Code Vulnerability Evaluation With Hybrid Parallel Analysis
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Solution Overview
Problem
Existing code vulnerability detection methods have low code coverage and fail to effectively identify malicious code, leading to security breaches, operational damage, and reputational harm, especially in complex and decentralized systems.
Innovation Solution
A hybrid approach combining static and dynamic vulnerability validation with real-time parallel technique execution using a quantum graph categorizer and quantum polymorphism execution channels to enhance code coverage and reduce false positives.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If static and dynamic vulnerability detection methods are used, then vulnerability detection capability is provided, but code coverage remains low and false positives occur
Solution Approach 1:
The patent combines multiple vulnerability detection techniques (static analysis, dynamic analysis, symbolic execution, fuzzing) into a unified hybrid framework that operates simultaneously, allowing the system to leverage the strengths of each method while compensating for their individual weaknesses to achieve comprehensive code coverage
Solution Approach 2:
The vulnerability evaluation system is designed to perform multiple functions including static code analysis, dynamic runtime monitoring, symbolic execution, and fuzzing tests within a single unified platform, enabling it to detect various types of vulnerabilities across different code paths and execution scenarios
2Adaptability or versatility
If code complexity increases and systems become decentralized, then system functionality is enhanced, but vulnerability detection becomes more difficult
Solution Approach 1:
The patent segments the vulnerability detection process into distinct modular components including static analysis modules, dynamic analysis modules, symbolic execution engines, and fuzzing test generators, allowing each component to independently handle specific aspects of complex decentralized systems while working together through standardized interfaces
Solution Approach 2:
The system adds temporal dimension to vulnerability detection by performing both static pre-execution analysis and dynamic runtime monitoring, enabling detection of vulnerabilities that manifest only during specific execution states or environmental conditions in decentralized systems
3Reliability
If traditional vulnerability detection methods are used, then basic security checks are performed, but false positives reduce productivity
Solution Approach 1:
The patent implements dynamic configuration of detection depth and scope based on risk assessment, allowing the system to automatically adjust the intensity of analysis for different code segments, focusing computational resources on high-risk areas while performing lighter checks on low-risk code to maintain productivity
Solution Approach 2:
The system replaces traditional manual code review and basic automated scanners with advanced techniques including symbolic execution engines that mathematically explore code paths, machine learning models that predict vulnerability locations, and parallel processing architectures that evaluate multiple code paths simultaneously
Data Source
AI summary
A computing platform provides code vulnerability detection and evaluation. The computing platform may use a quantum graph categorizer along with quantum polymorphism execution channels to reduce false positives and provide optimized real-time vulnerability evaluation of code and code segments. The computing platform may use a hybrid approach comprising a mix of static and dynamic vulnerability validation and real-time parallel technique execution.