Batch PIR Retrieval With MPC for Private Database Queries
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Solution Overview
Problem
Existing data retrieval methods from databases fail to ensure data security and privacy, particularly in batch retrieval scenarios where servers can identify requested and returned data items, leading to potential breaches of confidential information.
Innovation Solution
Implementing private information retrieval (PIR) techniques combined with secure multi-party computation (MPC) using distributed point functions and probabilistic data structures, such as cuckoo filters, to encrypt and split key requests across multiple servers, ensuring that no single server can access the entire data or the requested keys and values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If traditional batch retrieval methods are used, then retrieval speed is improved, but data security and privacy are compromised as servers can identify requested and returned data items
Solution Approach 1:
The patent segments the retrieval process by splitting the batch request into multiple individual PIR requests, each processed separately through the MPC cluster. This segmentation prevents the server from identifying the complete set of requested data items while maintaining retrieval efficiency through parallel processing of the segmented requests.
Solution Approach 2:
The patent introduces secret-sharing mechanisms and cryptographic protocols as intermediaries between the client and server. These intermediaries enable the client to retrieve data without the server learning which specific items are requested, thus protecting data privacy while maintaining retrieval functionality.
2Object-affected harmful factors
If PIR techniques with MPC are implemented, then data security is improved, but computational complexity increases
Solution Approach 1:
The patent divides the computational workload by distributing it across multiple MPC servers in the cluster. Each server handles a portion of the secret-sharing computations, reducing the computational burden on any single server while maintaining strong security guarantees through the collective MPC protocol.
Solution Approach 2:
The patent uses secret-sharing copies of the data across multiple servers, where each server holds a share rather than the complete data. This copying approach enables secure computation without requiring any single server to possess the full computational complexity of processing the entire dataset.
3Loss of energy
If batch retrieval is performed without privacy protection, then bandwidth efficiency is improved, but servers can identify requested data items leading to privacy loss
Solution Approach 1:
The patent employs periodic padding in the PIR protocol where dummy data items are periodically inserted into the retrieval requests. This periodic action masks the actual requested items from the server while maintaining bandwidth efficiency through the structured nature of the padded requests.
Solution Approach 2:
The patent uses probabilistic data structures with porous characteristics that allow selective information flow. These structures enable the client to query for specific data items while the server cannot determine which items are actually requested, thus protecting privacy information while maintaining efficient bandwidth utilization.
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for batch retrieving data are described. In one aspect, a method includes receiving, from a client device and by a first multi-party computation (MPC) server of a cluster of MPC servers, a batch request for retrieving multiple database values stored in one or more databases. The batch request includes a first byte array that includes, for each requested key of multiple requested keys, a first secret share of the requested key. Each database includes multiple data items that each include a database key and a corresponding value. The MPC server processes each database key to generate first secret shares of matching data indicating whether the database key matches at least one requested key. The MPC server generates one or more results that represent database values corresponding to each database key that matches at least one requested key.