Event-Based Secure Data Access With Sensor-Driven Authorization
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Solution Overview
Problem
Existing data access systems fail to provide timely and secure access to sensitive information when the data owner is unavailable, leading to potential delays in critical treatments or actions.
Innovation Solution
A secure data access system utilizing a machine learning model to determine event types and grant access to different security levels of data based on sensor input, enabling access even when the data owner is unavailable.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual authorization is required for data access, then data security is maintained, but access time is delayed when the data owner is unavailable
Solution Approach 1:
The system performs preliminary actions by having data owners pre-configure authorization rules, event types, and security level designations before critical events occur. When an event is detected, the system can immediately execute pre-defined access permissions without requiring real-time manual authorization, thus resolving the contradiction between maintaining security and enabling timely access.
2Reliability
If uniform high-level protection is applied to all data, then maximum security is achieved, but access efficiency is reduced for non-sensitive information
Solution Approach 1:
The system applies local quality by assigning different security levels to different data elements based on their sensitivity. Each data element can have its own security classification (e.g., high, medium, low), allowing the system to apply appropriate protection measures and access controls tailored to each data type, thereby maintaining high security for sensitive information while enabling efficient access for non-sensitive information.
3Loss of time
If automated event-based access is implemented, then access speed is improved, but system complexity increases
Solution Approach 1:
The system segments the complex automated authorization process into distinct, manageable components: event detection module, event type determination module, security level identification module, and access control module. Each component performs a specific function, making the overall system more manageable and maintainable while still achieving rapid automated authorization decisions.
Data Source
AI summary
A system may include a memory device, a computing device and a sensor. The memory device may include a first partition and a second partition. The first partition stores first data of a first user at a first security level. The second partition is configured to store second data of the first user at a second security level different from the first security level. The computing device may include at least one processor that implements a machine learning algorithm. The sensor may be configured to provide information to the computing device. The machine learning algorithm analyzes the information from the sensor to determine an occurrence of an event. Based on a determination of the occurrence of the event, the computing device provides access to at least one of the first data or the second data to a second user.