Paper Title
HARNESSING REAL-WORLD BUG HUNTING TECHNIQUES FOR ADVANCED REAL-TIME THREAT DETECTION AND PREVENTION

Abstract
The goal of this project, "Harnessing Real-World Bug Hunting Techniques for Advanced Real-Time Threat Detection and Prevention," is to create a state-of-the-art web- based cybersecurity platform that combines cutting-edge approaches with useful bug-hunting knowledge for reliable threat identification. It continuously monitors network traffic using machine learning models to detect and stop malicious activity in real time. To do this, it blocks and dynamically changes IP addresses to prevent unwanted access. User and Entity Behavior Analytics (UEBA) for anomaly detection, Security Orchestration, Automation, and Response (SOAR) for effective threat management, and a threat intelligence feed to remain informed about new attack vectors are some of the key features. The platform includes comprehensive logging for forensic investigations, predictive analytics, and a continuous learning module to improve detection algorithms. Its user- friendly interface also encourages teamwork, data aggregation, and collective protection, providing an all-encompassing and flexible cybersecurity solution that fortifies businesses' defenses against constantly changing threats. Keywords - Threat Intelligence Sharing, Anonymization, Data Aggregation, Collective Defense, Cloud Platform, Cybersecurity, Encryption, Privacy, Collaboration, Python.