Cyber Range Generation With Conversational Validation
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Solution Overview
Problem
The creation of cyber ranges is a time-consuming, expensive, and tedious process that often results in non-functional or incorrectly constructed ranges, requiring detailed user input and expertise, and is difficult to modify or update.
Innovation Solution
A cyber range development system that uses a generative model to transform user inputs into a graphical representation, validate the range, and generate specifications for deployment, leveraging a large language model for conversational interaction and automated vulnerability assessment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional manual methods are used to create cyber ranges, then customization for specific training scenarios is possible, but the process is time-consuming and expensive
Solution Approach 1:
The system creates templates from previously generated cyber ranges that can be reused and modified for new training scenarios. Instead of manually creating each range from scratch, the system copies and adapts existing range configurations, significantly reducing creation time while maintaining customization capability through template-based modification.
Solution Approach 2:
The system employs automated generation algorithms that self-configure cyber ranges based on high-level scenario descriptions. The system serves itself by automatically translating training scenario requirements into complete range configurations without requiring manual intervention for each component, thus reducing both time and expertise requirements.
2Manufacturing precision
If detailed specifications are required for cyber range creation, then functional accuracy can be improved, but user expertise requirements increase and the process becomes more complex
Solution Approach 1:
The system introduces an intermediary layer of automated configuration tools that translate high-level training scenario descriptions into detailed technical specifications. This intermediary automatically handles the complex mapping between user intent and implementation details, maintaining functional accuracy while shielding users from complexity.
Solution Approach 2:
The system replaces manual configuration processes with automated generation algorithms and AI-driven configuration tools. These automated systems handle the complex specification generation, validation, and optimization tasks that previously required expert manual intervention, thereby maintaining precision while reducing process complexity.
3Ease of manufacture
If manual construction methods are used, then initial creation is possible, but modifications and updates become difficult and time-consuming
Solution Approach 1:
The system implements dynamic configuration management where cyber ranges are defined through parameterized templates and configuration files rather than static manual constructions. This allows rapid modification by simply updating configuration parameters or swapping template components, making the system adaptable to changing training requirements without complex reconfiguration.
4Reliability
If expert knowledge is required for cyber range creation, then quality can be maintained, but accessibility to non-experts is reduced
Solution Approach 1:
The system introduces automated validation and quality assurance intermediaries that check generated configurations against best practices and functional requirements. These intermediary systems enforce quality standards automatically, allowing non-experts to create reliable cyber ranges without requiring deep domain knowledge, while still maintaining quality through automated verification.
Data Source
AI summary
A cyber range development system and method is configured to receive conversational inputs from a user regarding a desired cyber range, generate a graphical representation of the desired cyber range from the inputs, validate the created range, and export specifications for the created range for use by a range orchestrator in generating the actual range.