Blockchain Numerical Ranking via Homomorphic Encryption
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Solution Overview
Problem
In anonymous auctions based on blockchain, ensuring the credibility of numerical value rankings while protecting participants' privacy is challenging due to potential collusion and lack of transparency in bid processes.
Innovation Solution
A blockchain-based numerical value ranking method where participants encrypt their private values using public keys, generate challenge values, and determine mixed results to rank themselves without revealing others' private values, ensuring credibility and privacy through homomorphic encryption and on-chain operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If bids are publicly disclosed in the entire auction process, then transparency is improved, but participant privacy is compromised
Solution Approach 1:
The bidding information is segmented into two parts: encrypted bid values stored on blockchain for transparency, and private key information kept secret by participants for privacy protection. This segmentation allows the system to provide both transparency and privacy simultaneously.
Solution Approach 2:
Homomorphic encryption acts as an intermediary between transparency and privacy requirements. It allows the system to process and compare encrypted bid values on the blockchain without decrypting them, thus maintaining both transparency in the ranking process and privacy of the actual bid values.
2Reliability
If bids and transactions are obscured and controlled by a middle party, then participant privacy is protected, but credibility and reliability of the final result deteriorate
Solution Approach 1:
The blockchain serves as a trusted intermediary that eliminates the need for a middle party to control or verify bids. The homomorphic encryption scheme allows the blockchain to perform ranking operations on encrypted data, providing credibility without requiring the middle party to access or control the actual bid values.
Solution Approach 2:
Participants can independently verify their own ranking results by using their private keys to decrypt the ranking information published on the blockchain. This self-service capability eliminates the need to trust the middle party, as each participant can verify the results themselves.
3Reliability
If homomorphic encryption and blockchain operations are implemented, then privacy protection and credibility are improved, but computational complexity and system complexity increase
Solution Approach 1:
The homomorphic encryption scheme provides multiple functions: it encrypts bid values, enables comparison operations on encrypted data, and allows ranking computation without decryption. This multi-functionality reduces the need for separate cryptographic protocols and simplifies the overall system architecture.
Solution Approach 2:
The system uses encrypted copies of the bid values on the blockchain instead of the actual values. These encrypted copies contain all the necessary information for ranking and verification, eliminating the need for participants to share or transmit their actual bid values, thus simplifying the interaction protocol.
4Reliability
If encrypted texts are used for bidding, then participant privacy is protected, but the ability to compare and rank bids deteriorates
Solution Approach 1:
Homomorphic encryption serves as an intermediary that preserves the numerical comparison capability within the encrypted domain. The encryption scheme is designed to maintain the order relationship of the original values, allowing the blockchain to compare encrypted bids and determine rankings without decrypting them.
Solution Approach 2:
The system changes the parameter representation from plaintext numerical values to homomorphically encrypted values. This parameter transformation maintains the essential property of numerical comparability while adding the security property of confidentiality, allowing both privacy protection and accurate ranking.
Data Source
AI summary
A blockchain based numerical value ranking method includes: using, by a first participant, a public key of the first participant to encrypt a private value of the first participant to obtain an encrypted text of the first participant; obtaining encrypted texts of other participants, and generating a challenge value having a preset bit length; based on the challenge value and the private value of the first participant, and the encrypted texts and public keys of the other participants, determining mixed results of the first participant with respect to the other participants; and determining a numerical value ranking result between the first participant and a second participant based on the mixed result of the second participant with respect to the first participant.