Analysis of Cyber Security Threats Using Machine Learning Techniques

Ranjana B Nadagoudar

doi:10.55524/ijircst.2024.12.1.7

Abstract

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.

Keywords

Malware Detection, Malware Family Detection, KNN, SVM, API Calls Argument

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Cites this article as

R. B. Nadagoudar "Analysis of Cyber Security Threats Using Machine Learning Techniques", International Journal of Innovative Research in Computer Science and Technology (IJIRCST), Vol-12, Issue-1, Page No-35-39, 2024. Available from: https://doi.org/10.55524/ijircst.2024.12.1.7

Corresponding Author

Ranjana B Nadagoudar

Assistant Professor, Department of Computer Science & Engineering, Visvesvaraya Technological University, Belagavi, India

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