Compliance Evidence Analysis for Automated Cybersecurity Scoring
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Solution Overview
Problem
Existing cybersecurity compliance assessments in organizations are time-consuming, expensive, and prone to subjectivity due to manual processes and varying levels of human competency, necessitating a more efficient and objective evaluation method.
Innovation Solution
An automated system utilizing machine learning algorithms, regular expression analysis, and image text extraction to assess cybersecurity compliance, incorporating hardware and software probes to monitor network activity, generate compliance scores, and transmit remediation commands.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual processes are used for cybersecurity compliance assessments, then human judgment and flexibility can be applied, but the assessments become time-consuming, expensive, and prone to subjectivity
Solution Approach 1:
The patent replaces manual human assessment processes with an automated computer-based system that uses machine learning models, regular expression analysis, and image text extraction. This substitution eliminates human subjectivity and variability while maintaining consistent, objective evaluation criteria across all assessments. The automated system processes compliance data without human intervention, thereby resolving the contradiction between achieving objective measurements and reducing assessment time.
Solution Approach 2:
The system enables self-service automation where the compliance assessment process serves itself through automated data collection, analysis, and scoring. The computer-based system automatically extracts data from network devices, applies assessment criteria, generates compliance scores, and identifies remediation actions without requiring human operators to manually perform each step. This self-service capability simultaneously improves objectivity and reduces the time required for assessments.
2Reliability
If manual cybersecurity compliance assessments are performed, then detailed human analysis can be conducted, but the process becomes expensive and inconsistent due to varying human competency
Solution Approach 1:
The patent replaces variable human analysis with a standardized automated computer-based assessment system. The system uses consistent machine learning models and regular expression patterns that apply the same evaluation criteria to all assessments, eliminating variability caused by different human competencies. This substitution ensures reliable and consistent results while managing system complexity through automated processes.
Solution Approach 2:
The system transforms the assessment process from human-dependent to parameter-driven evaluation. By using machine learning models with defined parameters, regular expression patterns, and standardized scoring criteria, the system ensures that the same parameters are applied consistently across all assessments. This parameter-based approach guarantees reliability and consistency while the automated nature of the system manages the complexity of implementing these standardized parameters.
3Productivity
If traditional compliance assessment methods are used, then comprehensive analysis can be performed, but frequent monitoring becomes impractical due to time and resource constraints
Solution Approach 1:
The patent replaces traditional manual compliance assessment methods with an automated computer-based system that can execute assessments frequently and efficiently. The automated system collects data from network devices, processes compliance information, and generates reports without the time and resource constraints that limit manual assessment frequency. This substitution enables continuous or near-continuous monitoring while managing the complexity of the automation infrastructure.
Solution Approach 2:
The system performs preliminary automated data collection and preparation from network devices before conducting compliance assessments. By pre-collecting and organizing compliance data through automated probes and data extraction mechanisms, the system reduces the time required for each assessment execution, thereby enabling more frequent monitoring. This preliminary action approach manages the complexity of frequent assessments by preparing data in advance.
Data Source
AI summary
A method and a system for assessing the compliance of continuous cybersecurity data security of infrastructure, endpoints, and other organization aspects. The method may include obtaining image data from a data repository and performing, by a computer processor, a similarity comparison of the obtained image data using a plurality of comparison techniques. Further, the method includes extracting cybersecurity data from the obtained image data and preprocessing the cybersecurity data using at least one preprocessing technique. A first assessment of the preprocessed cybersecurity data is generated using regular expression analysis and a second assessment of the preprocessed cybersecurity data is generated using a plurality of machine learning models. A cybersecurity compliance score is computed based on the first assessment and the second assessment and a remediation command configured to adjust at least one configuration setting of a network is transmitted.