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A Systematic Literature Review of Multimodal Analysis Techniques for Malware Detection

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dc.citedby0
dc.contributor.authorIbrahim Z.-A.en_US
dc.contributor.authorIsmail S.A.en_US
dc.contributor.authorRahim F.A.en_US
dc.contributor.authorid57203863738en_US
dc.contributor.authorid56943570600en_US
dc.contributor.authorid57350579500en_US
dc.date.accessioned2025-03-03T07:45:02Z
dc.date.available2025-03-03T07:45:02Z
dc.date.issued2024
dc.description.abstractAs cyber threats continue to evolve in complexity, traditional malware detection methods often fall short in identifying sophisticated attacks. Multimodal analysis, which integrates various data sources and analytical methods, has emerged as a promising approach to enhance malware detection capabilities. This paper presents a systematic literature review (SLR) of existing research on multimodal analysis techniques for malware detection. We conducted an extensive search across two major databases and identified 31 studies that explore the multimodal approaches for malware detection. Our review synthesizes the methodologies, modalities, and evaluation metrics used in these studies, highlighting their strengths and limitations. The findings reveal that multimodal approaches significantly improve detection accuracy and robustness compared to single-modality methods. However, challenges such as data integration complexity, computational overhead, scalability, and transparency remain. This review also identifies research gaps and suggests directions for future work to further advance the field of malware detection. ? 2024 IEEE.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.1109/ICSSA62312.2024.10788667
dc.identifier.scopus2-s2.0-85216511165
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85216511165&doi=10.1109%2fICSSA62312.2024.10788667&partnerID=40&md5=a04b8c4970e08c0db88ec5025e924a50
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/36835
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.sourceScopus
dc.sourcetitle2024 5th International Conference on Smart Sensors and Application: Shaping the Future of Intelligent Innovation, ICSSA 2024
dc.subjectAnalysis techniques
dc.subjectCyber security
dc.subjectCyber threats
dc.subjectDetection methods
dc.subjectMalware detection
dc.subjectMulti-modal
dc.subjectMulti-modal analyze
dc.subjectMulti-modal approach
dc.subjectMultimodal analysis
dc.subjectSystematic literature review
dc.subjectCyber attacks
dc.titleA Systematic Literature Review of Multimodal Analysis Techniques for Malware Detectionen_US
dc.typeConference paperen_US
dspace.entity.typePublication
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