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In light of various detrimental leakage patterns, this paper starts with an investigation into which specific leakage patterns require our focus in the contexts of key-value, range-query, and dynamic workloads, respectively. Subsequently, we introduce new security notions tailored to the specific privacy requirements of these workloads. Accordingly, we propose and instantiate Swat, an efficient construction that progressively enables these workloads, while provably mitigating system-wide leakage via a suite of algorithms with tunable privacy-efficiency trade-offs. We conducted extensive experiments and compiled a detailed result analysis, showing the efficiency of our solution. Swat is about an order of magnitude slower than an encryption-only data store that reveals various leakage patterns and is two orders of magnitude faster than a trivial zero-leakage solution. Meanwhile, the performance of Swat remains highly competitive compared to other designs that mitigate specific types of leakage.<\/jats:p>","DOI":"10.14778\/3675034.3675038","type":"journal-article","created":{"date-parts":[[2024,8,6]],"date-time":"2024-08-06T22:19:11Z","timestamp":1722982751000},"page":"2445-2458","update-policy":"http:\/\/dx.doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["SWAT: A System-Wide Approach to Tunable Leakage Mitigation in Encrypted Data Stores"],"prefix":"10.14778","volume":"17","author":[{"given":"Leqian","family":"Zheng","sequence":"first","affiliation":[{"name":"City University of Hong Kong"}]},{"given":"Lei","family":"Xu","sequence":"additional","affiliation":[{"name":"Nanjing University of Science and Technology"}]},{"given":"Cong","family":"Wang","sequence":"additional","affiliation":[{"name":"City University of Hong Kong"}]},{"given":"Sheng","family":"Wang","sequence":"additional","affiliation":[{"name":"Alibaba Group"}]},{"given":"Yuke","family":"Hu","sequence":"additional","affiliation":[{"name":"Zhejiang University, The State Key Laboratory of Blockchain and Data Security"}]},{"given":"Zhan","family":"Qin","sequence":"additional","affiliation":[{"name":"Zhejiang University, The State Key Laboratory of Blockchain and Data Security"}]},{"given":"Feifei","family":"Li","sequence":"additional","affiliation":[{"name":"Alibaba Group"}]},{"given":"Kui","family":"Ren","sequence":"additional","affiliation":[{"name":"Zhejiang University, The State Key Laboratory of Blockchain and Data Security"}]}],"member":"320","published-online":{"date-parts":[[2024,8,6]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"Proc. of PETs","author":"Amjad Ghous","year":"2023","unstructured":"Ghous Amjad, Sarvar Patel, Giuseppe Persiano, Kevin Yeo, and Moti Yung. 2023. 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