@inproceedings{86cb3de45dd3443b9515559a1ad30ea2,
title = "AuthQX: Enabling Authenticated Query over Blockchain via Intel SGX",
abstract = "With the popularization of blockchain technology in traditional industries, though the desire for supporting various authenticated queries becomes more urgent, current blockchain platforms cannot offer sufficient means of achieving authenticated query for light clients, because Authenticated Data Structure (ADS) suffers from performance issues and state-of-the-art Trust Execution Environment (TEE) cannot deal with large-scale applications conveniently due to limited secure memory. In this study, we present a new query authentication scheme, named AuthQX, leveraging the commonly available trusted environment of Intel SGX. AuthQX organizes data hierarchically in trusted SGX enclave and untrusted memory to implement authenticated query cheaply.",
keywords = "Authenticated query, Blockchain, Intel SGX, MB-tree",
author = "Shuaifeng Pang and Qifeng Shao and Zhao Zhang and Cheqing Jin",
note = "Publisher Copyright: {\textcopyright} 2020, Springer Nature Switzerland AG.; 25th International Conference on Database Systems for Advanced Applications, DASFAA 2020 ; Conference date: 24-09-2020 Through 27-09-2020",
year = "2020",
doi = "10.1007/978-3-030-59419-0\_45",
language = "英语",
isbn = "9783030594183",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "727--731",
editor = "Yunmook Nah and Bin Cui and Sang-Won Lee and Yu, \{Jeffrey Xu\} and Yang-Sae Moon and Whang, \{Steven Euijong\}",
booktitle = "Database Systems for Advanced Applications - 25th International Conference, DASFAA 2020, Proceedings",
address = "德国",
}