Volume- 12
Issue- 1
Year- 2024
DOI: 10.55524/ijircst.2024.12.1.7 | DOI URL: https://doi.org/10.55524/ijircst.2024.12.1.7 Crossref
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)
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Ranjana B Nadagoudar
Nowadays malware detection is a problem that researchers have tried to solve for so many years by using enormous type of methods. The behaviors of two given malware variants remain similar, although their signatures could also be distinct. The proposed project mainly concentrates on classifying the malware families by considering the malware API sequence or API commands. This type of classification is helpful for the analyst as it helps them to get a better insight into the functioning of the malware.
Assistant Professor, Department of Computer Science & Engineering, Visvesvaraya Technological University, Belagavi, India
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Bingxing Wang, Yuxin Dong , Jianhua Yao, Honglin Qin, Jiajing Wang.
July 2024 - Vol 12, Issue 4
Mohit Apte.
July 2024 - Vol 12, Issue 4
Mohit Apte.
July 2024 - Vol 12, Issue 4