Cybersecurity Pipeline Modeling for Dynamic Incident Valuation
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Solution Overview
Problem
Existing cybersecurity systems and architectures face challenges such as lack of integrated incident response capabilities, complex procurement processes for incident response services, and inability to dynamically adapt to changes in the security landscape.
Innovation Solution
A customized cybersecurity framework that includes a data protection system for pipeline modeling, which identifies and collects cybersecurity incident data, generates metadata to characterize cyber incidents, determines catastrophic incidents, and provides a claim data package to a protection entity computing system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a customized cybersecurity framework with pipeline modeling is implemented, then incident response capabilities are integrated and security landscape adaptability is improved, but device complexity and implementation costs increase
Solution Approach 1:
The cybersecurity framework is divided into distinct pipeline stages (data collection, metadata generation, catastrophic incident determination, claim data packaging) that can be independently configured and managed. This segmentation allows the system to adapt to different security landscapes by adjusting individual stages without redesigning the entire system, resolving the contradiction between adaptability and complexity.
Solution Approach 2:
The framework employs dynamic metadata generation that adapts to changing incident characteristics and security conditions. The system can dynamically adjust its analysis parameters, metadata schemas, and incident classification criteria based on the evolving security landscape, enabling adaptability while maintaining manageable complexity through automated adjustments.
2Measurement precision
If comprehensive cybersecurity incident data collection and metadata generation are performed, then measurement precision and incident characterization are improved, but loss of time and processing resources increase
Solution Approach 1:
The system performs preliminary data validation and metadata schema preparation before actual incident analysis. By pre-configuring metadata templates and validation rules, the system reduces processing time during incident response while maintaining comprehensive characterization precision through the pre-established analytical framework.
Solution Approach 2:
The framework uses metadata templates and standardized data structures that can be replicated across different incident types. This copying approach allows comprehensive incident characterization to be achieved through template instantiation rather than creating unique analysis structures for each incident, significantly reducing processing time while maintaining precision.
3Productivity
If catastrophic incident determination and claim data packaging are automated, then productivity and response speed are improved, but device complexity increases
Solution Approach 1:
The automated determination and packaging system uses universal metadata schemas and standardized processing workflows that handle multiple incident types through a single unified platform. This multi-functionality approach improves productivity by eliminating the need for separate systems for different incident types while managing complexity through standardization rather than proliferation of specialized components.
Data Source
AI summary
Systems, methods, and computer-readable storage media for pipeline modeling. A data protection system can include one or more processing circuits including memory and at least one processor configured to verify a state of cybersecurity of an entity based on one or more cybersecurity measures implemented by the entity at a time of a catastrophic incident and generate data comprising the state of the cybersecurity from cybersecurity incident data based on at least on at least one categorized incident and corresponding at least one claim. The at least one processor can determine at least one categorized incident corresponding with at least one claim corresponds to the catastrophic incident based on at least on the data, generate a claim data package comprising the data and the catastrophic incident, and provide the claim data package to a computing system.