Cyber Risk Score for OT Network Devices
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The increasing complexity and integration of Operational Technology (OT) systems in Smart Buildings make them highly vulnerable to cyber-attacks, posing significant risks to cybersecurity, regulatory compliance, and brand reputation.
Innovation Solution
A method and system for determining a cyber risk score for entities with multiple network devices, involving data collection from individual devices and external risk data sources, normalization, correlation, and aggregation to assess individual and overall cyber risk.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If OT systems are integrated with IT ecosystems for economic and practical reasons, then system functionality and connectivity are improved, but cybersecurity vulnerability and system complexity increase
Solution Approach 1:
The patent segments the cybersecurity assessment into device-level and system-level evaluations. Individual OT devices are assessed separately for their security health status, then aggregated to determine overall system risk. This segmentation allows targeted security measures without requiring complete system redesign.
Solution Approach 2:
The patent introduces a cybersecurity assessment system as an intermediary layer between OT devices and IT ecosystems. This intermediary evaluates security risks, collects device data, and provides compensation controls, acting as a buffer that enables integration while managing vulnerability.
2Duration of action of stationary object
If legacy OT devices are retained without retrofitting, then device availability and operational continuity are maintained, but security risk and compliance vulnerability increase
Solution Approach 1:
The patent applies beforehand cushioning by implementing compensation controls and security assessments before legacy devices become critical vulnerabilities. The system continuously evaluates security health and prepares mitigation strategies in advance, cushioning against potential security incidents without requiring immediate device replacement.
3Measurement precision
If comprehensive security assessment of all OT devices is performed, then cybersecurity risk identification is improved, but management complexity and resource requirements increase
Solution Approach 1:
The patent applies local quality by tailoring security assessment depth to individual device characteristics and risk profiles. Not all devices receive identical assessment intensity; instead, resources are allocated based on device criticality, vulnerability level, and security health status, optimizing assessment precision while managing complexity.
Solution Approach 2:
The patent changes parameters by dynamically adjusting assessment frequency, depth, and scope based on device security health status. Devices with deteriorating security health receive more intensive assessment, while stable devices receive routine monitoring. This parameter adaptation maintains assessment accuracy while reducing overall management burden.
4Productivity
If OT devices are tightly integrated with IT ecosystems, then operational efficiency and functionality are improved, but cascading threat propagation and system vulnerability increase
Solution Approach 1:
The patent implements feedback mechanisms that continuously monitor device security health and system-wide risk levels. When security degradation is detected in individual devices, the system provides feedback to increase assessment intensity and activate compensation controls, preventing local vulnerabilities from propagating as cascading threats while maintaining operational efficiency.
Data Source
AI summary
A method for determining and using a security risk score for devices includes searching a network to automatically identify devices associated with potential security risks, collecting a first set of data from the devices including at least one of a device configuration, an IP address, a MAC address, or data related to software operated on the devices, collecting a second set of data from an external data source including risk data, comparing the second set of data to the first set of data to evaluate a potential security risk and determine a risk score for the devices, and using the risk score to perform an automated action including at least one of (i) providing an alert to a user identifying the potential security risk, (ii) generating a dashboard identifying the potential security risk, or (iii) initiating a corrective action responsive to the potential security risk based on the risk score.


