Structured Cybersecurity Issue Aggregation for Threat Data Freshness
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Solution Overview
Problem
The rapid increase in cybersecurity threat publications overwhelms researchers and security experts with a continuously growing flood of unstructured information, making it difficult to efficiently consume and update structured information about cybersecurity issues.
Innovation Solution
A system leveraging artificial intelligence to structure and update cybersecurity information by periodically crawling websites, prompting a foundation model to generate structured representations of cybersecurity issues, and maintaining a staging database for consolidated consumption by various consumers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If researchers manually review and structure cybersecurity threat publications, then information accuracy and contextual understanding are improved, but the time and resources required increase significantly due to the overwhelming volume of publications
Solution Approach 1:
The patent introduces an intermediary system comprising a foundation model and a structured representation generator that mediates between unstructured threat publications and structured databases. This intermediary automatically processes publications, extracts relevant information, and generates structured representations, thereby reducing manual review time while maintaining information accuracy through multiple processing stages including redundancy checks and consistency validations.
2Speed
If the system processes and structures all cybersecurity publications in real-time, then information freshness is improved, but computational resources and processing complexity increase
Solution Approach 1:
The system performs preliminary actions by pre-processing publications as they are received, immediately generating structured representations and storing them in databases. This preliminary processing ensures information freshness without requiring complex real-time analysis of all publications simultaneously. The system prepares data in advance for future queries, reducing the complexity of on-demand processing.
Solution Approach 2:
The patent segments the processing system into distinct modular components: a foundation model for understanding publications, a structured representation generator for formatting data, multiple specialized databases for different types of information, and various consumer systems. This segmentation allows each component to process specific tasks independently, reducing overall processing complexity while maintaining information freshness through parallel operation of these segmented modules.
3Adaptability or versatility
If the system maintains multiple detailed databases for different cybersecurity information types, then information accessibility and utility for different consumers are improved, but data management complexity and storage requirements increase
Solution Approach 1:
The patent implements a universal structured representation format that can serve multiple database types and consumer needs. The same structured representation generated from a publication can be stored in and queried by multiple different databases (e.g., vulnerability databases, product databases, organization databases) without requiring separate processing pipelines. This multi-functionality improves information accessibility for diverse consumers while reducing data management complexity by eliminating redundant processing for each database type.
Data Source
AI summary
A cybersecurity intelligence system maintains a current view of published cybersecurity issues by periodically crawling websites that publish information about cybersecurity issues, including first impression issues and updates to issues. The system aggregates unstructured descriptions for a same issue. For each published issue detected from crawling, the system prompts a foundation model to generate a structured representation that can be consumed. The structured representation includes key-value pairs corresponding to issue type and affected vendor product. Distilling and consolidating the issue descriptions into these informational components intelligently surfaces salient features of the information for addressing issues. After some quality assurance of the structured representations from the model, the structured representations are published for access by consumers.