An Advanced Machine Learning Framework for Cybersecurity

Abstract

AbstractThe world is turning out to be progressively digitalized raising security concerns and the urgent requirement for strong and propelled security innovations and procedures to battle the expanding complex nature of digital assaults. This paper examines how AI is being utilized in digital security in both resistance and offense exercises, remembering exchanges for digital attacks focused on AI models. Digital security is the assortment of approaches, systems, advancements, and procedures that work together to ensure the confidentiality, trustworthiness, and accessibility of processing assets, systems, programming projects, and information from attacks. Machine learning-based examination for cybersecurity is the following rising pattern in digital security, planned for mining security information to reveal progressed focused on digital threats and limiting the operational overheads of keeping up static relationship rules. In this paper, we are mainly focusing on the detection and diagnosis of various cyber threats based on machine learning.KeywordsCybersecurityMachine learningThreatGANAnomaly detection