Autonomous Email Report Composer for Cyber Threat Analysis

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Solution Overview

Problem

Current email security systems lack efficient mechanisms for real-time detection and reporting of cyber threats, often resulting in delayed identification and significant harm due to overwhelming volumes of data and the difficulty for human analysts to keep up with suspicious activities.

Innovation Solution

An autonomous email-report composer that cooperates with AI models and libraries to generate human-readable threat reports, using machine learning to analyze email patterns and format reports in a visually engaging manner, providing actionable insights and autonomous response actions.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Loss of information

If human analysts manually review and report cyber threats, then the reports can be customized and detailed, but the time consumption and labor costs increase significantly

Engineering Contradiction:

Improvecomprehensive threat intelligenceVSAvoidtime to generate reports

Core Design Contradiction:

Loss of informationVSLoss of time

Solution Approach 1:

The system enables autonomous self-service through AI models that automatically analyze email traffic, detect threats, and generate comprehensive threat intelligence reports without human intervention. The AI-composer autonomously composes natural language prose reports, eliminating the need for manual analyst involvement while maintaining comprehensive threat coverage.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces the mechanical system of manual human analysis with AI-based automated analysis. Machine learning models process email data and the AI-composer generates reports, substituting human cognitive work with automated intelligent systems that operate faster and without fatigue.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Measurement precision

If human analysts manually analyze cyber threats, then nuanced understanding can be achieved, but productivity and response speed decrease due to overwhelming data volumes

Engineering Contradiction:

Improvethreat detection accuracyVSAvoidthreat analysis throughput

Core Design Contradiction:

Measurement precisionVSProductivity

Solution Approach 1:

The system replaces manual human analysis with AI-based automated analysis using machine learning models. These models process overwhelming volumes of email data at machine speed while maintaining high detection accuracy through trained algorithms that identify threat patterns, achieving both precision and high productivity simultaneously.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The AI-composer acts as an intermediary between raw email data and human users. It translates complex machine-generated threat data into comprehensible natural language reports, bridging the gap between automated analysis and human understanding while maintaining both speed and accuracy.

Inventive Principle:

Principle #24Intermediary (Mediator)

3Device complexity

If traditional email security systems list only bad emails, then the system remains simple, but the loss of actionable threat intelligence increases

Engineering Contradiction:

Improvereporting system complexityVSAvoidthreat intelligence value

Core Design Contradiction:

Device complexityVSLoss of information

Solution Approach 1:

The system replaces simple listing mechanisms with AI-driven natural language generation. The AI-composer automatically synthesizes threat intelligence into coherent narrative reports that explain threats, their implications, and recommended actions, transforming basic data into actionable intelligence without requiring complex manual report writing.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

4Loss of information

If comprehensive threat analysis is performed manually, then detailed insights can be produced, but the cost in man-hours and operational expenses increases

Engineering Contradiction:

Improvedetailed threat insightsVSAvoidoperational costs

Core Design Contradiction:

Loss of informationVSLoss of energy

Solution Approach 1:

The system performs comprehensive threat analysis autonomously without requiring human analyst resources. The AI models and AI-composer work independently to produce detailed threat insights, eliminating manual labor costs while maintaining comprehensive analysis coverage.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent substitutes expensive manual analytical work with cost-effective AI-based automated analysis. Machine learning models process data and the AI-composer generates detailed reports at minimal operational cost compared to human analyst expenses, while delivering equivalent or superior insight quality.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS20240380781A1Autonomous email report generator

Publication Date: 2024.11.14 DARKTRACE HLDG LTD

AI summary

An autonomous email-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 email-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.