Combinatorial Test Design for Cybersecurity Attack Tree Reduction
Solution Overview
Problem
Current cybersecurity testing methods face inefficiencies in reducing the number of tests needed to ensure comprehensive coverage, particularly when dealing with large parameter lists and potential vulnerabilities in authorized services, leading to exponential growth in test cases and time consumption.
Innovation Solution
The implementation of combinatorial test design (CTD) using a combinatorics model to analyze and reduce the complexity of attack trees, generating a set of test vectors that provide complete pairwise coverage, and applying binary decision trees to identify redundant or missing tests, thereby reducing the number of tests required.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If comprehensive cybersecurity testing is performed on authorized services with large parameter lists, then test coverage is improved, but the number of test cases grows exponentially and time consumption increases
Solution Approach 1:
The patent segments the large parameter space into smaller groups using attack tree decomposition, where each node represents a subset of parameters. This allows testing to be performed on segmented portions rather than the entire parameter space at once, reducing the exponential growth of test cases while maintaining comprehensive coverage through systematic traversal of the attack tree structure.
Solution Approach 2:
The patent applies partial action by using combinatorial test design to generate a reduced set of test cases that cover the most critical parameter combinations. Instead of exhaustively testing all possible parameter combinations (excessive action), the system identifies and tests only the necessary combinations that provide adequate coverage, thereby reducing time consumption while maintaining reliability.
2Reliability
If all possible parameter combinations are tested to ensure complete coverage, then test completeness is improved, but device complexity and test case management become unmanageable
Solution Approach 1:
The attack tree structure segments the complex testing task into hierarchical nodes, where each node manages a specific subset of parameters and test cases. This segmentation reduces test case management complexity by organizing tests in a structured hierarchy rather than as a flat, unmanageable set of all possible combinations.
Solution Approach 2:
The patent introduces combinatorial test design algorithms as intermediaries between the authorized service and the test execution. These algorithms automatically generate optimized test cases from the attack tree structure, mediating the complexity of parameter combinations and producing a manageable set of test cases that maintain completeness without requiring manual management of all possible combinations.
3Device complexity
If traditional testing methods are used on authorized services, then implementation simplicity is maintained, but vulnerability detection capability is insufficient
Solution Approach 1:
The patent performs preliminary action by constructing an attack tree model before actual testing begins. This model pre-identifies potential attack vectors, parameter combinations, and vulnerability paths based on the structure of the authorized service. By preparing this structured model in advance, the system enhances vulnerability detection capability without complicating the actual test execution, as the complex analysis work is done during the model construction phase.
Data Source
AI summary
A method includes receiving test objective data indicates an objective to be achieved during a cybersecurity test of a target system. An attack tree is generated by processing the test objective data into attack tree data including a plurality of data parameter sets and links between data parameter sets. Complexity of the attack tree is analyzed based on the test objective data using a combinatorics model. The attack tree is reduced to achieve the objective of the cybersecurity test based on the analyzed complexity of the attack tree.