Secure Database Group-By Using One-Hot Encoding in MPC
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Solution Overview
Problem
Existing secure multi-party computation (MPC) protocols for group-by operations in databases face high computational and communication complexities due to the need for ciphertext sorting and numerous comparison operations, especially when attributes are distributed across multiple databases controlled by different entities.
Innovation Solution
Perform local operations such as one-hot encoding on categorical data to convert it into numerical data, and use oblivious shuffling protocols for sorting, reducing complexity and ensuring data privacy by leveraging secure MPC.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If secure MPC protocols are used for group-by operations with distributed attributes, then data privacy is protected, but computational and communication complexities increase significantly
Solution Approach 1:
The patent applies preliminary action by performing one-hot encoding on categorical attributes before the secure MPC group-by operation. This preprocessing converts categorical data into numerical format, enabling more efficient computation during the secure protocol execution and reducing the overall computational complexity while maintaining privacy guarantees
Solution Approach 2:
The patent changes the parameter representation by transforming categorical attributes into one-hot encoded binary vectors. This parameter transformation allows the secure MPC protocol to operate on numerical data with reduced complexity compared to handling raw categorical data or using traditional ciphertext sorting methods
2Reliability
If traditional ciphertext sorting methods are used in secure MPC, then data privacy is maintained, but communication complexity increases due to numerous comparison operations
Solution Approach 1:
The patent extracts the sorting operation from the secure MPC protocol by performing one-hot encoding and grouping operations locally or semi-locally before final aggregation. This separation removes the need for numerous ciphertext comparison operations within the secure protocol, significantly reducing communication overhead while preserving privacy through the secure aggregation of encoded results
Data Source
AI summary
The present disclosure involves methods, apparatus, and systems for processing group-by operations in databases. In one example, a method includes receiving a query to perform a group-by operation based on first attributes and second attributes of a plurality of entities. The first attributes are private data owned by a first participant of a secure multi-party computation (MPC), and the second attributes are private data owned by a second participant of the secure MPC. The method further includes performing one-hot encoding on the first attributes to generate encoded first attributes, and calculating, based on secure MPC, a secret share of a dataset. The dataset includes the first set of numbers and the second attributes. The method further includes performing the group-by operation including arranging the plurality of entities into groups based on at least the encoded first attributes, and aggregating the second attributes of entities in each of the groups.