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Stargazing in the Dark: Secure Skyline Queries with SGX

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Database Systems for Advanced Applications (DASFAA 2020)

Abstract

Skylining for multi-criteria decision making is widely applicable and often involves sensitive data that should be encrypted, especially when the database and query engine are outsourced to an untrusted cloud platform. The state-of-the-art designs (ICDE’17) of skylining over encrypted data, while relying on two non-colluding servers, are still slow – taking around three hours to get the skyline for 9000 2-D points.

This paper proposes a very efficient solution with a trusted processor such as SGX. A challenge is to support dynamic queries while keeping the memory footprint small and simultaneously preventing unintended leakage with only lightweight cryptographic primitives. Our proposed approach iteratively loads data to the memory-limited SGX on-demand and builds a binary-tree-like index for logarithmic query time. For millions of points, we gain \({6000} - {28000}\times \) improvement in query time (ICDE’17).

The first two authors contributed equally and share the “co-first author” status. Sherman S. M. Chow is supported by General Research Funds (CUHK 14209918 and 14210217) of the Research Grants Council, UGC, Hong Kong. The authors would like to thank Shuaike Dong and Di Tang for their advice on the experiments, and the anonymous reviewers for their suggestions and comments.

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Notes

  1. 1.

    We remark that the assumption of two non-colluding servers and the usage of AHE enables both addition and multiplication over encrypted data  [19].

  2. 2.

    Two other works  [17, 22] also use AHE over distributed encrypted datasets (cf.  computing on data encrypted under multiple keys  [19]), but only for static skyline.

  3. 3.

    We do not exploit multi-dimensional tree structures, such as R-tree, kd-tree, or their variants, since they will leak the distribution of the entire database before querying.

  4. 4.

    Associated files are encrypted under another SKE key, generated by the data owner and shared with authorized users. The server (or SGX) cannot decrypt these files.

  5. 5.

    Due to the page limit, we defer proof of Theorem 1 to the full version of this paper.

  6. 6.

    CLBP: https://archive.ics.uci.edu/ml/datasets.php, EMR: http://www.emrbots.org.

  7. 7.

    The extended version of  [16] studies optimizations of BSSP and FSSP, which discusses the influence of parameters separately rather than providing a complete optimized scheme. We thus focus on the comparisons with regular BSSP and FSSP.

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Correspondence to Sherman S. M. Chow .

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Wang, J., Du, M., Chow, S.S.M. (2020). Stargazing in the Dark: Secure Skyline Queries with SGX. In: Nah, Y., Cui, B., Lee, SW., Yu, J.X., Moon, YS., Whang, S.E. (eds) Database Systems for Advanced Applications. DASFAA 2020. Lecture Notes in Computer Science(), vol 12114. Springer, Cham. https://doi.org/10.1007/978-3-030-59419-0_20

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  • DOI: https://doi.org/10.1007/978-3-030-59419-0_20

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