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 misuse of personal information have increased, and individuals seek tools to minimize data processing by entities they do not actively engage with, while companies must navigate diverse jurisdictional requirements.
Innovation Solution
A computer-implemented method for generating visualizations of data transfers, assessing risks, and determining relative readiness in personal data management, involving identifying data assets, analyzing data elements, determining relevant regulations, and calculating risk scores, as well as comparing privacy controls across entities to provide a relative readiness assessment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If organizations implement comprehensive data transfer monitoring and analysis systems to identify risks and ensure regulatory compliance, then data security and compliance capability are improved, but system complexity and implementation cost increase
Solution Approach 1:
The system segments data transfer monitoring into distinct functional modules: risk identification module that analyzes transfer patterns, visualization generation module that creates geographic representations, and regulatory determination module that assesses compliance requirements. Each module operates independently but integrates through standardized data interfaces, reducing overall system complexity while maintaining comprehensive monitoring capability.
Solution Approach 2:
The patent introduces an intermediary data processing layer that sits between raw data transfer logs and the analysis functions. This intermediary layer standardizes data formats, filters relevant information, and prepares data for downstream processing, thereby simplifying the complexity of direct analysis operations and improving system reliability.
2Adaptability or versatility
If organizations implement detailed data transfer visualization and risk assessment systems to comply with diverse jurisdictional requirements, then compliance capability is improved, but operational complexity increases
Solution Approach 1:
The system implements a universal data structure and analysis framework that can handle multiple jurisdictional requirements through a single operational interface. The risk identification module applies the same analytical methods across different regulatory contexts, while the regulatory determination module adapts compliance rules dynamically based on the jurisdiction being assessed, eliminating the need for separate operational procedures for each regulation.
Solution Approach 2:
The system changes parameters dynamically based on the target jurisdiction: it adjusts regulatory thresholds, risk tolerance levels, and visualization details according to the specific compliance requirements being assessed. This parameter-based adaptation allows the same system to comply with diverse jurisdictional requirements without increasing operational complexity.
3Reliability
If organizations conduct comprehensive risk assessments and calculate risk scores for data transfers, then ability to identify and mitigate data breaches is improved, but time and computational resources required increase
Solution Approach 1:
The system performs preliminary risk identification and scoring on data transfer patterns before actual data breaches occur. By continuously analyzing transfer metadata, access patterns, and anomaly indicators in advance, the system pre-calculates risk scores and identifies potential breach vectors, enabling organizations to mitigate risks proactively rather than reactively, thus reducing the time needed for breach identification.
Solution Approach 2:
The patent replaces manual, mechanical risk assessment processes with automated computational analysis. The system uses algorithmic risk scoring that processes multiple risk factors simultaneously through computer-based calculations, dramatically reducing the time and human resources required compared to traditional manual assessment methods while improving the accuracy and consistency of breach identification.
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.