zk-AuthFeed: How to Feed Authenticated Data into Smart Contract with Zero Knowledge
Zhiguo Wan, Zhangshuang Guan, Yan Zhou, Kui Ren
Abstract
Zhiguo Wan, Zhangshuang Guan, Yan Zhou, Kui Ren
Abstract
The emerging blockchain technology, powered by the smart contract functionality, is expected to revolutionize traditional systems by decentralization and autonomy. When the blockchain technology is applied in real-life systems, a smart contract may need to take in sensitive data to execute its code. For example, a decentralized medical insurance smart contract needs access to personal health data. Therefore, it is crucial to guarantee both privacy and authenticity of data sent to the smart contract, so that everyone can verify data without leaking sensitive information. Currently, only few works have tried to achieve privacy and authenticity at the same time. In this work, we first propose zk-DASNARK, a zero-knowledge SNARK scheme for authenticated data. It is designed by combining the zk-SNARK technique with digital signature in an effective way. Based on zk-DASNARK, we design zk-AuthFeed, a zero-knowledge authenticated data feed scheme to achieve both data privacy and authenticity for smart contract. We implement zk-AuthFeed and conduct comprehensive experiments on Ethereum. The experiments show that zk-AuthFeed is highly efficient: key generation takes about 7 seconds only, proof generation takes less than 2 seconds, and proof verification takes less than 40 ms.
OpenAlex reports 22 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
The emerging blockchain technology, powered by the smart contract functionality, is expected to revolutionize traditional systems by decentralization and autonomy. When the blockchain technology is applied in real-life systems, a smart contract may need to take in sensitive data to execute its code. For example, a decentralized medical insurance smart contract needs access to personal health data. Therefore, it is crucial to guarantee both privacy and authenticity of data sent to the smart contract, so that everyone can verify data without leaking sensitive information. Currently, only few works have tried to achieve privacy and authenticity at the same time. In this work, we first propose zk-DASNARK, a zero-knowledge SNARK scheme for authenticated data. It is designed by combining the zk-SNARK technique with digital signature in an effective way. Based on zk-DASNARK, we design zk-AuthFeed, a zero-knowledge authenticated data feed scheme to achieve both data privacy and authenticity for smart contract. We implement zk-AuthFeed and conduct comprehensive experiments on Ethereum. The experiments show that zk-AuthFeed is highly efficient: key generation takes about 7 seconds only, proof generation takes less than 2 seconds, and proof verification takes less than 40 ms.
Key concepts: Zero-knowledge proof, Smart contract, Computer science, Blockchain, Scheme (mathematics), Key (lock), Computer security, Zero (linguistics)