Automated Personal Data Access Control System
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Solution Overview
Problem
Current systems for controlling user personal data lack automation in granting and revoking access rights, requiring manual user intervention.
Innovation Solution
An automated system that collects information about consumers of personal data, compares it with risk criteria templates, and adjusts access parameters based on identified risks using a hardware processor to control access to the user's personal information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual control of personal data access is implemented, then user control capability is improved, but automation level deteriorates
Solution Approach 1:
The system enables automated self-service control where the access control system automatically monitors consumer behavior, assesses risks, and adjusts access parameters without requiring manual user intervention. The system serves itself by autonomously making access control decisions based on predefined risk criteria and real-time data analysis.
Solution Approach 2:
The system implements continuous feedback loops where access patterns are monitored, risk assessments are updated in real-time, and access parameters are dynamically adjusted based on the feedback from risk analysis. This closed-loop control enables automated adaptation while maintaining user control objectives.
2Extent of automation
If automated risk-based access control is implemented, then automation level is improved, but system complexity deteriorates
Solution Approach 1:
The automated access control system is segmented into distinct functional modules: data collection module, risk assessment module, decision-making module, and access control module. Each module performs a specific function, making the overall complex system manageable through modular design where each segment can be independently developed, tested, and maintained.
Solution Approach 2:
The system introduces intermediary components such as risk assessment algorithms and decision rules that mediate between raw data collection and final access control decisions. These intermediaries simplify the complexity by providing structured processing layers that transform complex data into actionable access control decisions.
3Speed
If real-time monitoring of consumer data is implemented, then response speed to risk changes is improved, but information processing load deteriorates
Solution Approach 1:
The system applies partial monitoring by focusing only on critical risk indicators and key access events rather than continuously processing all possible data. Risk assessment is triggered selectively based on predefined conditions, reducing unnecessary processing while maintaining rapid response to genuine risks.
Solution Approach 2:
The system dynamically adjusts monitoring parameters such as sampling rates, threshold values, and assessment intervals based on current risk levels and system load. When risk is low, monitoring intensity is reduced to minimize processing load; when risk increases, the system intensifies monitoring to maintain rapid response capability.
Data Source
AI summary
Disclosed are system and methods for controlling access of a consumer to personal data of a user. An example method includes: collecting information about the consumer of personal data; comparing the collected information with one or more templates containing risk criteria to determine whether a risk is associated with the consumer; setting, based on the determined risk, consumer access parameters for access of the consumer to the personal information of the user; and controlling access of the consumer to the personal data of the user based on the set consumer access parameters.