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Anti-obfuscation techniques: Recent analysis of malware detection

One of the challenging issues in detecting the malware is that modern stealthy malware prefers to stay hidden during their attacks on our devices and be obfuscated. They can evade antivirus scanners or other malware analysis tools and might attempt to thwart modern detection, including altering the...

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Bibliographic Details
Main Authors:	Gorment, Nor Zakiah, Selamat, Ali, Krejcar, Ondrej
Format:	Conference or Workshop Item
Published:	2022
Subjects:	QA76 Computer software
Online Access:	http://eprints.utm.my/id/eprint/100542/ http://dx.doi.org/10.3233/FAIA220249
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id	my.utm.100542
record_format	eprints
spelling	my.utm.1005422023-04-17T06:52:14Z http://eprints.utm.my/id/eprint/100542/ Anti-obfuscation techniques: Recent analysis of malware detection Gorment, Nor Zakiah Selamat, Ali Krejcar, Ondrej QA76 Computer software One of the challenging issues in detecting the malware is that modern stealthy malware prefers to stay hidden during their attacks on our devices and be obfuscated. They can evade antivirus scanners or other malware analysis tools and might attempt to thwart modern detection, including altering the file attributes or performing the action under the pretense of authorized services. Therefore, it's crucial to understand and analyze how malware implements obfuscation techniques to curb these concerns. This paper is dedicated to presenting an analysis of anti-obfuscation techniques for malware detection. Furthermore, an empirical analysis of the performance evaluation of malware detection using machine learning algorithms and the obfuscation techniques was conducted to address the associated issues that might help researchers plan and generate an efficient algorithm for malware detection. 2022 Conference or Workshop Item PeerReviewed Gorment, Nor Zakiah and Selamat, Ali and Krejcar, Ondrej (2022) Anti-obfuscation techniques: Recent analysis of malware detection. In: 21st International Conference on New Trends in Intelligent Software Methodologies, Tools and Techniques, SoMeT 2022, 20 - 22 September 2022, Kitakyushu, Japan. http://dx.doi.org/10.3233/FAIA220249
institution	Universiti Teknologi Malaysia
building	UTM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Teknologi Malaysia
content_source	UTM Institutional Repository
url_provider	http://eprints.utm.my/
topic	QA76 Computer software
spellingShingle	QA76 Computer software Gorment, Nor Zakiah Selamat, Ali Krejcar, Ondrej Anti-obfuscation techniques: Recent analysis of malware detection
description	One of the challenging issues in detecting the malware is that modern stealthy malware prefers to stay hidden during their attacks on our devices and be obfuscated. They can evade antivirus scanners or other malware analysis tools and might attempt to thwart modern detection, including altering the file attributes or performing the action under the pretense of authorized services. Therefore, it's crucial to understand and analyze how malware implements obfuscation techniques to curb these concerns. This paper is dedicated to presenting an analysis of anti-obfuscation techniques for malware detection. Furthermore, an empirical analysis of the performance evaluation of malware detection using machine learning algorithms and the obfuscation techniques was conducted to address the associated issues that might help researchers plan and generate an efficient algorithm for malware detection.
format	Conference or Workshop Item
author	Gorment, Nor Zakiah Selamat, Ali Krejcar, Ondrej
author_facet	Gorment, Nor Zakiah Selamat, Ali Krejcar, Ondrej
author_sort	Gorment, Nor Zakiah
title	Anti-obfuscation techniques: Recent analysis of malware detection
title_short	Anti-obfuscation techniques: Recent analysis of malware detection
title_full	Anti-obfuscation techniques: Recent analysis of malware detection
title_fullStr	Anti-obfuscation techniques: Recent analysis of malware detection
title_full_unstemmed	Anti-obfuscation techniques: Recent analysis of malware detection
title_sort	anti-obfuscation techniques: recent analysis of malware detection
publishDate	2022
url	http://eprints.utm.my/id/eprint/100542/ http://dx.doi.org/10.3233/FAIA220249
_version_	1765296669888348160
score	13.211869

Anti-obfuscation techniques: Recent analysis of malware detection

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