Anonymous Insights Records for Secure Personal Data Access
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Solution Overview
Problem
The transmission, use, and retention of personal data by service providers compromise individuals' privacy, as data is often retained beyond consented use and is susceptible to undesired uses due to privacy regulations and data sharing restrictions.
Innovation Solution
An insights provider creates anonymous insights records on a blockchain using limited-use subject random numbers, encrypting and sharding data across decentralized storage, ensuring secure access and minimizing exposure of personal information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If service providers obtain and retain personal data for risk analysis and transaction processing, then service delivery and risk assessment capabilities are improved, but privacy protection deteriorates as data is retained beyond consented use and susceptible to undesired uses
Solution Approach 1:
The patent segments personal data into multiple shards distributed across different storage locations. Each shard alone is insufficient to reconstruct the original data, requiring a threshold number of shards for access. This segmentation prevents any single service provider from obtaining complete personal data, thereby protecting privacy while still enabling risk analysis through cryptographic operations on distributed data fragments.
Solution Approach 2:
The patent introduces cryptographic intermediaries (homomorphic encryption schemes, zero-knowledge proofs, and secure multi-party computation protocols) as mediators between service providers and personal data. These intermediaries enable risk assessment and transaction processing without direct access to raw personal information, allowing service delivery while preventing unauthorized data retention and misuse.
2Adaptability or versatility
If personal data is transmitted and shared among multiple service providers and data providers, then comprehensive risk analysis and service quality are improved, but data security deteriorates due to increased exposure and susceptibility to undesired uses
Solution Approach 1:
The patent divides personal data into multiple encrypted shards that are distributed across different providers. Each provider receives only a fragment of the data, making it impossible for any single provider to access complete personal information. This enables comprehensive risk analysis through collaborative cryptographic operations while minimizing individual exposure and security risks.
Solution Approach 2:
The patent transforms personal data from plaintext to encrypted form using homomorphic encryption and other cryptographic transformations. This parameter change allows mathematical operations to be performed on encrypted data directly, enabling risk analysis and service quality assessment without decrypting the data, thereby maintaining security while achieving versatility.
3Ease of operation
If service providers retain personal data beyond the duration of consented use, then operational flexibility and service continuity are improved, but privacy protection deteriorates as data is kept longer than necessary
Solution Approach 1:
The patent implements preliminary action through automated data deletion schedules and expiration mechanisms configured before data is stored. Data is set to be automatically deleted after a predetermined period or upon completion of the transaction, preventing unauthorized retention. This preliminary configuration ensures service continuity during the authorized period while automatically enforcing privacy protection afterward.
Solution Approach 2:
The patent incorporates feedback mechanisms that monitor data usage and retention status. The system tracks whether data retention exceeds the consented duration and automatically triggers deletion procedures when the authorized period expires. This feedback loop maintains service continuity during the valid period while preventing unauthorized extended retention.
Data Source
AI summary
Techniques are described for algorithmic confidential computing on personal data and to an insights provider providing access to personal data using limited-use anonymous insights records stored on a blockchain. To enable service providers and other queriers to obtain such insights information in a secure manner, an insights provider creates an anonymous insights record that is recorded on a blockchain responsive a request from a subject indicating that the subject desires to share one or more items of insights information. An anonymous insights record contains a single-use (or limited number of use) random number that is used by the insights provider to index the data in a shards index database for the relevant shards of the insights data file. These multiple segments can then be stored across multiple separate repositories using a decentralized file storage service.