Virtual Computer Model Fuzz Testing for Internal Signal Detection
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Solution Overview
Problem
Traditional fuzz testing methods struggle to effectively detect internal state changes and security events in software and hardware systems, lacking real-time analysis capabilities and quantitative metrics for test coverage.
Innovation Solution
A fuzz testing system utilizing a Virtual Computer Model (VCM) that enables real-time monitoring of internal and external signals, incorporating automatic assertion generation and detection functions to enhance security verification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional fuzz testing methods are used to inject random inputs into systems, then security vulnerability detection is performed, but internal state changes and security events cannot be effectively detected
Solution Approach 1:
The patent introduces a Virtual Computer Model as an intermediary between the fuzz tester and the target system. This virtual model intercepts and monitors internal signals and state changes that would otherwise be inaccessible, enabling the detection of internal security events while maintaining the fuzz testing process.
Solution Approach 2:
The patent replaces direct physical/system-level monitoring with a virtualized monitoring approach. By substituting the need for invasive hardware or system-level access with a software-based Virtual Computer Model, internal states become observable without disrupting the target system's normal operation.
2Productivity
If traditional fuzz testing is conducted on physical systems, then testing can be performed, but real-time monitoring of internal signals is not achievable
Solution Approach 1:
The patent creates a virtual copy (Virtual Computer Model) of the target system's computational behavior. This copy replicates the system's internal state transitions and signal flows, allowing observers to monitor internal signals in real-time without affecting the original system's performance or losing any information.
3Reliability
If conventional fuzz testing methods are used, then testing can be performed, but quantitative metrics for test coverage are lacking
Solution Approach 1:
The patent implements a feedback mechanism where the Virtual Computer Model continuously monitors internal state changes and provides quantitative data about test coverage. This feedback loop enables the generation of precise metrics that measure how thoroughly different parts of the system have been tested, allowing for objective evaluation of testing completeness.
Data Source
AI summary
The present invention provides a fuzz testing system and method based on a virtual computer model. Traditional fuzz testing approaches primarily modify external inputs to detect security vulnerabilities, making it difficult to monitor internal state changes in real-time. This invention constructs a test environment using a virtual computer model and incorporates automatic assertion generation and detection functions, enabling precise analysis of both internal and external signals of the system. After executing fuzz testing, assertion data is analyzed to assess test coverage and identify untested code regions, allowing for an optimized testing strategy. This improves the detection rate of security vulnerabilities, enhances test automation and reliability, and can be applied in various fields such as networks, automotive ECUs, IoT, finance, aerospace, and semiconductors.