Pedersen Commitment and Schnorr Proof for Digital Identity Privacy
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Solution Overview
Problem
Digital identity systems face privacy and security issues due to data leaks, where compromised personal data can be linked back to users' public keys, compromising their identity and privacy.
Innovation Solution
A method using a Pedersen commitment scheme for secure data storage and a Schnorr zero-knowledge proof to ensure that even if data is leaked, it cannot be linked to the user's public key, maintaining unlinkability and enhancing privacy and security.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If personal data is committed to a public blockchain platform, then data integrity and verification capability are improved, but user privacy and security deteriorate due to potential data leaks and linkability to public keys
Solution Approach 1:
The personal data is segmented into two separate components: the commitment (hash) is stored on the public blockchain for integrity verification, while the actual personal data remains stored privately on the user's device or secure cloud storage. This segmentation allows the system to maintain data integrity through blockchain verification while preventing privacy leakage by never exposing the actual data on the public platform.
Solution Approach 2:
A cryptographic commitment acts as an intermediary between the personal data and the blockchain. The commitment (c = H(data || salt)) serves as a verifiable placeholder that links to the data without revealing it. Third parties can verify data integrity by comparing the commitment on blockchain with a newly computed commitment from the data, without ever accessing the actual personal data.
2Object-affected harmful factors
If personal data is stored securely on cloud or local device, then privacy is improved, but verification capability deteriorates as third parties cannot verify data integrity
Solution Approach 1:
The user performs a preliminary action of computing a cryptographic commitment from the personal data and storing it on the blockchain before sharing the data with third parties. This preliminary commitment serves as a verification anchor that allows third parties to later verify data integrity without accessing the actual data, thus maintaining both privacy and verification capability.
Solution Approach 2:
The system implements a feedback mechanism where third parties can verify data integrity by computing a commitment from the received data and comparing it with the pre-stored commitment on the blockchain. This feedback loop ensures that data has not been tampered with while keeping the data private, as the verification process only requires the data and the public commitment, not the private key.
3Loss of information
If data is leaked and commitment is recomputed, then linkability to public key is possible, but user identity security deteriorates
Solution Approach 1:
The system converts the potential harm of data leaks into a benefit through the use of salted commitments. Even if data is leaked, the salted commitment structure ensures that the leak does not reveal the public key or enable tracking. The commitment c = H(data || salt) with random salt means that even identical data produces different commitments, and data leaks cannot be used to reverse-engineer the public key or link multiple commitments to the same user.
Solution Approach 2:
The system changes the parameter of the commitment function by introducing a random salt value that changes with each commitment. This parameter change ensures that even if the same personal data is committed multiple times or leaked, each commitment appears completely different and cannot be used to link back to the user's identity or public key, thus maintaining identity security even in case of data leaks.
Data Source
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AI summary
A method of generating a deniable commitment of personal data of a user with an unlinkable proof of the commitment of the personal data for securing user privacy in a digital identity system includes receiving the personal data of the user and receiving the commitment of the personal data according to a commitment scheme. An interactive zero-knowledge proof is engaged in with the user so as to verify that the commitment of the personal data opens to the personal data of the user.