Grey-Box Fuzzy Testing Framework for Software Vulnerability Assessment
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The vehicle software industry faces challenges in security testing due to system complexity, size, outsourcing, input and output fluctuations, and test-bed complexity, with existing methods like black-box fuzzy testing being unreliable and white-box testing being time-consuming, making it difficult to ensure comprehensive security validation for Connected Autonomous Vehicles (CAVs).
Innovation Solution
A grey-box fuzzy testing framework that prioritizes vulnerable components using security vulnerability metrics, assigning weights to functions based on vulnerability scores, and employing a mutation engine to perform small data type mutations, allowing for efficient and focused security testing without increasing testing complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If black-box fuzzy testing is used, then testing complexity is reduced, but reliability of security validation deteriorates
Solution Approach 1:
The patent introduces grey-box testing as an intermediary approach between black-box and white-box testing. It uses security vulnerability metrics as a mediator to guide the testing process, combining the simplicity of black-box testing with the reliability of targeted analysis by prioritizing vulnerable components without requiring full system transparency
Solution Approach 2:
The patent changes the parameter of testing approach from purely black-box to grey-box by incorporating security vulnerability metrics. This parameter change allows the system to maintain low complexity while improving reliability by focusing testing efforts on components with higher vulnerability scores
2Reliability
If white-box testing is used, then reliability of security validation is improved, but testing time increases
Solution Approach 1:
The patent extracts and focuses testing efforts on the most vulnerable components by using security vulnerability metrics to identify and prioritize critical areas. This extraction principle allows the system to achieve high reliability by concentrating testing time on the most important targets rather than uniformly testing all components
Solution Approach 2:
The patent segments the testing process into priority levels based on vulnerability scores. By dividing the software system into segments of varying vulnerability levels, the system can allocate testing time efficiently, spending more time on high-vulnerability components and less on low-vulnerability ones, thus improving overall reliability without excessive time investment
3Reliability
If comprehensive security testing is performed on all callable units, then reliability is improved, but productivity decreases
Solution Approach 1:
The patent changes the parameter of test distribution by using security vulnerability metrics to dynamically allocate testing resources. Instead of uniform testing, the system adjusts the number of tests per callable unit based on its vulnerability score, achieving both comprehensive security validation and improved productivity through intelligent resource allocation
4Productivity
If security vulnerability metrics are used to prioritize testing, then testing efficiency is improved, but device complexity increases
Solution Approach 1:
The patent introduces security vulnerability metrics as an intermediary layer that bridges the gap between simple testing and complex analysis. This mediator enables efficient prioritization without requiring the full complexity of white-box testing, as the metrics provide guidance without demanding complete system transparency or intricate analysis mechanisms
Data Source
AI summary
The disclosure is directed to a method, system and a computer readable medium of fuzzy testing a software system, using a grey-box fuzzy testing framework that optimizes the vulnerability exposure process while addressing security testing challenges. The grey-box fuzzy testing framework, unlike white-box testing, provides a focused and efficient assessment of a software system without analyzing each line of code. The disclosed embodiments provide a robust security mechanism that accumulates information about the system without increasing testing complexity, enabling fast and efficient security testing. The disclosed embodiments use security vulnerability metrics designed to identify vulnerable components in the software systems and ensures thorough testing of these components by assigning weights. A mutation engine may perform small data type mutations at the input's high-level design. The grey-box approach addresses three testing challenges: the system's complexity and size by avoiding intensive code analysis, outsourcing by limiting the knowledge about the system, and input and output fluctuation by creating a massive number of inputs.