The Power of AI and Machine Learning in Cybersecurity: Innovations and Challenges

Abstract

Networks and sensitive data are no longer adequately protected by traditional security methods due to the ongoing evolution and sophistication of cyber-attacks. Cybersecurity can be enhanced with the exploitation of machine learning and artificial intelligence techniques, which make threat detection more effective and efficient. This article, while giving an outline of the field's present position, discusses the difficulties in adapting machine learning and artificial intelligence (ML) to cybersecurity. The research discusses machine learning methods that are applied to tasks like malware classification, anomaly detection, and network intrusion detection. Lastly, the necessity for sizable labeled datasets, the adversarial attacks on machine learning models, and the adversity of deciphering models of black-box ML are some of the boundaries and challenges that are also covered.