Confidential Ledger Transfers With ZK Proofs and Encrypted Balances
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Solution Overview
Problem
Existing blockchain technologies face challenges in integrating substantial privacy measures due to limitations in versatility, user experience, and impractical implementation, particularly in supporting large value ranges and efficient operations on devices with limited computational resources.
Innovation Solution
A confidentiality-preserving token (CPT) protocol leveraging zk-proofs and Elliptic Curve ElGamal (ECEG) encryption provides on-chain confidentiality for transactions, enabling efficient homomorphic operations and auditability, using a sub-value method to handle large value ranges and prevent front-running attacks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional blockchain transparency is implemented, then data integrity and security are enhanced, but user privacy is compromised
Solution Approach 1:
The patent segments transaction data into encrypted components that can be independently verified without revealing the underlying values. Zero-knowledge proofs are divided into verification statements that confirm validity without exposing sensitive information, allowing the system to maintain data integrity while preserving user privacy through cryptographic segmentation of information.
Solution Approach 2:
The patent introduces zero-knowledge proofs as an intermediary mechanism between transparent blockchain verification and private user data. These proofs act as mediators that allow third parties to verify transaction validity without directly accessing or exposing the underlying sensitive information, thus maintaining both integrity and privacy simultaneously.
2Loss of information
If privacy measures are integrated into blockchain, then user confidentiality is improved, but device complexity and computational requirements increase
Solution Approach 1:
The patent applies preliminary action by pre-computing and storing verification parameters and circuit definitions before actual transactions occur. This allows the complex zero-knowledge proof verification logic to be prepared in advance, reducing the computational burden on devices during actual transaction verification and simplifying the user experience while maintaining strong privacy protections.
Solution Approach 2:
The patent utilizes parameter changes in elliptic curve cryptography, specifically transitioning between different curve parameters and mathematical representations to enable efficient homomorphic operations. By changing cryptographic parameters and using additive homomorphic encryption properties, the system achieves privacy protection with optimized computational requirements suitable for resource-constrained devices.
3Loss of information
If zero-knowledge proofs are used for transaction verification, then privacy is preserved, but verification time and computational overhead increase
Solution Approach 1:
The patent applies partial action by implementing selective verification where only critical aspects of transactions require full zero-knowledge proof verification. Less sensitive operations can use simplified verification mechanisms, allowing the system to preserve privacy where necessary while reducing verification time for routine operations, thus balancing security and efficiency.
Solution Approach 2:
The patent uses copying by creating and verifying cryptographic hashes and commitments of transaction data before full verification. These cryptographic copies allow rapid preliminary validation of transaction integrity, with full zero-knowledge proof verification only required when necessary, significantly reducing average verification time while maintaining privacy protection.
4Loss of information
If homomorphic encryption is implemented for confidential transfers, then balance confidentiality is maintained, but computational resources required increase
Solution Approach 1:
The patent substitutes traditional cryptographic verification mechanisms with homomorphic encryption-based verification. Instead of requiring computationally intensive decryption and re-encryption operations, the system uses the mathematical properties of homomorphic encryption to allow verification of confidential transfers through simpler homomorphic operations, reducing computational energy requirements while maintaining balance confidentiality.
Data Source
AI summary
Various aspects of the subject technology relate to systems, methods, and machine-readable media for improving the privacy of transfers in a distributed ledger. Various aspects may include encrypting a transaction using a first public key corresponding to a first user and a second public key corresponding to a second user. Aspects may also include transmitting the encrypted transaction to a blockchain, the encrypted transaction including at least an encrypted amount, a zero-knowledge proof, and an encrypted balance of the first user. Aspects may also include verifying a correctness of the zero-knowledge proof. Aspects may also include, based on the correctness, executing the transaction through a smart contract of the blockchain and homomorphically updating encrypted balances of the first user and the second user in accordance with the encrypted amount.