International Journal of Science, Engineering and TechnologyAuthors: J.Bindhu Bhargavi
Abstract: Organizations can now identify, evaluate, and react to threats with previously unheard-of speed and precision thanks to artificial intelligence (AI), which has emerged as a key cyber security tool. However, cryptography is still necessary to safeguard non-repudiation, confidentiality, integrity, and authentication. This study examines how artificial intelligence (AI) improves network security and cryptographic systems, including intrusion detection, malware categorization, anomaly detection, adaptive authentication, and cryptanalysis. Additionally, it looks at issues like explainability, model bias, adversarial attacks, and privacy problems. Future directions in post-quantum cryptography, explainable AI, federated learning, and autonomous cyber security are discussed in the paper's conclusion. The results indicate that cyber security risks can be considerably decreased by putting in place strong data validation methods, safe model training procedures, ongoing monitoring, encryption, and moral AI governance. According to the study's findings, proactive and comprehensive cyber security measures are crucial for guaranteeing the secure and long-term implementation of AI applications in the digital age. The main cyber security threats connected to AI applications are examined in this study, along with practical mitigating techniques for dealing with these issues. Based on secondary data gathered from scholarly journals, industry reports, and reputable publications, the study takes a descriptive and analytical approach. The study underlines the necessity of AI-specific security frameworks and dr
