Trigger-Based Scanning of Cyber-Physical Assets
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Solution Overview
Problem
Current methods for tracking and updating asset information in networks are manual, costly, and prone to human error, especially when assets undergo changes such as addition, removal, or reconfiguration, necessitating a more efficient and automated system for scanning cyber-physical assets.
Innovation Solution
A system utilizing a directed computational graph for ongoing trigger-based scanning of network resources, which includes a computing device that determines a geographical location, generates encrypted status updates, and transmits them to another device for scanning and updating a cyber-physical graph, using time-series metadata and scan rules to detect and report network vulnerabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual scanning and updating of asset information is performed, then accuracy of asset tracking can be maintained, but labor costs and time consumption increase significantly
Solution Approach 1:
The system enables assets to self-report their status and location through automated sensors and identifiers. RFID tags, GPS receivers, and other sensing devices on assets automatically transmit data to the centralized system, eliminating the need for manual scanning and updating while maintaining high accuracy in asset tracking.
Solution Approach 2:
The patent replaces manual mechanical scanning processes with automated electronic detection systems. RFID readers, barcode scanners, and sensor networks automatically detect and track assets, substituting human labor with electronic systems that provide continuous, real-time monitoring without time loss.
2Reliability
If manual updating of inventory databases is performed, then data accuracy can be maintained, but human errors and operational costs increase
Solution Approach 1:
Assets automatically update the inventory database through self-reporting mechanisms. Sensors detect asset status changes (location, condition, movement) and autonomously transmit this information to update the database, eliminating manual data entry and associated human errors while reducing operational costs.
Solution Approach 2:
The system implements continuous feedback loops where sensors monitor asset status and automatically feed this information back to the inventory database. This real-time feedback mechanism ensures data accuracy is maintained automatically without manual intervention, reducing both errors and operational costs.
3Loss of information
If continuous monitoring of all assets is performed, then real-time network awareness is achieved, but system complexity and resource consumption increase
Solution Approach 1:
The system implements differential monitoring that focuses computational resources on assets or network segments where changes are detected. Instead of uniformly monitoring all assets continuously, the system applies monitoring intensity proportional to the likelihood or importance of changes, reducing overall system complexity while maintaining real-time awareness where needed.
Solution Approach 2:
The system employs periodic scanning intervals that adapt based on asset criticality and change frequency. High-priority assets are monitored more frequently, while lower-priority assets use longer intervals between scans. This periodic action with variable frequency achieves real-time awareness for critical assets while reducing system complexity and resource consumption overall.
Data Source
AI summary
A system and method for trigger-based scanning of cyber-physical assets, including a distributed operating system, parameter evaluation engine, at least one cyber-physical asset, at least one crypt-ledger, a network, and a scanner that detects trigger conditions and events and performs scans of cyber-physical assets based on the trigger and any relevant stored scan rules before storing scan results as time-series data.