Artificial Intelligence and Cybersecurity: Innovations, Threats, and Defense Strategies

Abstract

The application of artificial intelligence (AI) to cybersecurity has been examined in this study, which reveals a landscape characterized by innovations, difficulties, as well as transformative potential. Looking into modern AI applications shows that deep learning models—most notably recurrent neural networks—dominate in threat detection. Empirical data demonstrates AI's remarkable effectiveness in threat analysis in real-time, enabling quick response protocols. Notwithstanding, obstacles like comprehensibility and vulnerability to hostile assaults underscore the necessity for additional investigation. Establishing explainable AI methods and strengthening defenses against hostile attacks are two recommendations. In the future, research must concentrate on improving AI models for interpretability and investigating cutting-edge tactics for robust cybersecurity against changing threats.