• Supreet kaur
• Prof. Sandeep Kaur Benipal

Over the past decade, the increasing sophistication of cyber threats has posed a significant challenge to even the most advanced security infrastructures. In parallel, Artificial Intelligence (AI) has emerged as a promising solution for identifying and mitigating these threats. The ability of AI algorithms to analyze extensive datasets is crucial for detecting the subtle patterns and anomalies that indicate a security breach. This research emphasizes the vital role of human cybersecurity expertise working in tandem with AI, exploring the historical evolution of cyber defence, the importance of human-machine collaboration, and a comparative analysis of existing and newly proposed models. The experimental results demonstrate that a voting classifier, which combines Bernoulli Naive Bayes, Random Forest, and K-Nearest Neighbors, consistently outperformed all other algorithms in this study, achieving the highest precision and F1-score. The study concludes by discussing the ethical implications, challenges, and limitations of integrating AI into cybersecurity

Artificial Intelligence, Machine Learning, cybersecurity, accuracy

"An Algorithmic Approach to Cybercrime Prevention", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 8, page no.e557-e562, August-2025, Available :http://www.jetir.org/papers/JETIR2508474.pdf

"An Algorithmic Approach to Cybercrime Prevention", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 8, page no. ppe557-e562, August-2025, Available at : http://www.jetir.org/papers/JETIR2508474.pdf