Cross-Border Data Transfer Visualization and Risk Assessment
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Solution Overview
Problem
There is a growing need for improved systems and methods to manage personal data in compliance with privacy and security policies, as frequent breaches and unauthorized access to sensitive information have become more common, and individuals seek tools to minimize data processing by entities they do not actively engage with.
Innovation Solution
A computer-implemented method for generating a visualization of data transfers and assessing risks associated with these transfers, involving identifying data assets, analyzing data elements, determining relevant regulations, and calculating risk scores, while also providing tools for data subject access requests and compliance with legal and industry standards.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If comprehensive data transfer monitoring and analysis systems are implemented to identify all data transfers between data assets, then data security and compliance capability is improved, but system complexity and resource consumption increase
Solution Approach 1:
The system segments data transfers into different types (internal, external, cross-border) and processes them through specialized modules. Each data transfer record is analyzed independently through a pipeline of assessment rules, rather than attempting to analyze all transfers monolithically. This segmentation reduces overall system complexity while maintaining comprehensive security monitoring.
Solution Approach 2:
The patent introduces intermediary components including data transfer records that mediate between data assets and analysis systems, risk assessment rules that mediate between regulations and evaluation criteria, and visual representation systems that mediate between complex data and user comprehension. These intermediaries buffer complexity while preserving security monitoring capability.
2Measurement precision
If detailed risk assessment rules and regulations are applied to all data transfers, then compliance accuracy is improved, but processing time and computational resources increase
Solution Approach 1:
The system performs preliminary actions by pre-defining risk assessment rules and regulations in a structured format before actual data transfer monitoring begins. Assessment rules are pre-configured with criteria, weights, and thresholds, allowing the system to quickly evaluate transfers against established standards rather than creating assessments in real-time, thus maintaining accuracy while reducing processing time.
Solution Approach 2:
The patent applies parameter changes by adjusting risk assessment thresholds, weights, and criteria based on data transfer characteristics, asset sensitivity levels, and regulatory requirements. The system dynamically modifies assessment parameters to match the specific context of each transfer, achieving high compliance accuracy without applying uniform complex rules to all transfers.
3Loss of information
If visual representations of data transfers are generated showing physical locations and regulatory compliance, then data flow visibility is improved, but information processing overhead increases
Solution Approach 1:
The system creates simplified visual representations (copies) of the complex data transfer network, showing physical locations, data flows, and compliance status in an easily interpretable format. Rather than processing and displaying all raw data transfer details, the system generates condensed visual models that preserve essential information while reducing processing overhead for display and analysis.
Solution Approach 2:
The patent adds spatial and regulatory dimensions to data transfer visualization by mapping transfers to physical locations and overlaying compliance information. This multi-dimensional representation consolidates complex data into intuitive visual formats that improve visibility without requiring proportional increases in processing resources.
Data Source
AI summary
In particular embodiments, a Cross-Border Visualization Generation System is configured to: (1) identify one or more data assets associated with a particular entity; (2) analyze the one or more data assets to identify one or more data elements stored in the identified one or more data assets; (3) define a plurality of physical locations and identify, for each of the identified one or more data assets, a respective particular physical location of the plurality of physical locations; (4) analyze the identified one or more data elements to determine one or more data transfers between the one or more data systems in different particular physical locations; (5) determine one or more regulations that relate to the one or more data transfers; and (6) generate a visual representation of the one or more data transfers based at least in part on the one or more regulations.