Invention:
GRID-LM is an advanced, AI-powered distributed model designed for Operational Technology (OT) network security monitoring, infrastructure threat detection, and response. By leveraging machine learning, GRID-LM can detect deviations from established baselines, helping organizations identify and respond to potential threats before they impact operations. By leveraging distributed resources within a local-based environment, GRID-LM aims to provide near-real-time threat detection and responses to enhance security around sensitive data and systems, ultimately providing a sophisticated layer of protection for critical infrastructure. While GRID-LM was developed as an automated network monitoring solution for OT infrastructure security, it can be adapted for use in other industries, such as water supply systems, transportation networks, healthcare systems, and telecommunications.
Background:
Industrial networks protect critical infrastructure vital to modern society. Operational technology (OT) industrial control system networks often struggle to effectively detect malicious communication or identify network-based threats, and historically have not been designed to monitor unauthorized internal activity. Connecting to external networks, such as commercial cloud-based environments in traditional Information Technology environments, can exacerbate existing security issues. In the field of cybersecurity, there is a significant gap in understanding and managing the complex behaviors of OT networks, which underscores the need for sophisticated defensive tools to aid administrators of building control systems. While current network security solutions often focus on edge-layer devices, the internal Industrial Control System network is typically left unmonitored, creating a significant visibility and security gap. GRID-LM addresses these challenges by leveraging AI and machine learning techniques to continuously monitor and analyze network activity, effectively detecting and responding to threats within industrial control systems and OT networks.
Applications:
- Network security, threat detection, and monitoring in
- Operational Technology infrastructure
- Industrial control systems
- Water supply systems
- Transportation networks
- Healthcare systems
- Telecommunications
- AI-based technology security
Advantages:
- Automates OT network security processes
- Near-real-time threat detection and response
- Leverages distributed resources
- Improves accuracy and speed in threat detection compared to traditional methods
- Supports continued business operations even when faults or anomalies are detected, minimizing disruption
- Addresses a gap in network security around internal activities
