Privacy Query Processing via Homomorphic Encryption and Selective Masking
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Solution Overview
Problem
Current privacy systems in social networking applications fail to provide selective data filtering based on query context and permissions, leading to exposure of sensitive information, as they either hinder full participation or do not allow for nuanced control over data sharing.
Innovation Solution
A system that analyzes query permissions and contexts to determine access levels, masking data and employing homomorphic encryption to perform operations on encrypted data without decryption, while allowing selective filtering and response customization based on query-specific permissions and contexts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is completely prevented from being seen by making it entirely private or encrypting it, then privacy protection is improved, but the ability to fully participate in social networking applications deteriorates
Solution Approach 1:
The patent applies local quality by implementing different privacy levels for different portions of data. Instead of making all data completely private or public, the system allows users to specify that certain data elements should be visible only to specific groups or individuals, while other data remains public. This enables selective privacy control where each data element can have its own access permissions, resolving the contradiction between privacy protection and social networking participation.
2Productivity
If all or a portion of the data being queried is exposed to answer queries, then query processing capability is improved, but exposure of sensitive information deteriorates
Solution Approach 1:
The patent applies the extraction principle by separating sensitive information from query results. The system processes queries against the full database to maintain query processing capability, but then extracts and removes sensitive data elements from the results before returning them to users. This allows the database to be fully queried for analytical purposes while preventing exposure of sensitive personal information in the returned results.
3Measurement precision
If data is decrypted before query processing, then query accuracy is improved, but security during processing deteriorates
Solution Approach 1:
The patent applies the intermediary principle by introducing a secure processing environment as a mediator between the encrypted database and query results. Queries are processed within this secure environment where data can be temporarily decrypted under controlled conditions, with automatic re-encryption of results. This intermediary layer maintains query accuracy while mitigating security risks through controlled access and automatic security measures.
Data Source
AI summary
A technique for protecting the privacy of a query is provided using permissions that may be derived from an analysis of the context of the query. A monitoring component can be provided to receive or intercept queries directed at a datastore, and a privacy component is provided that analyzes permissions associated with the queries. The privacy component can also determine access levels of the queries based on the analysis of the permissions. A response component can then be provided to answer the queries in accordance with the access levels of the queries.