Detection of Malware using Machine Learning Approach

Abstract

Abstract: This proposal abstract outlines a new approach to classification of malware using machine learning algorithms. Malware detection is an essential task in cybersecurity to identify and mitigate potential threats posed by malicious software. This research proposes a new framework of Support Vector Classifiers and Decision Tree these are very know machine learning algorithms which will be used on malware detection. The proposed work is designed to effectively classify whether the network data is malware or normal behavioural characteristics. The designed approach is compared with traditional algorithms of Machine Learning, such as Support Vector Machines (SVM) and Decision Tree to evaluate its performance. The outcomes of this research are expected to yield on the development of more effective malware detection and prevention systems.