Privacy Data Governance System for Dark Source Compliance
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Solution Overview
Problem
Organizations face challenges in adapting their privacy data protection programs to comply with increasingly complex and region-specific data privacy regulations, particularly in identifying and addressing non-compliance in unknown or 'dark' data sources within their ecosystems.
Innovation Solution
A method and system that utilizes a processor circuitry to detect dark data sources, identify user information and relationships, scan for user privacy data using natural language processing, and apply relevant compliance policies to eliminate non-compliance by processes such as backup, encryption, or masking, while monitoring for new data sources and handling individual rights and consent requests.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If organizations focus solely on compliance with data privacy regulations, then regulatory requirements are met, but the complexity of adapting to increasingly detailed and region-specific regulations increases
Solution Approach 1:
The system provides a universal privacy data protection platform that automatically adapts to multiple region-specific regulations (GDPR, CCPA, PIPEDA, etc.) through a single integrated solution. The compliance engine evaluates data sources against multiple regulatory frameworks simultaneously, eliminating the need for separate compliance programs for each jurisdiction.
Solution Approach 2:
The system enables automated self-service compliance through machine learning models that automatically detect dark data sources, classify personal data, assess compliance status, and generate remediation plans without manual intervention. The continuous monitoring and auto-remediation capabilities allow the system to maintain compliance autonomously.
2Reliability
If organizations manually monitor all data sources for compliance, then compliance status can be tracked, but the time and resources required increase significantly
Solution Approach 1:
The system replaces manual compliance monitoring with automated machine learning models and natural language processing engines. These AI systems continuously scan and evaluate data sources, replacing the mechanical process of manual review with intelligent automated analysis that operates 24/7 without human intervention.
Solution Approach 2:
The system implements continuous automated monitoring of all data sources including dark data, ensuring compliance is tracked constantly rather than through periodic manual audits. The machine learning models continuously evaluate new data sources as they emerge, maintaining uninterrupted compliance oversight.
3Device complexity
If organizations ignore dark data sources, then existing known data sources remain manageable, but unknown data sources may contain personal data that creates compliance risks
Solution Approach 1:
The system performs preliminary detection and classification of dark data sources before they become compliance liabilities. Machine learning models proactively identify unknown data sources, assess their contents, and evaluate compliance risks in advance, allowing organizations to address potential issues before they result in violations.
Solution Approach 2:
The system introduces an intermediary layer of AI-powered discovery and assessment tools that bridge the gap between known managed data sources and unknown dark data. This intermediary automatically explores uncharted data territories, classifies personal data, and connects dark data sources to the compliance management framework.
4Productivity
If organizations implement comprehensive automated compliance systems, then compliance monitoring improves, but the initial setup and implementation complexity increases
Solution Approach 1:
The system employs dynamic machine learning models that automatically adapt to new regulations, data sources, and compliance requirements without requiring complex reconfiguration. The system evolves autonomously, adjusting its monitoring and assessment capabilities based on changing regulatory landscapes and organizational data ecosystems.
Data Source
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AI summary
A system for governing user privacy data may include detecting a dark data source in a data ecosystem including data sources storing user privacy data. The system may further include identifying user information from the data ecosystem according to a lineage of datasets and scanning the dark data source by executing a natural language processing engine to identify existence of and content of user privacy data in the dark data source based on the user information. The system may further include selecting a target user privacy data compliance policy from user privacy data compliance policies based on a geographical region associated with the dark data source and detecting non-compliance in protecting the user privacy data in the dark data source based on the target user privacy data compliance policy. The system may further include, in response to the non-compliance, processing the user privacy data to eliminate the non-compliance.