Generic fuzzer for scanning cyber physical, computer and network connected device systems

Background

As digital infrastructures become more complex and vital, the frequency and sophistication of cyber threats continue to grow. Traditional network security tools often rely on static rule sets or signature-based detection systems, which are increasingly ineffective against novel or adaptive threats. Proactive and intelligent cybersecurity solutions are essential for large enterprises, critical infrastructure, and government networks that need ongoing protection. This invention addresses the growing demand for real-time, context-aware, and scalable cybersecurity systems.

Advanced Cybersecurity Systems | NDSU Research Foundation

System Architecture for Cybersecurity Processing and Threat Analysis Deployment

Invention Summary

This patent application discloses a next-generation cybersecurity system designed to analyze, detect, and mitigate vulnerabilities in networked infrastructures using advanced artificial intelligence and machine learning techniques. The system employs a dynamic risk engine that continuously monitors network behavior, configuration states, and threat intelligence data to assess vulnerabilities in real time. It integrates both internal and external data sources—including system logs, anomaly detection models, and known threat databases—to build a comprehensive risk profile for any network node or device. A key innovation is its hierarchical architecture, which allows scalable deployment across various network layers—from endpoint devices to core servers—while maintaining centralized control and analytics. The AI models are trained to recognize not only known attack vectors but also emerging threats by identifying patterns of anomalous behavior. The system also includes automated mitigation capabilities, such as traffic throttling, access reconfiguration, and alert prioritization, which significantly reduce response time and human intervention. Moreover, it supports adaptive learning by continuously refining its models based on feedback and new data, ensuring evolving defense mechanisms. This makes it highly suitable for enterprise-scale networks, critical infrastructure systems (e.g., energy grids, transportation), and high-security environments like defense or finance.

Benefits

Real-time threat and vulnerability detection
Scalable and adaptive AI-based analysis
Automated mitigation and response mechanisms
Integration of diverse threat intelligence sources
Suitable for both enterprise and critical infrastructure

Applications

Enterprise IT networks
Government and defense cybersecurity
Smart grid and critical infrastructure protection
Financial and healthcare data systems
Industrial IoT and smart city networks

Patent

This technology has a U.S. Patent US20240403445A1 pending and is available for licensing/partnering opportunities.

Contact

NDSU Research Foundation
info(at)ndsurf(dot)org
(701) 231-8173

NDSURF Tech Key

RFT, 686, RFT686

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