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Anti-Obfuscation Techniques: Recent Analysis of Malware Detection

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dc.contributor.authorGorment N.Z.en_US
dc.contributor.authorSelamat A.en_US
dc.contributor.authorKrejcar O.en_US
dc.contributor.authorid57201987388en_US
dc.contributor.authorid24468984100en_US
dc.contributor.authorid14719632500en_US
dc.date.accessioned2023-05-29T09:36:30Z
dc.date.available2023-05-29T09:36:30Z
dc.date.issued2022
dc.descriptionMachine learning; Malware; Analysis tools; Anti virus; Anti-obfuscation; Comparatives studies; Machine learning algorithms; Malware analysis; Malware detection; Malwares; Obfuscation technique; Stealthy malware; Learning algorithmsen_US
dc.description.abstractOne 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 The authors and IOS Press. All rights reserved.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.3233/FAIA220249
dc.identifier.epage192
dc.identifier.scopus2-s2.0-85139749407
dc.identifier.spage181
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85139749407&doi=10.3233%2fFAIA220249&partnerID=40&md5=470a2c46a06666b19d7c5cb453892c6c
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/26748
dc.identifier.volume355
dc.publisherIOS Press BVen_US
dc.sourceScopus
dc.sourcetitleFrontiers in Artificial Intelligence and Applications
dc.titleAnti-Obfuscation Techniques: Recent Analysis of Malware Detectionen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
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