Adaptive threat detection and real-time anomaly analysis for modern infrastructures

The RCF-Secure module provides an advanced, resonance-based approach to cybersecurity and operational anomaly detection. It analyzes system behavior across multiple layers — network traffic, application signals, infrastructure metrics and LLM-related activity — to identify unusual patterns and emerging threats before they escalate.

Using principles from the Resonant Compute Framework (RCF), the system recognizes deep structural correlations that traditional rule-based or statistical detectors often miss. Its goal is to deliver at least 30–40% improvement in detection accuracy, fewer false alarms, and more stable security operations.

What does RCF-Secure do?

The module continuously monitors and interprets system signals through:

• – real-time anomaly detection (unexpected traffic, unusual load, unknown processes, irregular activity),
• – adaptive threat prediction that identifies potential security incidents in advance,
• – resonance-based pattern analysis to detect hidden or slow-forming attack signatures,
• – automatic risk-mitigation actions, such as isolating suspicious processes,
• – an independent security layer that complements existing firewalls, IDS/IPS and SIEM platforms.

It functions as a fully external module — no architectural modification is required.

Key advantages

• – at least 30–40% improvement in detection accuracy
• – reduced false positives
• – prediction of emerging attack vectors
• – faster response times in critical situations
• – compatible with cloud, on-premise, hybrid and LLM-driven environments
• – simple integration into enterprise, financial, governmental or industrial systems

Why is it a safe and reliable solution?

• – does not alter existing security architecture
• – does not require new or sensitive data collection
• – uses only standard operational telemetry
• – hardware-agnostic, transparent and auditable
• – resistant to overload attempts and metric-obfuscation attacks

Where can it be deployed?

• – banking and financial systems
• – cloud service providers
• – enterprise infrastructures
• – AI/LLM-based operational environments
• – government and critical infrastructure
• – industrial IoT and autonomous systems

How it fits into the AVA ecosystem

The RCF-Secure module forms the security layer of the Resonant Intelligence architecture:

• – collaborates with AVA Core for deep pattern interpretation,
• – uses Meta-Hopfield structures for predictive pattern extraction,
• – operates alongside RCF-LIM and ADC-Optim,
• – and serves as the foundation of future global AVA-network security.

Project status

• – Ready-to-start project, suitable for pilots
• – low integration risk
• – easy to demonstrate and benchmark
• – applicable across a wide range of international environments