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BlockMaze: An Efficient Privacy-Preserving Account-Model Blockchain Based on zk-SNARKs
Authors: Zhangshuang Guan, Zhiguo Wan, Yang Yang, Yan Zhou, Butian HuangAbstract:
The disruptive blockchain technology is expected to have broad applications in many areas due to its advantages of transparency, fault tolerance, and decentralization, but the open nature of blockchain also introduces severe privacy issues. Since anyone can deduce private information about relevant accounts, different privacy-preserving techniques have been proposed for cryptocurrencies under the UTXO model, e.g., Zerocash and Monero. However, it is more challenging to protect privacy for account-model blockchains (e.g., Ethereum) since it is much easier to link accounts in the account-model blockchain. In this paper, we propose BlockMaze, an efficient privacy-preserving account-model blockchain based on zk-SNARKs. Along with dual-balance model, BlockMaze achieves strong privacy guaran- tees by hiding account balances, transaction amounts, and linkage between senders and recipients. Moreover, we provide formal security definitions and prove the security of BlockMaze. Finally, we implement a prototype of BlockMaze based on Libsnark and Go-Ethereum, and conduct extensive experiments to evaluate its performance. Our 300-node experiment results show that BlockMaze has high efficiency in computation and transaction throughput: one transaction verification takes about 13.8 ms, one transaction generation takes 4.6-18.2 seconds, and its throughput is around 20 TPS.
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