Abstract: Cybersecurity threats have become increasingly sophisticated, with phishing attacks remaining one of the most prevalent and damaging forms of cybercrime. This project focuses on developing a threat intelligence system designed to detect and mitigate phishing links in real time. By utilizing advanced machine learning algorithms and natural language processing techniques, the system analyzes URLs, email content, and website characteristics to identify malicious patterns indicative of phishing attempts. The model is trained on large datasets of legitimate and fraudulent links to maximize detection accuracy and reduce false positives. Additionally, the system integrates threat intelligence feeds to enhance adaptability against evolving attack strategies. The ultimate goal of this project is to provide a proactive cybersecurity solution that identifies phishing threats before they compromise user data or organizational networks. If effectively implemented, the system can strengthen online security, prevent financial losses, and support the broader effort toward safer digital ecosystems.

Downloads: | DOI: 10.17148/IJIREEICE.2026.14427