Analysis Unit for Computer System Security Evaluation
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Solution Overview
Problem
Complex computer systems face challenges in evaluating their own performance and security due to the difficulty in identifying vulnerabilities and strengths, which can lead to inefficiencies and increased risk from cyber-attacks, especially given the limitations of in-house IT departments or third-party providers.
Innovation Solution
An analysis system that evaluates computer systems by assessing understanding, implementation, and operation through various evaluation categories and metrics, including identify, protect, detect, respond, and recover, using data extraction and analysis modules to provide an evaluation rating and auto-correction capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If comprehensive system evaluation is implemented to identify vulnerabilities and strengths, then system security and reliability are improved, but system complexity and resource requirements increase
Solution Approach 1:
The evaluation system is divided into multiple independent modules including data extraction module, data analysis module, and evaluation rating module. Each module handles specific aspects of the evaluation process, making the overall system more manageable and less complex while maintaining comprehensive evaluation capabilities.
Solution Approach 2:
The patent introduces an intermediary evaluation system that acts as a mediator between the monitored system and the evaluation output. This intermediary layer processes raw system data through structured evaluation categories and metrics, transforming complex system states into interpretable evaluation ratings without requiring direct complex interactions between all system components.
2Productivity
If continuous monitoring and evaluation of system performance is performed, then system efficiency and security are improved, but loss of time and computational resources increase
Solution Approach 1:
The evaluation system operates periodically rather than continuously, collecting data over time intervals and performing comprehensive evaluations at scheduled moments. This periodic operation reduces computational overhead and time loss while still maintaining effective monitoring and evaluation of system performance trends.
Solution Approach 2:
The system applies partial evaluation actions by focusing on specific evaluation categories and metrics relevant to particular system states or concerns, rather than performing exhaustive evaluation of all possible parameters continuously. This selective approach reduces resource consumption while maintaining evaluation effectiveness.
Data Source
AI summary
An analysis unit of an analysis system includes a data module and an analyze and score module. The data module receives data analysis parameters regarding a particular evaluation of a system, determines data collection parameters and data parsing parameters, interacts with a collection of data to collect data relevant to the particular evaluation, based upon the data parsing parameters, parses the data relevant to the particular evaluation to produce source data. The analyze and score module receives the data analysis parameters regarding the particular evaluation, determines a system aspect, an evaluation aspect, one or more evaluation metrics, one or more evaluation modes, and one or more evaluation perspectives, and evaluates the source data in accordance with the system aspect, the evaluation aspect, the one or more evaluation metrics, the one or more evaluation modes, and the one or more evaluation perspectives to produce one or more evaluation outputs including ratings.