Geographic Proximity Infrastructure Identification
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Solution Overview
Problem
Critical infrastructures are vulnerable to cyberattacks due to exposed Internet Protocol (IP) addresses, which can lead to catastrophic consequences such as denial of service or unauthorized intrusion.
Innovation Solution
The system identifies similar geographically proximate infrastructures by determining the geographic location of a compromised infrastructure from its IP address and comparing it with other infrastructures within a predetermined distance, using network fingerprints and satellite images to verify similarity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If geographic location determination from IP address is performed for all infrastructures, then the ability to identify geographically proximate infrastructures is improved, but the computational complexity and time required increases
Solution Approach 1:
The system pre-determines and stores geographic locations for all infrastructures in a database before any security analysis is performed. When a compromise is detected, the system simply queries this pre-prepared database for infrastructures within a predetermined distance, avoiding real-time geographic calculations and significantly reducing response time.
Solution Approach 2:
Instead of analyzing all infrastructures globally, the system limits its analysis to only those infrastructures that fall within a predetermined geographic distance from the compromised infrastructure. This partial action approach reduces the dataset size and computational requirements while still capturing all potentially affected infrastructures.
2Measurement precision
If network fingerprints and satellite images are compared to identify similar infrastructures, then the accuracy of identifying infrastructures with same industrial purpose is improved, but the device complexity and computational resources required increase
Solution Approach 1:
The system creates simplified digital representations (network fingerprints) of infrastructure characteristics that can be efficiently stored and compared. Instead of analyzing complete network configurations, the system uses condensed fingerprint profiles that capture essential industrial purpose indicators, reducing computational complexity while maintaining identification accuracy.
Solution Approach 2:
The system divides the infrastructure identification process into separate analytical components: network fingerprint analysis and satellite image analysis. Each component can be independently optimized and processed, allowing the system to handle complex analysis tasks in manageable segments rather than as a monolithic complex process.
3Speed
If the system monitors and compares all infrastructures in real-time, then the detection speed of extended cyberattacks is improved, but the loss of energy and computational resources increases
Solution Approach 1:
The system pre-establishes geographic proximity relationships and stores infrastructure data in ready-to-query formats before attacks occur. When a compromise is detected, the system performs rapid pattern matching against pre-processed data rather than conducting real-time analysis of all infrastructures, dramatically reducing energy consumption during detection events.
Solution Approach 2:
Instead of continuous real-time monitoring of all infrastructures, the system performs periodic updates to infrastructure databases and triggers comprehensive analysis only when specific events occur (such as a detected compromise). This event-driven periodic action reduces continuous computational energy consumption while maintaining rapid detection capability when needed.
Data Source
AI summary
Similar geographically proximate infrastructures are identified from a received compromised Internet protocol (IP) address of a compromised infrastructure. The geographic location of the compromised infrastructure is determined from the compromised IP address. The geographic locations of other infrastructures are determined from their respective exposed IP addresses. Geographically proximate infrastructures are identified from among the other infrastructures, with the geographically proximate infrastructures having geographic locations that are within a predetermined distance of the geographic location of the compromised infrastructure. Similar geographically proximate infrastructures are identified from among the geographically proximate infrastructures, with the similar geographically proximate infrastructures having a same industrial purpose as the compromised infrastructure.