Data Transfer Risk Identification via Metadata Intermediary
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Solution Overview
Problem
There is a growing need for improved systems and methods to manage personal data securely and comply with varying privacy and security policies, as frequent breaches and misuse of personal data have increased, and individuals seek tools to minimize data processing by unauthorized entities.
Innovation Solution
A method and system that identify unauthorized data transfers by analyzing network addresses and data maps, generate metadata to block unauthorized transfers, and provide graphical user interfaces for approval or denial of data transfers, ensuring compliance with data handling requirements across different jurisdictions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If automated systems are used to detect and block unauthorized data transfers, then data security is improved, but system complexity increases
Solution Approach 1:
The system performs preliminary actions by detecting data transfers and generating metadata records before unauthorized transfers can occur. The automated detection system proactively identifies potential security violations and blocks them in advance, preventing breaches rather than responding after they occur.
Solution Approach 2:
The patent introduces metadata as an intermediary element that mediates between data transfer requests and security enforcement. The metadata records act as a intermediary layer that captures transfer information and enables automated decision-making about whether to allow or block transfers, simplifying the overall security architecture.
2Ease of operation
If manual review processes are implemented for data transfer approval, then control over data processing is improved, but processing time increases
Solution Approach 1:
The system applies partial manual review by requiring human approval only for metadata records that meet specific risk criteria, while allowing automated processing for lower-risk transfers. This selective approach maintains control where needed while minimizing time losses for routine transfers.
Solution Approach 2:
The system implements feedback loops where manual review decisions feed back into the automated detection system, refining future detection accuracy. The metadata records created during manual review processes provide feedback that improves the automated system's ability to make accurate decisions without human intervention in the future.
Data Source
AI summary
A data transfer analysis system is disclosed that analyzes data transfer log entries to determine whether a data transfer is authorized. The system determines information about the data assets involved in the data transfer (e.g., network address, geographical location, etc.) and uses a data map to determine if data transfers are authorized between the two data assets. If not, the system may take one or more actions, such as generating a notification, terminating the data transfer, restricting the access of the user that initiated the transfer, modifying network communications capabilities between the assets to prevent future transfers, and storing metadata that can be used to prevent future such transfers.