Autonomous Threat Report Composition for Faster Cyber Analysis
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Solution Overview
Problem
The manual process of drafting security and threat intelligence reports for cyber security professionals is time-consuming and inefficient, often leading to delayed detection of cyber threats due to the overwhelming volume and real-time nature of security incidents.
Innovation Solution
An AI cyber security analyst system that collaborates with an autonomous report composer to analyze and generate human-readable reports on cyber threats, using machine learning and pre-written templates with fillable blanks to present findings in a format tailored to different audiences, including business executives and cyber professionals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual drafting of security reports is used, then detailed analysis can be performed, but time consumption increases significantly
Solution Approach 1:
The patent introduces an autonomous report composer as an intermediary between the AI cyber security analyst and human readers. This composer automatically generates human-readable reports from structured data, eliminating the need for manual drafting while preserving analysis depth. The system uses templates with fillable blanks that are populated with threat intelligence data, achieving both detailed analysis and rapid report generation.
Solution Approach 2:
The system creates standardized report templates that can be repeatedly instantiated with different threat data. These templates contain pre-written sections that are copied and adapted for each report, maintaining consistency and quality while dramatically reducing generation time. The templates include standard threat intelligence sections that are automatically populated with current data.
2Loss of information
If comprehensive threat intelligence reports are generated manually, then complete coverage of threat landscapes is achieved, but productivity decreases
Solution Approach 1:
The report composition process is segmented into distinct modules: threat data collection, analysis, template selection, and report generation. Each segment handles specific aspects of threat intelligence, allowing parallel processing and automation. The segmented approach ensures comprehensive coverage while improving throughput by eliminating sequential manual operations.
Solution Approach 2:
The autonomous report composer performs self-service by automatically selecting appropriate templates, populating them with relevant threat data, and generating final reports without human intervention. The system autonomously determines which threat intelligence sections are relevant and fills them with current data, maintaining completeness while maximizing productivity.
3Speed
If real-time threat analysis is performed, then early detection of cyber threats is achieved, but the volume of data to be processed increases
Solution Approach 1:
The system performs preliminary actions by pre-configuring report templates with standard sections and pre-writing boilerplate content. This preparation work is done in advance, so when real-time threat data arrives, it can be quickly integrated into the predefined structure without requiring extensive processing or formatting decisions during the critical detection phase.
Data Source
AI summary
An autonomous report composer composes a type of report on cyber threats that is composed in a human-readable format with natural language prose, terminology, and level of detail on the cyber threats aimed at a target audience. The autonomous report composer cooperates with libraries with prewritten text templates with i) standard pre-written sentences written in the natural language prose and ii) prewritten text templates with fillable blanks that are populated with data for the cyber threats specific for a current report being composed, where a template for the type of report contains two or more sections in that template. Each section having different standard pre-written sentences written in the natural language prose.