Real-Time Network Intrusion Prevention System Based on Machine Learning)
Computer Science and Information Technology · 2025/2026
The CyberTrap project offers a new way to detect threats using cyber deception. It fixes a main problem in traditional security systems, which often cannot reliably detect complex and long-term threats. By placing misleading virtual resources called “Honeytokens,” CyberTrap provides an immediate sign when a system is breached. These tokens are designed to look like real resources to an attacker. However, as soon as they are touched or used, they send a clear and accurate alert to cybersecurity administrators, giving them valuable time to respond. The project method includes reviewing existing research, building a central management platform and a monitoring agent, and running a series of simulated attack tests. The results aim to show how this approach greatly improves threat detection, speeds up response time, and provides a scalable solution to support effective responses against a wide range of advanced and complex cyber threats.