Homomorphic Encryption Compression for Private Database Search
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Solution Overview
Problem
The rapid growth of data storage demand has outpaced the capacity to store it, leading to storage and transmission bottlenecks, particularly with multimedia data, and existing data compression methods are inadequate for maintaining privacy during data searches.
Innovation Solution
A system and method for data compression using homomorphic encryption, enabling secure storage and comparison of encrypted data by optimizing data for lossless compression and employing an encrypted search engine to perform homomorphic encryption and store encrypted data in a database, allowing encrypted queries to be compared against encrypted elements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data compression is applied to reduce storage demand, then storage capacity utilization improves, but data privacy and security deteriorate
Solution Approach 1:
The patent applies preliminary action by performing data compression before encryption. The system compresses the original data to reduce its size, then encrypts the compressed data. This sequence allows the data to be stored in compressed form (improving storage utilization) while still maintaining security through subsequent encryption, resolving the contradiction between storage efficiency and data privacy.
Solution Approach 2:
The patent introduces an intermediary approach by using compressed data as a intermediate state between original data and encrypted data. Instead of directly encrypting uncompressed data or storing uncompressed data, the system creates a compressed intermediate representation that occupies less space, then applies encryption to this intermediate form, thereby balancing storage efficiency with security.
2Reliability
If homomorphic encryption is applied to maintain data privacy during storage, then data security improves, but computational complexity increases
Solution Approach 1:
The patent reduces computational complexity by performing data compression before homomorphic encryption. Since homomorphic encryption operates on the compressed (smaller) data rather than the original larger data, the computational burden is significantly reduced while still maintaining the security benefits of homomorphic encryption on the sensitive information.
3Manufacturing precision
If lossless compression is used to maintain data integrity, then data accuracy improves, but compression ratio deteriorates
Solution Approach 1:
The patent applies partial action by using lossless compression only when data integrity is critical, rather than universally applying aggressive compression. The system prioritizes maintaining complete data fidelity through lossless methods, accepting the resulting larger compressed size, then applies homomorphic encryption to this intact data, ensuring both integrity and security are preserved.
Data Source
AI summary
Data compression with homomorphic encryption enables secure storage of private information in a database and searching and comparison of encrypted data within the database. A stream conditioning system optimizes the contents of received data for lossless compression by a data encoder that performs the lossless compression. An encrypted search engine encrypts the compressed data according to a homomorphic encryption scheme and store the encrypted data in a database. Data queries are received and encrypted according to the homomorphic encryption scheme. The encrypted data query is compared against an encrypted element in the database and an encryption score generated. The encryption score may be compared against a set of criteria to determine if a match is found. Matched data may be returned to the requesting entity.