInformation10.3390/info1502010215:2(102)Online publication date: 9-Feb-2024
  • (2023)A survey on run-time packers and mitigation techniquesInternational Journal of Information Security10.1007/s10207-023-00759-y23:2(887-913)Online publication date: 1-Nov-2023
  • (2018)An Optimized Running Window Entropy Algorithm2018 National Cyber Summit (NCS)10.1109/NCS.2018.00016(72-77)Online publication date: Jun-2018
  • Show More Cited By

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cover image ACM Conferences
SIN '12: Proceedings of the Fifth International Conference on Security of Information and Networks
October 2012
226 pages
ISBN:9781450316682
DOI:10.1145/2388576
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Publication History

Published: 25 October 2012

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Author Tags

  1. entropy
  2. malware
  3. obfuscation
  4. packing
  5. unpacking

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Overall Acceptance Rate 102 of 289 submissions, 35%

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Cited By

View all
  • (2024)Identifying Malware Packers through Multilayer Feature Engineering in Static AnalysisInformation10.3390/info1502010215:2(102)Online publication date: 9-Feb-2024
  • (2023)A survey on run-time packers and mitigation techniquesInternational Journal of Information Security10.1007/s10207-023-00759-y23:2(887-913)Online publication date: 1-Nov-2023
  • (2018)An Optimized Running Window Entropy Algorithm2018 National Cyber Summit (NCS)10.1109/NCS.2018.00016(72-77)Online publication date: Jun-2018
  • (2015)An efficient block-discriminant identification of packed malwareSadhana10.1007/s12046-015-0399-x40:5(1435-1456)Online publication date: 21-Aug-2015

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