NLP Risk Management Workflow for Cyber Threat and Regulatory Analysis
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Solution Overview
Problem
Organizations face challenges in managing cyber security and regulatory risks due to the overwhelming volume and complexity of security advisories, difficulty in understanding and acting on regulatory requirements, and the need for user-friendly interfaces that can automate and streamline these processes.
Innovation Solution
An automated system using natural language processing (NLP) to interpret and adapt to changes in the threat landscape, retrieving and analyzing internal and external information, generating actionable insights, and integrating with workflow management solutions for timely responses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual processes are used to review and assess security advisories, then detailed analysis can be performed, but the process is labor-intensive and results in delays
Solution Approach 1:
An AI assistant acts as an intermediary between security advisories and human analysts. The AI automatically retrieves, summarizes, and analyzes security advisories, vulnerability data, and internal asset information, then presents synthesized findings to human users. This mediator handles the time-consuming manual review work while preserving analytical depth through structured questioning and evidence presentation.
Solution Approach 2:
The patent replaces manual mechanical review processes with automated AI-based analysis. The AI system automatically performs information retrieval, cross-referencing, vulnerability assessment, and risk calculation that previously required human analysts to manually examine documents and data, thereby eliminating delays while maintaining analytical rigor through systematic automated procedures.
2Reliability
If comprehensive security assessment is performed manually, then thorough risk analysis is achieved, but resource consumption increases
Solution Approach 1:
The AI assistant performs self-service by automatically retrieving its own data from multiple sources including vulnerability databases, security advisories, and internal asset inventories. It autonomously executes assessment workflows, calculates risk scores, and generates reports without requiring human resources for data collection and initial analysis, thereby maintaining comprehensive assessment while reducing resource consumption.
Solution Approach 2:
The AI assistant serves multiple functions within a single system: it retrieves security information, analyzes vulnerabilities, assesses internal assets, calculates risk scores, generates reports, and provides recommendations. This multi-functional approach consolidates what previously required multiple separate tools and human experts into one automated system, achieving thorough assessment with optimized resource usage.
3Measurement precision
If sophisticated cyber security tools are provided, then advanced analysis capabilities are available, but accessibility to non-technical users is reduced
Solution Approach 1:
The AI assistant serves as an intelligent intermediary that translates complex security analysis capabilities into user-friendly interactions. It handles sophisticated data processing, vulnerability assessment, and risk calculation in the background while presenting simplified questions, clear summaries, and actionable recommendations to non-technical users through natural language communication.
Solution Approach 2:
The system dynamically adjusts its interaction parameters based on user expertise level. For non-technical users, it presents high-level summaries and simplified questions. For technical users, it provides detailed data and advanced options. This parameter adaptation maintains advanced analysis capability while optimizing accessibility for different user groups.
Data Source
AI summary
This invention provides an automated system for managing cyber security and regulatory risks. It retrieves internal documents from platforms like Google Drive and OneDrive, and external documents from trusted sources via RSS feeds. Documents are stored in centralized locations with lifecycle management, enriched with contextual labels, and used to augment and fine-tune a language model. Real-time threat intelligence and news feeds are integrated, enabling the system to analyze security advisories and regulatory requirements, generating actionable insights and recommendations. The system integrates with workflow management tools like Jira for tracking work items and provides a natural language interface for ad-hoc user interaction. This comprehensive solution enhances operational efficiency, reduces manual efforts, and ensures timely responses to emerging threats and regulatory changes.