AI-Driven Cyber Threat Prediction: Analyzing Patterns in Cybercrime to Enhance Proactive Defense Strategies

The proliferation of cyberattacks in modern digital ecosystems poses significant challenges for businesses, governments, and individuals alike. Traditional reactive security measures have proven insufficient in countering sophisticated and evolving cyber threats. This research proposes an AI-driven predictive model to identify and prevent cyber threats before they materialize. By analyzing patterns of cybercrime incidents and leveraging advanced machine learning algorithms, we present a proactive security architecture capable of enhancing early threat detection. Experimental results demonstrate the model’s efficiency in terms of accuracy, precision, recall, and F1-score, indicating its viability as an industry solution.