An Investigation into the Performances of the State-of-the-art Machine Learning Approaches for Various Cyber-attack Detection: A Survey

arXiv:2402.17045v1 Announce Type: cross
Abstract: To secure computers and information systems from attackers taking advantage of vulnerabilities in the system to commit cybercrime, several methods have been proposed for real-time detection of vulnerabilities to improve security around information systems. Of all the proposed methods, machine learning had been the most effective method in securing a system with capabilities ranging from early detection of software vulnerabilities to real-time detection of ongoing compromise in a system. As there are different types of …

abstract art arxiv computers cs.ai cs.cr cs.lg cyber cybercrime detection information investigation machine machine learning performances real-time security state survey systems type vulnerabilities