Distributed Cybersecurity Analysis for Scalable Vulnerability Scoring
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Solution Overview
Problem
Large organizational networks face challenges in comprehensively surveying and scoring their vulnerability to cyberattacks due to complexity and scale, making it difficult to manage cybersecurity effectively.
Innovation Solution
A system utilizing distributed, cloud-based computing services with an in-memory associative array, proxy server, and data packet modifier to analyze enterprise IT networks, revealing threat actors and blocking them, while providing scalable computing power and storage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional centralized cybersecurity analysis methods are used, then analysis capability is limited, but system complexity and management difficulty increase significantly for large networks
Solution Approach 1:
The system divides the cybersecurity analysis function into distributed scanning nodes deployed across multiple locations. Each node independently performs vulnerability scanning and data collection on specific network segments, eliminating the need for a single complex centralized system while maintaining comprehensive analysis capability across large organizational networks.
2Reliability
If comprehensive vulnerability scanning is performed on large networks, then security coverage is improved, but the time and resources required become unmanageable
Solution Approach 1:
The system performs preliminary actions by deploying distributed scanning nodes in advance across the network infrastructure. These nodes continuously monitor and collect vulnerability data before actual security assessments are needed, enabling comprehensive security coverage to be achieved without requiring extensive scanning time when security evaluations are required.
Solution Approach 2:
The distributed scanning nodes operate continuously in the background, constantly gathering vulnerability intelligence and updating security data. This continuous operation ensures comprehensive security coverage is maintained over time without requiring periodic lengthy scanning campaigns, thus eliminating unmanageable time requirements.
3Productivity
If more scanning nodes are deployed to increase analysis capacity, then productivity improves, but system complexity and management overhead increase
Solution Approach 1:
Each scanning node in the distributed system is designed as a universal, multi-functional unit capable of performing vulnerability scanning, data collection, local analysis, and communication with other nodes. This standardization allows analysis capacity to be scaled by simply adding identical nodes without increasing management complexity, as all nodes operate with the same functionality and protocols.
Data Source
AI summary
Cybersecurity reconnaissance, analysis, and scoring uses distributed, cloud or edge-based pools of computing services to provide sufficient scalability for analysis of IT/OT networks using only publicly available characterizations. An in-memory associative array manages a queue of configuration and vulnerability search tasks through at least one public-facing proxy network which uses configurable search nodes to approach the target network with search tools in a desired manner to control certain aspects of the search in order to obtain the desired results, especially when target network behavior adjusts based on counterparty characteristics. A data packet modifier reveals IP addresses of threat actors behind port scans and subsequently block the threat actors.