Encrypted Index Construction via Permutation Networks
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Solution Overview
Problem
Existing PIR algorithms for encrypted queries suffer from slower performance compared to standard queries, due to the inability of the database to learn query constraints and optimize data retrieval.
Innovation Solution
The system creates an encrypted index by mapping records to integers, permuting them using a pseudo-randomly selected permutation generated by a permutation network, and encrypting the permutation using homomorphic encryption to create an encrypted swap vector, which is then applied to the plaintext index to generate the encrypted index.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing PIR algorithms are used for encrypted queries, then data privacy is maintained, but query performance deteriorates (slower than standard queries)
Solution Approach 1:
The system performs preliminary actions by constructing encrypted indexes before queries are executed. The encrypted index is built by applying a permutation network to the plaintext index and encrypting the swap vector, so that when a query arrives, the database can efficiently retrieve encrypted records using the pre-computed encrypted index without performing heavy cryptographic operations during the actual query execution.
Solution Approach 2:
The patent introduces an encrypted permutation index as an intermediary data structure between the plaintext database and the query system. This intermediary allows the database to perform efficient range queries and equality searches on encrypted data by translating query constraints into positions in the encrypted index, avoiding the need for full database scans while maintaining encryption.
2Loss of information
If the database cannot learn query constraints, then query privacy is improved, but data retrieval optimization deteriorates
Solution Approach 1:
The system changes the parameter representation by transforming query constraints into positions in the encrypted permutation index. Instead of the database seeing the actual query constraints (which would compromise privacy), the query is transformed into a position-based access pattern on the encrypted index, allowing efficient retrieval without revealing the underlying constraint values.
3Productivity
If encrypted indexes are constructed using permutation networks and homomorphic encryption, then query efficiency is improved (sub-linear amortized performance), but system complexity increases
Solution Approach 1:
The patent replaces traditional cryptographic mechanisms with a permutation-based approach. Instead of using complex homomorphic encryption schemes for every query operation, the system uses a permutation network that can be efficiently evaluated and updated. The permutation index allows the database to perform efficient range queries and equality searches on encrypted data without requiring the querier to download the entire database.
Data Source
AI summary
Described herein are methods and systems for constructing an encrypted index of a database to facilitate secure and efficient encrypted queries. An example method includes creating a plaintext index sorted by specific attributes, mapping records to integers via a hash function, permuting records using a pseudo-random permutation network, and generating an encrypted swap vector through homomorphic encryption. This encrypted swap vector is then sent to the database, enabling the creation of an encrypted index that maintains query privacy while supporting efficient retrieval of data.