QShield: Protecting Outsourced Cloud Data Queries with Multi-User Access Control Based on SGX

Yaxing Chen*, Qinghua Zheng, Zheng Yan, Dan Liu

*Corresponding author for this work

    Research output: Contribution to journalArticleScientificpeer-review

    28 Citations (Scopus)
    421 Downloads (Pure)

    Abstract

    Due to the concern on cloud security, digital encryption is applied before outsourcing data to the cloud for utilization. This introduces a challenge about how to efficiently perform queries over ciphertexts. Crypto-based solutions currently suffer from limited operation support, high computational complexity, weak generality, and poor verifiability. An alternative method that utilizes hardware-assisted Trusted Execution Environment (TEE), i.e., Intel SGX, has emerged to offer high computational efficiency, generality and flexibility. However, SGX-based solutions lack support on multi-user query control and suffer from security compromises caused by untrustworthy TEE function invocation, e.g., key revocation failure, incorrect query results, and sensitive information leakage. In this article, we leverage SGX and propose a secure and efficient SQL-style query framework named QShield. Notably, we propose a novel lightweight secret sharing scheme in QShield to enable multi-user query control; it effectively circumvents key revocation and avoids cumbersome remote attestation for authentication. We further embed a trust-proof mechanism into QShield to guarantee the trustworthiness of TEE function invocation; it ensures the correctness of query results and alleviates side-channel attacks. Through formal security analysis, proof-of-concept implementation and performance evaluation, we show that QShield can securely query over outsourced data with high efficiency and scalable multi-user support.

    Original languageEnglish
    Article number9200772
    Pages (from-to)485-499
    Number of pages15
    JournalIEEE Transactions on Parallel and Distributed Systems
    Volume32
    Issue number2
    DOIs
    Publication statusPublished - 1 Feb 2021
    MoE publication typeA1 Journal article-refereed

    Funding

    The authors would like to thank Wen-hai Sun, Ning Zhang, and Xue-qin Liang for their insightful comments on the manuscript. They would also like to thank Wen-jing Lou for her constructive suggestions and kind comments on this research topic. This work was sponsored by National Key Research and Development Program of China under Grant Nos. 2018YFB1004500, 2016YFB1000903, Innovative Research Group of the National Natural Science Foundation of China (61721002), Innovation Research Team of Ministry of Education (IRT_17R86), the National Science Foundation of China under Grant Nos. 61502379, 61532015, 61672410, and 61672420, Project of China Knowledge Center for Engineering Science and Technology. This work was also supported in part by the Academy of Finland under Grants 308087 and 314203.

    Keywords

    • cloud computing
    • Intel SGX
    • multi-user query control
    • outsourced data
    • secure hardware
    • Secure query

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