Trust Tree Mechanism for Secure Third-Party Data Access
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Solution Overview
Problem
Users often grant unnecessary access to sensitive data through complex permission negotiations, leading to misuse by third-party applications that request data for one purpose but use it for nefarious activities, and sensitive information can be inadvertently revealed or extracted through online interactions.
Innovation Solution
A server-based system utilizing a hashing unit to provide unique hashes for user data, an authentication unit to verify requesting entities, and a decoding unit to display information securely within a protected environment, preventing data leakage to external parties by using overlays to manage and parcel sensitive data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If third-party applications are granted access to sensitive user data to provide services, then service functionality is improved, but data security and privacy protection deteriorate
Solution Approach 1:
The patent introduces a trusted execution environment (TEE) as an intermediary layer between third-party applications and sensitive user data. The TEE creates a protected enclave that applications can interact with through controlled interfaces, allowing service functionality while preventing direct access to raw sensitive data. This mediator architecture enables data processing within the TEE without exposing plaintext information to untrusted applications.
Solution Approach 2:
The patent segments the data access architecture into multiple isolated components: untrusted application space, trusted execution environment, and secure storage. By dividing the system into these distinct segments with controlled communication channels, the patent allows applications to perform their functions while limiting their access to only what is necessary through defined interfaces, thereby maintaining security boundaries.
2Adaptability or versatility
If applications request broad classes of user data to ensure service coverage, then service adaptability is improved, but data exposure and misuse risk worsen
Solution Approach 1:
The patent applies local quality by providing different levels of data access to different applications based on their specific needs. Rather than granting uniform broad access, the system evaluates each application's requirements and provides only the necessary data subsets through the TEE interfaces. This localized access control ensures service coverage while minimizing data exposure for each specific application context.
3Productivity
If web crawlers and data mining applications are allowed to traverse user interactions, then data analytics capability is improved, but user privacy protection deteriorates
Solution Approach 1:
The TEE acts as an intermediary that enables data analytics operations while protecting user privacy. Analytics applications can submit processing requests to the TEE, which performs computations on sensitive data within the protected environment. The TEE returns only the necessary results without exposing the underlying sensitive information to crawlers or data mining applications, thus enabling analytics capability while maintaining privacy boundaries.
Data Source
AI summary
Example implementations described herein are directed to a trust tree that allows third party applications to operate on sensitive user data within the confines of a protected environment. The environment storing the sensitive user data prevents the third party application from receiving sensitive user data through use of an overlay, while preserving the function of the third party application. This permits the value of the application to be provided to a user without the risk of the application violating the user's privacy.