{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,29]],"date-time":"2025-10-29T14:38:10Z","timestamp":1761748690757,"version":"build-2065373602"},"reference-count":17,"publisher":"Association for Computing Machinery (ACM)","issue":"3","content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["SIGMOD Rec."],"published-print":{"date-parts":[[2025,10,28]]},"abstract":"<jats:p>Securing analytics on shared data is important but expensive. Analyzing datasets from multiple data owners can yield valuable insights [1, 2, 3, 4, 5] but poses significant security risks. Even within enterprises - our primary focus - precautions are necessary when handling data across subsidiaries and geographic regions [6, 7]. Existing security solutions based on Trusted Execution Environments (TEEs) [8, 9], fully homomorphic encryption [10], and structured encryption [11] offer strong protections, albeit in a physically centralized manner. For more decentralization, there are exciting approaches based on Secure Multi-Party Computation (MPC) [12] that do not need a trusted third party nor merging datasets at a central location. Recent projects [6, 13, 14, 15] show that MPC can reduce the risk of leaks for analytics on shared data under stronger security guarantees. However, MPC queries are often impractically slow, requiring orders of magnitude more computation and communication than plain-text or TEEbased query execution.<\/jats:p>","DOI":"10.1145\/3774303.3774311","type":"journal-article","created":{"date-parts":[[2025,10,29]],"date-time":"2025-10-29T13:49:41Z","timestamp":1761745781000},"page":"31-32","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Navigating the Performance-Security Trade-Off in Future Analytics on Shared Data"],"prefix":"10.1145","volume":"54","author":[{"given":"Zsolt","family":"Istv\u00e1n","sequence":"first","affiliation":[{"name":"Systems Group, TU Darmstadt, Germany"}]}],"member":"320","published-online":{"date-parts":[[2025,10,29]]},"reference":[{"issue":"12","key":"e_1_2_1_1_1","first-page":"1749","article-title":"From keys to databases-real-world applications of secure multi-party computation","volume":"61","author":"Archer D. 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Talviste, \"Students and taxes: a privacy-preserving study using secure computation,\" Proceedings on Privacy Enhancing Technologies, 2016."},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/3133956.3133982"},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/3209811.3212699"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/3615952.3615962"},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.14778\/3685800.3685821"},{"key":"e_1_2_1_7_1","volume-title":"Paper 2025\/463","author":"Becker S.","year":"2025","unstructured":"S. Becker, C. B\u00a8osch, B. Hettwer, T. Hoeren, M. Rombach, S. Trieflinger, and H. Yalame, \"Multi-party computation in corporate data processing: Legal and technical insights.\" Cryptology ePrint Archive, Paper 2025\/463, 2025."},{"key":"e_1_2_1_8_1","first-page":"516","volume-title":"EDBT","author":"Lutsch A.","year":"2025","unstructured":"A. Lutsch, M. El-Hindi, M. Heinrich, D. Ritter, Z. Istv\u00b4an, and C. Binnig, \"Benchmarking analytical query processing in intel sgxv2,\" in Proceedings 28th International Conference on Extending Database Technology, EDBT 2025, Barcelona, Spain, March 25--28, 2025 (A. Simitsis, B. Kemme, A. Queralt, O. Romero, and P. Jovanovic, eds.), pp. 516--528, OpenProceedings.org, 2025."},{"key":"e_1_2_1_9_1","first-page":"1511","volume-title":"Azure sql database always encrypted,\" in Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data","author":"Antonopoulos P.","year":"2020","unstructured":"P. Antonopoulos, A. Arasu, K. D. Singh, K. Eguro, N. Gupta, R. Jain, R. Kaushik, H. Kodavalla, D. Kossmann, N. Ogg, et al., \"Azure sql database always encrypted,\" in Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, pp. 1511--1525, 2020."},{"key":"e_1_2_1_10_1","first-page":"2930","volume-title":"He3db: An efficient and elastic encrypted database via arithmetic-and-logic fully homomorphic encryption,\" in Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security","author":"Bian S.","year":"2023","unstructured":"S. Bian, Z. Zhang, H. Pan, R. Mao, Z. Zhao, Y. Jin, and Z. Guan, \"He3db: An efficient and elastic encrypted database via arithmetic-and-logic fully homomorphic encryption,\" in Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security, pp. 2930--2944, 2023."},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/2043556.2043566"},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1017\/CBO9781107337756"},{"key":"e_1_2_1_13_1","first-page":"1031","volume-title":"SECRECY: Secure collaborative analytics in untrusted clouds,\" in 20th USENIX Symposium on Networked Systems Design and Implementation (NSDI 23)","author":"Liagouris J.","year":"2023","unstructured":"J. Liagouris, V. Kalavri, M. Faisal, and M. Varia, \"SECRECY: Secure collaborative analytics in untrusted clouds,\" in 20th USENIX Symposium on Networked Systems Design and Implementation (NSDI 23), pp. 1031--1056, 2023."},{"key":"e_1_2_1_14_1","volume-title":"Shrinkwrap: efficient sql query processing in differentially private data federations,\" Proceedings of the VLDB Endowment","author":"Bater J.","unstructured":"J. Bater, X. He, W. Ehrich, A. Machanavajjhala, and J. Rogers, \"Shrinkwrap: efficient sql query processing in differentially private data federations,\" Proceedings of the VLDB Endowment, vol. 12, no. 3, 2018."},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.14778\/3407790.3407854"},{"key":"e_1_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.14778\/3594512.3594529"},{"key":"e_1_2_1_17_1","volume-title":"Reflex: Speeding up smpc query execution through efficient and flexible intermediate result size trimming.\" https:\/\/arxiv.org\/abs\/2503.20932","author":"Gu L.","year":"2025","unstructured":"L. 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Istv\u00b4an, \"Reflex: Speeding up smpc query execution through efficient and flexible intermediate result size trimming.\" https:\/\/arxiv.org\/abs\/2503.20932, 2025."}],"container-title":["ACM SIGMOD Record"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3774303.3774311","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,29]],"date-time":"2025-10-29T13:49:54Z","timestamp":1761745794000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3774303.3774311"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,28]]},"references-count":17,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2025,10,28]]}},"alternative-id":["10.1145\/3774303.3774311"],"URL":"https:\/\/doi.org\/10.1145\/3774303.3774311","relation":{},"ISSN":["0163-5808"],"issn-type":[{"value":"0163-5808","type":"print"}],"subject":[],"published":{"date-parts":[[2025,10,28]]},"assertion":[{"value":"2025-10-29","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}