{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T05:16:25Z","timestamp":1755839785058,"version":"3.32.0"},"reference-count":14,"publisher":"Association for Computing Machinery (ACM)","issue":"12","content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["Proc. VLDB Endow."],"published-print":{"date-parts":[[2024,8]]},"abstract":"<jats:p>Differential privacy (DP) has garnered significant attention from both academia and industry due to its potential in offering robust privacy protection for individual data during analysis. With the increasing volume of sensitive information being collected by organizations and analyzed through SQL queries, the development of a general-purpose query engine that is capable of supporting a broad range of SQLs while maintaining DP has become the holy grail in privacy-preserving query release.<\/jats:p>\n          <jats:p>In this demonstration, we present DOP-SQL, a DP SQL system that can answer a broad class of queries consisting of the selection, projection, aggregation, join, and group by operators. DOP-SQL has integrated a suite of down-neighborhood optimal DP mechanisms, thus achieving state-of-the-art utility. The current implementation of DOP-SQL is based on PostgreSQL, but its extensible feature allows it to be used in conjunction with any standard SQL engine.<\/jats:p>","DOI":"10.14778\/3685800.3685881","type":"journal-article","created":{"date-parts":[[2024,11,8]],"date-time":"2024-11-08T17:25:21Z","timestamp":1731086721000},"page":"4385-4388","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["DOP-SQL: A General-Purpose, High-Utility, and Extensible Private SQL System"],"prefix":"10.14778","volume":"17","author":[{"given":"Jianzhe","family":"Yu","sequence":"first","affiliation":[{"name":"Hong Kong University of Science and Technology"}]},{"given":"Wei","family":"Dong","sequence":"additional","affiliation":[{"name":"Hong Kong University of Science and Technology"}]},{"given":"Juanru","family":"Fang","sequence":"additional","affiliation":[{"name":"Hong Kong University of Science and Technology"}]},{"given":"Dajun","family":"Sun","sequence":"additional","affiliation":[{"name":"Hong Kong University of Science and Technology"}]},{"given":"Ke","family":"Yi","sequence":"additional","affiliation":[{"name":"Hong Kong University of Science and Technology"}]}],"member":"320","published-online":{"date-parts":[[2024,11,8]]},"reference":[{"doi-asserted-by":"publisher","key":"e_1_2_1_1_1","DOI":"10.1145\/3654931"},{"doi-asserted-by":"publisher","key":"e_1_2_1_2_1","DOI":"10.1145\/3514221.3517844"},{"doi-asserted-by":"publisher","key":"e_1_2_1_3_1","DOI":"10.1109\/SP46215.2023.10179466"},{"doi-asserted-by":"publisher","key":"e_1_2_1_4_1","DOI":"10.1145\/3589268"},{"doi-asserted-by":"publisher","key":"e_1_2_1_5_1","DOI":"10.1145\/3448016.3452813"},{"doi-asserted-by":"publisher","key":"e_1_2_1_6_1","DOI":"10.1145\/3584372.3588669"},{"volume-title":"Theory of Cryptography","author":"Dwork Cynthia","unstructured":"Cynthia Dwork, Frank McSherry, Kobbi Nissim, and Adam Smith. 2006. Calibrating Noise to Sensitivity in Private Data Analysis. In Theory of Cryptography, Shai Halevi and Tal Rabin (Eds.). 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