Adaptive Cybersecurity Protocol with Real-Time Threat Detection

A software-defined cybersecurity protocol that uses adaptive neural networks to detect and neutralize threats in real-time. The system learns from each attack pattern, continuously improving its detection accuracy which currently exceeds 99.7%. Unlike traditional signature-based systems, this protocol detects zero-day vulnerabilities and novel attack vectors. It integrates seamlessly with existing enterprise infrastructure through standard APIs. With cybersecurity spending projected to exceed $300B annually, this patent offers significant licensing revenue potential across enterprise software, cloud services, and IoT platforms.