Cyber Threat Prediction and Analysis Platform

The growing scale and sophistication of cybercrime in India present critical challenges for digital security. According to the Indian Cyber Crime Coordination Centre, nearly 7,000 complaints were recorded daily in May 2024, reflecting a 113.7% increase between 2021 and 2023 and a 60.9% surge from 2022 to 2023 alone. Significantly, approximately 85% of these cases were linked to financial online fraud, underscoring the urgent need for predictive solutions. This paper presents a Cyber Threat Prediction and Analysis Platform that forecasts future cyber incidents by state and year using the Random Forest algorithm. Cyber acts considered include hacking, tampering with computer source codes, and data/resource loss. The methodology integrates dataset collection, preprocessing, and classification, with measures to address class imbalance and data quality. The web-based platform, built with HTML, CSS, and JavaScript, enhances accessibility and user interaction by visualizing predictive results in real time. Experimental evaluation achieved 89% accuracy, demonstrating the model’s effectiveness in anticipating cybercrime trends and supporting proactive threat mitigation. The study highlights the importance of continuous innovation to strengthen cyber resilience and safeguard digital ecosystems.