Industrial Control System Security Monitoring via Data Correlation
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Solution Overview
Problem
Industrial control systems face challenges in detecting advanced persistent threats and sabotage malware, which can lead to catastrophic damage due to their difficulty in detection and the inability of existing systems to recognize unknown or unrecognizable security events.
Innovation Solution
A method and apparatus for monitoring industrial control systems by collecting and aggregating data from both internal and external sources, correlating it with previous data to identify security risks, and reacting to potential threats through autonomous or manual actions, utilizing sensors, agents, and external security databases to provide early detection and response capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If data is collected and analyzed from multiple internal and external sources to detect security threats, then detection capability improves, but system complexity increases
Solution Approach 1:
The monitoring system is divided into multiple independent data collection modules, each responsible for specific data sources (internal system data, external threat intelligence, vulnerability databases). This segmentation allows the complex monitoring task to be distributed across modular components, improving detection capability while managing system complexity through organized modularity.
Solution Approach 2:
The patent introduces an intermediary analysis layer that collects data from multiple sources, processes and correlates the information, and generates security assessments. This intermediary layer acts as a mediator between raw data collection and security decision-making, enabling comprehensive threat detection while abstracting the complexity from the core monitoring function.
2Reliability
If comprehensive data collection from multiple sources is performed to identify security risks, then security monitoring effectiveness improves, but processing time increases
Solution Approach 1:
The system performs preliminary actions by pre-collecting and pre-processing security data from external sources such as threat intelligence feeds and vulnerability databases before actual security events occur. This advance preparation allows the system to quickly correlate incoming data with pre-analyzed information, improving monitoring effectiveness while reducing real-time processing time.
Solution Approach 2:
The monitoring system operates continuously to collect and analyze security data from multiple sources without interruption. This continuous operation ensures that security threats are detected as they emerge, maintaining high monitoring effectiveness while distributing processing load over time rather than concentrating it during critical events.
3Speed
If the system monitors and analyzes security events in real-time, then early detection capability improves, but computational resource consumption increases
Solution Approach 1:
The system applies local quality by focusing computational resources on specific critical data sources and security parameters that are most relevant to detecting industrial control system threats. Rather than uniformly processing all collected data with equal intensity, the system selectively intensifies analysis where security risks are most likely to manifest, improving detection speed while optimizing resource consumption.
Data Source
AI summary
A method is for monitoring an industrial control system. The method comprises collecting data from one or more sources external to the industrial control system; collecting data from one or more internal sources on the industrial control system; aggregating data collected from said internal sources or from said external sources; correlating said collected data by analyzing and interpreting said collected data in view of previously collected data so as to monitor the security of the industrial control system. An apparatus is for performing the method.