Machine Learning Security Analysis Effort Estimation
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Solution Overview
Problem
Estimating the effort and cost of analyzing software systems for security vulnerabilities is challenging due to their complexity and interdependencies, leading to inaccurate and subjective assessments that result in suboptimal resource utilization and financial performance for security intelligence platform providers.
Innovation Solution
A method and system utilizing machine learning-based analytics with dynamic and static analysis tools to generate quantitative estimates of security analysis effort and cost, employing an intermediate code representation that allows analysis without requiring source code disclosure, and using modified analysis tools to collect data from various sources within the software system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If human experts perform security analysis estimation, then subjective judgment and experience are applied, but accuracy and repeatability deteriorate due to system complexity
Solution Approach 1:
The patent replaces human expert judgment (mechanical/cognitive system) with automated machine learning algorithms and statistical analysis tools. The system uses decomposition of software features, complexity categorization, code structure analysis, and static/runtime dependency tracking to objectively measure security analysis effort, eliminating subjective human estimation while maintaining accuracy despite system complexity.
2Productivity
If subjective estimation methods are used, then quick assessments are obtained, but resource utilization and financial performance deteriorate
Solution Approach 1:
The patent performs preliminary automated analysis of software system attributes, complexity metrics, and interdependencies before security assessment begins. By pre-calculating these parameters using machine learning models trained on historical data, the system establishes accurate baseline estimates that guide resource allocation and pricing decisions, eliminating the need for reactive subjective adjustments.
3Measurement precision
If detailed analysis of software attributes and interdependencies is performed, then estimation accuracy improves, but analysis time and computational resources increase
Solution Approach 1:
The patent segments the security analysis estimation process into distinct measurable components: software feature decomposition, complexity categorization, code structure analysis, and static/runtime dependency identification. Each segment is analyzed independently using specialized algorithms, allowing parallel processing and reducing overall analysis time while maintaining comprehensive precision through aggregation of segment results.
Data Source
AI summary
A method, system and computer-usable medium for generating a security analysis effort, cost and process scope estimates, comprising: analyzing a software system; identifying a complexity level of a security analysis, the complexity level of the security analysis comprising identification of an effort level for the security analysis; and, generating the security analysis effort estimate, the security analysis effort estimate comprising an estimate of an effort expenditure to perform a security analysis on the software system at the identified complexity level.