Event-Triggered Forensic Capture for Cybersecurity Data Management

Solution Overview

Problem

Current cybersecurity measures struggle to efficiently capture and analyze relevant data during cyber incidents, balancing the need for comprehensive data with the costs and performance impacts of extensive logging and storage.

Innovation Solution

The implementation of an event-triggered forensic capture functionality that dynamically adapts data capture by correlating basic status data with predefined trigger events and capture specifications, allowing for the selective capture and analysis of extended status data only when necessary.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Loss of information

If extensive logging and storage are implemented to capture comprehensive data during cyber incidents, then data completeness and security analysis capability are improved, but storage costs and system performance degradation increase

Engineering Contradiction:

Improvedata completenessVSAvoidstorage cost

Core Design Contradiction:

Loss of informationVSQuantity of substance

Solution Approach 1:

The system performs preliminary actions by continuously collecting and storing basic status data (process lists, network connections, registry keys) before incidents occur. When a trigger event is detected, this pre-collected data is immediately available for forensic analysis without requiring real-time capture of all system state, thereby reducing storage costs while maintaining data completeness for incident response.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system dynamically adjusts its data capture behavior based on trigger events. It transitions from passive storage of basic status data to active capture of extended status data only when trigger events are detected. This dynamic approach ensures comprehensive data availability when needed while minimizing storage costs during normal operation.

Inventive Principle:

Principle #15Dynamics

2Loss of information

If extensive logging and storage are implemented to capture comprehensive data during cyber incidents, then data completeness and security analysis capability are improved, but system performance degradation increases

Engineering Contradiction:

Improvedata completenessVSAvoidsystem performance

Core Design Contradiction:

Loss of informationVSProductivity

Solution Approach 1:

The system performs preliminary actions by continuously collecting and storing basic status data (process lists, network connections, registry keys) before incidents occur. When a trigger event is detected, this pre-collected data is immediately available for forensic analysis without requiring real-time capture of all system state, thereby reducing storage costs while maintaining data completeness for incident response.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system dynamically adjusts its data capture behavior based on trigger events. It transitions from passive storage of basic status data to active capture of extended status data only when trigger events are detected. This dynamic approach ensures comprehensive data availability when needed while minimizing storage costs during normal operation.

Inventive Principle:

Principle #15Dynamics

3Reliability

If continuous capture of all status data is implemented, then readiness for forensic analysis is improved, but data management complexity and storage requirements increase

Engineering Contradiction:

Improveforensic analysis readinessVSAvoiddata management complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The system segments data capture into two distinct categories: basic status data that is continuously collected and stored, and extended status data that is captured only when trigger events occur. This segmentation simplifies data management by separating routine monitoring from incident-specific capture, reducing overall data volume while maintaining forensic analysis readiness through the structured organization of captured data.

Inventive Principle:

Principle #1Segmentation

Data Source

PatentUS12299119B2Event-triggered forensics capture

Publication Date: 2025.05.13 MICROSOFT TECHNOLOGY LICENSING LLC

AI summary

Event-triggered forensics capture technologies balance security incident data availability against data processing and storage costs. A forensic correlation engine receives basic status data of a monitored computing system. A forensic computing system detects a trigger event in the basic status data, and starts capturing extended status data per a corresponding capture specification. Captured data is submitted to a forensic analysis tool. Different trigger events may cause different data captures. A query specifying which data to capture from a live stream or from virtual machines may operate as a capture trigger start event. Extended status data capture activity may be stopped by a change in the basic status data being received, by a timeout, or by forensic analysis that finds no vulnerability or threat based on captured data. Data transfers and storage may be restricted to comply with privacy regulations or policies.