NEXT-GEN CYBERSECURITY SYSTEM FOR MESSAGE-BASED THREAT ANALYSIS

Abstract

As cyber threats continue to escalate, deploying strong security measures to protect sensitive information and essential Infrastructure is now more vital than ever. The paper “Next-Gen Cybersecurity System for Message-Based Threat Analysis” aims to provides a widespread use of email has made it a major and prime target for cyber threats such as phishing, malware, and attacks from insiders, which often bypass traditional security tools. This project introduces an AI-powered Email Threat Detection system that uses machine learning and Natural Language Processing (NLP) to spot and handle these risks in real time. By integrating rule-based methods, behavior analysis, and threat intelligence, the system can catch a wide range of threats, including complex phishing schemes, Advanced Persistent Threats (APTs), and harmful attachments. It uses models like Random Forest, Naive Bayes, and Isolation Forest and features a Flask-based dashboard for real-time monitoring. This solution offers a scalable, automated, and comprehensive approach to securing email communications. It helps organizations by offering valuable insights, reducing false positives, and actively fighting against new and changing cyber threats.