Policy Rule Script Generation for Automated Compliance Testing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing controls monitoring systems in organizations require significant manual effort for deployment and configuration, leading to code errors and challenges in detecting and remediating non-compliance, due to the specificity and variability of controls across different domains.
Innovation Solution
A script generation system that automatically creates system-generated scripts based on policy data in a tabular format, using a two-dimensional dataframe to generate executable commands that test for compliance with policy rules, thereby reducing manual coding and enhancing accuracy in preventing, detecting, and correcting non-compliance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual coding is used to create controls monitoring scripts, then flexibility in customizing controls can be achieved, but code errors increase and deployment efficiency decreases
Solution Approach 1:
The patent uses templates to generate control monitoring scripts automatically. Instead of manually coding each script, the system copies and adapts pre-defined template structures, filling in specific control parameters and policies. This eliminates manual coding errors while maintaining the ability to customize controls for different domains and requirements.
Solution Approach 2:
The system performs self-service by automatically generating, validating, and deploying control scripts without requiring manual intervention for each script creation. The automated script generation engine reads control definitions, selects appropriate templates, and produces ready-to-deploy scripts, significantly improving deployment efficiency while ensuring consistency and accuracy.
2Adaptability or versatility
If manual configuration is used for controls monitoring, then adaptability to different domains can be achieved, but human error increases and time consumption increases
Solution Approach 1:
The system dynamically adapts to different domains by automatically selecting and configuring appropriate control templates based on the specific domain requirements. The script generation engine adjusts script parameters, control frequencies, and monitoring thresholds dynamically according to the input control definitions, enabling versatile domain adaptation without manual reconfiguration.
Solution Approach 2:
The patent employs pre-defined control templates that contain standard monitoring patterns and configurations for common control types. These templates are prepared in advance with best practices and domain-specific knowledge already embedded, allowing the system to quickly generate accurate scripts by simply filling in domain-specific parameters rather than configuring everything from scratch.
3Productivity
If automated script generation is implemented, then deployment efficiency improves, but system complexity increases
Solution Approach 1:
The system architecture is segmented into distinct modular components: control definition input module, template selection module, script generation engine, validation module, and deployment module. Each component has a specific function and can be independently developed, maintained, and scaled. This segmentation manages system complexity while enabling efficient automated script generation through coordinated operation of specialized modules.
Data Source
AI summary
In some implementations, a system may receive policy data that defines one or more controls and a set of variable definitions associated with the one or more controls in a tabular format. The system may generate a two-dimensional dataframe in which each row corresponds to a policy rule, of the set of policy rules. The system may create a system-generated script that includes a sequence of commands based on the two-dimensional dataframe, wherein each command in the sequence of commands is generated from a row of the two-dimensional dataframe using string manipulations based on information in each column associated with the respective row and the set of variable definitions associated with the one or more controls. The system may execute the system-generated script to generate an output that indicates whether input data subject to the set of policy rules complies with the one or more controls.