AI for Cybersecurity Threat Detection: A Machine Enabled Computing Perspective
Mayuri Mishra, Rohit Raj Pradhan, Kesab Agrawalla, Raveendranadh Bokka · 2025
With the increasing sophistication of cyber threats through Advanced Persistent Threats, ransomware, and insider attacks, innovative cybersecurity strategy is required, and AI represents a crucial instrument that uses deep learning and reinforcement learning to determine, analyze, and mitigate risks. This paper discusses AI-based cybersecurity, outlining a new model for AI, which improves on threat detection and response efficiency by increasing explainability. Analyzing large datasets and recognizing attack patterns and vulnerabilities to predict them has significantly improved the anomaly detection system and threat mitigation. The model also ensures that it follows ethical standards, including bias and transparency in AI-driven security. The results of this study show the significant advancements of cybersecurity resilience by integrating AI into modern threat defense. This AI-based approach offers scalable, adaptive, and proactive security. It allows organizations to effectively be prepared to deal with increasingly changing cyber threats.