AI Security Report Generation Through Semantic Threat Matching
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Solution Overview
Problem
Security analysts face challenges in manually combining security data with threat intelligence, leading to a brittle process that fails to match similar but not exactly the same entities across different data sources, which can result in ineffective security incident analysis.
Innovation Solution
An artificially intelligent (AI) agent analyzes security data, automatically pulls in relevant threat intelligence, performs fuzzy and semantic matching, and generates real-time reports to enrich security investigations, without requiring parsers for different data types.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual combining of security data with threat intelligence is performed, then security analysis can be conducted, but the process is brittle and fails to match similar but not exactly the same entities
Solution Approach 1:
The patent replaces manual mechanical processes with an AI agent that performs automated entity resolution. The AI agent uses semantic understanding and fuzzy matching algorithms to identify similar entities across different data sources, replacing the brittle manual matching process with intelligent automated entity resolution that can handle variations in entity representation.
Solution Approach 2:
The patent transforms discrete exact-match parameters into continuous similarity scores. Instead of binary match/no-match decisions, the system calculates similarity metrics between entities and applies threshold-based filtering, allowing flexible matching that accommodates variations in entity representation while maintaining reliability.
2Measurement precision
If automated AI agent is used to perform fuzzy and semantic matching, then entity matching accuracy is improved, but system complexity increases
Solution Approach 1:
The patent introduces an AI agent as an intermediary layer between raw security data and threat intelligence data. This intermediary performs semantic understanding, entity extraction, and similarity matching, bridging the gap between different data formats and structures without requiring complex integration logic throughout the entire system.
Solution Approach 2:
The patent creates standardized entity representations (copies) from various source formats. The AI agent extracts essential attributes from diverse data sources and creates normalized entity objects, allowing comparison and matching without dealing with the complexity of source-specific formats directly.
3Productivity
If real-time report generation is implemented, then security incident analysis speed is improved, but computational resources required increase
Solution Approach 1:
The patent performs preliminary entity extraction, normalization, and indexing of security events and threat intelligence data before actual analysis is needed. This pre-processing creates ready-to-query structured representations, allowing rapid report generation when incidents occur without performing heavy computation in real-time.
Solution Approach 2:
The patent implements dynamic query execution that adapts computational effort to incident severity and available resources. For routine incidents, pre-computed results are used; for complex incidents, additional real-time analysis is performed. The system dynamically adjusts the depth and breadth of analysis based on contextual factors.
Data Source
AI summary
In some examples, a method of generating a security report is provided. The method includes receiving a user query and security data, and providing the user query and security data to a semantic model. The semantic model generates one or more first embeddings. The method further includes receiving, from a data model, one or more second embeddings. The data model is generated based on historical threat intelligence data. The model further includes generating an execution plan based on the one or more first embeddings and the one or more second embeddings, and returning a report that corresponds to the execution plan.