Vulnerability Prioritization Server Using Domain and User Knowledge
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Solution Overview
Problem
Current tools for identifying and prioritizing vulnerabilities in software code with external components are inefficient and require extensive training, lacking user-specific preferences and domain-specific knowledge integration.
Innovation Solution
A method and server configuration that utilize domain-specific knowledge (DSK) and user-specific knowledge (USK) databases to determine utility estimations for vulnerabilities, providing a prioritized list that accounts for user preferences and non-user defined features.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If external software components are included to reduce development time and error risk, then productivity and reliability are improved, but the complexity of vulnerability management increases and control over vulnerabilities decreases
Solution Approach 1:
The patent introduces an intermediary system that acts as a mediator between the user and the vulnerability data. This system automatically collects, stores, and processes vulnerability information from multiple sources, comparing it against the user's software code and preferences. The intermediary handles the complexity of vulnerability management by filtering and prioritizing vulnerabilities based on user-specific criteria, thus resolving the contradiction between improved productivity and increased management complexity.
Solution Approach 2:
The system enables self-service by automatically gathering vulnerability data, analyzing it against the user's codebase, and generating prioritized vulnerability reports without requiring manual intervention. The system serves itself by maintaining databases of vulnerability information and automatically updating and comparing this data, reducing the burden on users while maintaining high productivity and managing complexity internally.
2Measurement precision
If comprehensive vulnerability assessment systems are implemented to identify all vulnerabilities, then measurement precision is improved, but the time required for assessment increases
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting the assessment criteria and data collection parameters based on user preferences and specific needs. The system changes parameters such as vulnerability severity thresholds, data sources to monitor, and comparison criteria to optimize the balance between comprehensive identification and time efficiency. This allows the system to maintain high measurement precision while adapting the assessment process to minimize time loss.
Solution Approach 2:
The system implements partial action by focusing assessment efforts on the most critical vulnerabilities and areas of highest risk, rather than attempting to assess every possible vulnerability with equal depth. By using user preferences and historical data to identify priority areas, the system achieves sufficient measurement precision for decision-making without the time cost of exhaustive assessment of all potential vulnerabilities.
3Adaptability or versatility
If user-specific preferences are integrated into vulnerability prioritization, then adaptability is improved, but the complexity of the system increases
Solution Approach 1:
The patent applies segmentation by dividing the system into distinct functional modules: a data collection module, a user preference management module, a vulnerability analysis module, and a reporting module. Each module handles specific tasks independently, allowing user preferences to be integrated without overwhelming the entire system. This modular architecture maintains adaptability while managing complexity through clear separation of concerns and defined interfaces between components.
4Measurement precision
If domain-specific knowledge databases are used to improve vulnerability assessment, then measurement precision is improved, but the initial setup time and resource requirements increase
Solution Approach 1:
The patent applies preliminary action by pre-collecting and organizing vulnerability data, domain-specific knowledge, and assessment criteria into databases before actual vulnerability assessment begins. The system performs preliminary setup by establishing data collection mechanisms, configuring initial parameters, and preparing reference databases in advance. This preliminary preparation reduces the time required during actual assessment operations while maintaining high measurement precision through pre-validated data and criteria.
Data Source
AI summary
A method for prioritizing among vulnerabilities in a software code for a user by using a server is presented. The method comprises receiving a request, a software identification associated to the software code, and a user identification associated to the user from a user computer, fetching domain specific knowledge (DSK) data from a DSK database by using the software identification, wherein the DSK database comprises non-user defined features related to the vulnerabilities, fetching user specific knowledge (USK) data from a USK database by using the user identification, wherein the USK database comprises user defined features related to the vulnerabilities, determining utility estimations for the vulnerabilities, respectively, by comparing the vulnerabilities with the DSK data and comparing the vulnerabilities with the USK data, and transferring the utility estimations from the server to the user computer such that a prioritized list of vulnerabilities can be achieved.