Cyber Defense Training Orchestrator for Objective User Assessment
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Solution Overview
Problem
Current cybersecurity training systems lack flexibility and objectivity in evaluating user responses to simulated cyberattacks, making it difficult to assess the comprehensive knowledge and skills of SOC teams effectively.
Innovation Solution
A cyber defense training system with a training orchestrator that automatically evaluates user responses by simulating scenarios on a virtual IT infrastructure, generating evaluation reports based on predefined rules, allowing for flexible and objective assessment of user interactions and mitigations without requiring a supervisor.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If automated evaluation is implemented, then objectivity and reliability of training assessment is improved, but system complexity increases
Solution Approach 1:
The system automatically evaluates user responses without supervisor intervention. The training orchestrator autonomously compares user actions against expected outcomes, generates evaluation reports, and provides feedback, enabling the system to self-assess training effectiveness objectively.
Solution Approach 2:
The system implements continuous feedback loops where user responses are automatically evaluated, results are communicated back to users, and training scenarios are dynamically adjusted. This automated feedback mechanism ensures reliable assessment while managing complexity through structured evaluation protocols.
2Adaptability or versatility
If flexible evaluation methods are used, then adaptability to different training scenarios is improved, but measurement precision deteriorates
Solution Approach 1:
The evaluation system dynamically adapts to different training scenarios, attack types, and user skill levels while maintaining precise measurement through configurable evaluation criteria. The orchestrator adjusts evaluation parameters based on scenario requirements without sacrificing measurement accuracy.
Solution Approach 2:
The system changes evaluation parameters according to different training contexts, attack scenarios, and user profiles. By dynamically adjusting evaluation thresholds, metrics, and criteria based on scenario-specific requirements, the system maintains both flexibility and measurement precision across diverse training situations.
3Loss of information
If comprehensive training assessment is implemented, then completeness of evaluation is improved, but loss of time in generating reports increases
Solution Approach 1:
The system pre-defines evaluation criteria, expected outcomes, and reporting templates before training sessions begin. By preparing evaluation frameworks in advance and caching common assessment data, the system can generate comprehensive evaluation reports quickly without sacrificing assessment completeness.
Solution Approach 2:
The evaluation process operates continuously throughout the training session, collecting and analyzing data in real-time rather than performing batch processing after completion. This continuous evaluation approach ensures comprehensive assessment while minimizing report generation time by maintaining updated metrics throughout the training.
Data Source
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AI summary
One aspect of the invention relates to a method for automatically evaluating the training of a user of a cyber defense training system, the training being carried out on the cyber defense training system, the cyber defense training system comprising an IT infrastructure simulator, a scenario module, a test module, and a human-machine interface, implemented by a training orchestrator and comprising the steps of: - Starting a scenario, including sending a request, by the training orchestrator, to the scenario module, the scenario comprising at least one action to be implemented by the IT infrastructure simulator, - Receiving information relating to the state of the simulated IT infrastructure being the result of at least one test after the user has initiated a mitigation,- Generation of at least one user training evaluation report including at least verification that the information complies with a first predefined rule, the evaluation report including at least one first metric representative of a verification result.