Technical Unit Security Checks Through Attack Model Inference
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Solution Overview
Problem
The complexity of modern technical devices with numerous interconnected components poses a high risk for cyber attacks, and existing security checks struggle with managing the combinatorial diversity of test cases, requiring extensive manual processing and lacking comprehensive knowledge of internal configurations.
Innovation Solution
A method using a test computer system to establish a connection with the device, develop a plausible model variant through challenge actions, analyze behavior, and infer features to reduce the number of test cases, enabling automated security checks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If comprehensive security checks are performed on all possible configuration combinations, then security coverage is improved, but the time and complexity of testing increases exponentially
Solution Approach 1:
The patent applies preliminary action by inferring configuration features before comprehensive testing. The system performs challenge actions and analyzes characteristic behaviors to deduce configuration features, thereby narrowing down the test space in advance. This allows the security check to focus on the most relevant configuration combinations rather than exhaustively testing all possibilities, significantly reducing testing time while maintaining security coverage.
Solution Approach 2:
The patent implements feedback mechanisms where the results of challenge actions and behavior analysis are used to iteratively refine the configuration model. The system continuously updates its understanding of the technical unit's configuration based on observed behaviors, which guides subsequent testing efforts. This feedback loop enables the system to adaptively focus on promising configuration paths and avoid unnecessary testing of unlikely combinations.
2Ease of operation
If manual processing methods are used for security checks, then flexibility in analysis is improved, but productivity and automation level decrease
Solution Approach 1:
The patent applies self-service by enabling the system to automatically perform configuration inference and security analysis without requiring continuous manual intervention. The automated system conducts challenge actions, analyzes characteristic behaviors, infers configuration features, and generates security assessments autonomously. This self-service capability significantly increases productivity while maintaining the flexibility of comprehensive analysis through automated reasoning algorithms.
Solution Approach 2:
The patent replaces manual mechanical analysis processes with automated computational systems. Instead of relying on human analysts to manually examine each configuration possibility, the system uses automated algorithms to perform challenge actions, analyze behaviors, and infer configurations. This substitution of mechanical human analysis with automated computational processes dramatically increases testing throughput while preserving analytical flexibility through sophisticated software-based reasoning.
3Productivity
If the number of test cases is reduced for automated processing, then productivity is improved, but measurement precision of security vulnerabilities may decrease
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting the level of detail and scope of configuration features based on the automation requirements. The system selectively infers and tests specific configuration parameters that are most relevant to security risks, rather than exhaustively testing all possible parameters. This parameter-based approach allows the system to maintain high productivity through automated processing while preserving measurement precision by focusing computational resources on the most critical security-relevant configuration aspects.
Data Source
AI summary
Various embodiments of the present disclosure are directed to methods for checking the security of a technical unit, wherein at least one first plausible model variant is determined. In one example embodiment, the method includes the following steps carried out on a test computer system: assigning known vulnerabilities to components of the model variants; defining an attack aim; creating at least one attack model, based on the attack aim, for each model variant; weighting the nodes of the attack model with respect to at least one evaluation variable; determining an evaluation of at least one test vector of the attack model with respect to the evaluation variable; determining a security value as the pessimal value of all evaluations; and issuing a security confirmation if the security value corresponds to a security criterion.