CYBERSECURITY RESEARCH USING MACHINE LEARNING METHODS
Abstract: It is nearly impossible to quantify or justify the reasons why cyber security has such an outsized impact in the constantly expanding and quickly expanding field of cyber security. Allowing malicious threats to operate anywhere, at any time, or in any situation is far from acceptable and may result in serious harm. It specifically applies to the complex web of internet users, business information, and consumer data that cyber security organizations are struggling to protect and contain. For individuals and families, businesses, governments, and academic institutions that operate within the parameters of the global network or internet, cyber security may be an important consideration. We will improve the state of cyber security by using machine learning. Infrastructure systems that are currently in use are included together in this. The high-tech infrastructure of today, which includes network and cyber security systems, collects a vast quantity of data and performs analytics on nearly all the important components of mission-critical systems. Machine learning and artificial intelligence (AI) are gaining speed and gathering immense momentum in most of the areas of today’s systems, whether it’s positioned on premises or within the cyber security house, while people still provide the key operational oversight and insightful insights into the infrastructure of today.
Keywords: Machine Learning, cyber security, k-means, Random Forest, SVM etc.