Automated Multi-Domain Vulnerability Assessment for Critical Infrastructure
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Solution Overview
Problem
Existing systems and methods for multi-domain vulnerability assessments are inadequate as they lack automation, user-friendliness, and real-time data ingestion and analytics, making them inefficient for identifying vulnerabilities in critical infrastructure facilities.
Innovation Solution
The development of systems and methods that enable automated, real-time ingestion and analysis of wireless signal data to determine vulnerabilities, weaknesses, and threats in critical infrastructure facilities, using a pipeline that includes sensors, data processing systems, and interactive user interfaces.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated real-time data ingestion and analytics pipeline is implemented, then productivity and speed of vulnerability assessment is improved, but device complexity and implementation difficulty increases
Solution Approach 1:
The system divides the vulnerability assessment process into distinct modular components: data ingestion module, processing module, and analytics module. Each module handles specific tasks independently, allowing for easier implementation and maintenance while achieving automated real-time assessment capabilities.
Solution Approach 2:
The patent introduces standardized data formats and protocols as intermediaries between different system components. This abstraction layer simplifies the complexity by providing uniform interfaces for data exchange, making the overall system easier to implement despite its automated real-time capabilities.
2Ease of operation
If automated processing is implemented, then ease of operation is improved for non-experts, but measurement precision and expertise requirements may be compromised
Solution Approach 1:
The system performs self-validation and automated quality checks on the data processing pipeline. The analytics engine automatically verifies results and flags potential accuracy issues, allowing non-expert users to operate the system confidently while maintaining measurement precision through built-in validation mechanisms.
Solution Approach 2:
The patent implements feedback loops where the system continuously monitors its own performance and adjusts processing parameters to maintain accuracy. User feedback on assessment results is incorporated to refine the automated processing algorithms, ensuring precision improves over time while ease of operation is maintained.
3Reliability
If comprehensive multi-domain assessment is performed, then reliability and coverage of vulnerability identification is improved, but loss of time and processing duration increases
Solution Approach 1:
The system implements periodic scanning cycles where comprehensive multi-domain assessments are performed at scheduled intervals rather than continuously. Between comprehensive scans, the system performs rapid targeted checks on critical domains, maintaining reliable vulnerability detection while minimizing time loss through efficient use of assessment resources.
Solution Approach 2:
The patent applies preliminary filtering and triage to wireless signal data before comprehensive analysis. The system quickly identifies and prioritizes high-risk domains for detailed assessment while performing lighter checks on lower-risk areas, maintaining comprehensive coverage reliability while reducing overall processing time through intelligent resource allocation.
Data Source
AI summary
Systems and methods are provided for multi-domain vulnerability assessment. An exemplary system includes a plurality of wireless signal detectors, wherein each of the wireless signal detectors is configured to detect wireless signals of a respective wireless signal protocol of a plurality of wireless signal protocols. The wireless signal detectors transmit the signal data to a data processor that classifies the plurality of devices based on the wireless signal data, determines one or more device vulnerabilities associated with the plurality of devices based on the classification of the plurality of devices, and determine a plurality of device risks for the plurality of devices based on the plurality of device vulnerabilities.