Encrypted Information Retrieval via Secret Share Classification
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Solution Overview
Problem
Existing data retrieval methods fail to maintain both client and server privacy during querying, as they either require significant computational resources or do not allow for privacy preservation, and lack mechanisms to ensure adherence to protocols.
Innovation Solution
The method involves generating server-encrypted secret shares and client-encrypted secret shares, which are combined to classify client devices based on the number of shared secret shares, ensuring privacy by using commutative encryption and partitioning databases into shards and buckets, with special buckets containing server-only data to maintain privacy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If traditional data retrieval methods are used, then data can be retrieved from the server, but client privacy is revealed to the server and server privacy is revealed to the client
Solution Approach 1:
The database is partitioned into multiple database shards, each containing a subset of data. This segmentation allows the server to process queries on encrypted data without revealing the full database structure to the client, while the client can query specific shards without accessing the entire database. The special buckets within each shard further segment the data to enable privacy-preserving operations.
Solution Approach 2:
Encrypted secret shares act as an intermediary between the client and server. The client encrypts queries with its own key, the server processes these encrypted queries against encrypted data, and only the necessary encrypted results are transmitted back. This intermediary encryption layer prevents both parties from learning unnecessary information about each other's data.
2Loss of information
If encryption is applied to preserve privacy, then privacy is maintained, but computational resources and processing complexity increase
Solution Approach 1:
Instead of encrypting the entire database or all data operations, the system applies encryption only to specific query operations and only the necessary data portions. The server processes only the encrypted queries that are actually executed, rather than encrypting and processing the complete database schema and all potential queries. This partial encryption approach reduces computational overhead while maintaining privacy for actual data access operations.
3Loss of information
If the server processes all queries to ensure privacy, then privacy is maintained, but the server must verify client adherence to protocols
Solution Approach 1:
The server receives encrypted query results from the client and compares them against expected patterns to verify protocol adherence. The client is expected to submit queries in a specific format and receive results in predetermined structures. The server uses feedback mechanisms to validate that the client is following the agreed-upon query protocol, ensuring privacy is maintained while allowing efficient processing of compliant queries.
Data Source
AI summary
Methods, systems, and computer readable medium facilitating encrypted information retrieval. Methods can include receiving a batch of queries that includes queries to special buckets in each database shard. Query results responsive to the batch of queries are transmitted to the client device. The query results includes server-encrypted secret shares obtained from the special buckets. Client-encrypted versions of the secret shares are received. A full set of server-encrypted secret shares is transmitted to the client device, which is encrypted by the client device to create a full set of client-server-encrypted secret shares. The client device is classified based on how many of the secret shares are included in both of the client-encrypted secret shares received from the client device and the full set of client-server-encrypted secret shares received from the client device.