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Although existing research has attempted to enable such query services for low-dimensional data, such as relational and spatial data, these solutions can be inefficient in answering vector similarity queries involving high-dimensional data. Therefore, we are motivated to develop a new prototype system called FedSQ that (1) ensures privacy protection across data owners and (2) balances query efficiency and result accuracy when processing federated vector similarity queries. To achieve these goals, FedSQ utilizes advanced secure multi-party computation techniques to prevent information leakage during query processing and incorporates indexing and sampling based optimizations to strike a proper performance balance.<\/jats:p>","DOI":"10.14778\/3685800.3685895","type":"journal-article","created":{"date-parts":[[2024,11,8]],"date-time":"2024-11-08T17:25:21Z","timestamp":1731086721000},"page":"4441-4444","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":9,"title":["FedSQ: A Secure System for Federated Vector Similarity Queries"],"prefix":"10.14778","volume":"17","author":[{"given":"Zeqi","family":"Zhu","sequence":"first","affiliation":[{"name":"SKLCCSE Lab, Beihang University"}]},{"given":"Zeheng","family":"Fan","sequence":"additional","affiliation":[{"name":"SKLCCSE Lab, Beihang University"}]},{"given":"Yuxiang","family":"Zeng","sequence":"additional","affiliation":[{"name":"SKLCCSE Lab, Beihang University"}]},{"given":"Yexuan","family":"Shi","sequence":"additional","affiliation":[{"name":"SKLCCSE Lab, Beihang University"}]},{"given":"Yi","family":"Xu","sequence":"additional","affiliation":[{"name":"SKLCCSE Lab, Beihang University"}]},{"given":"Mengmeng","family":"Zhou","sequence":"additional","affiliation":[{"name":"Beijing Academy of Blockchain and Edge Computing"}]},{"given":"Jin","family":"Dong","sequence":"additional","affiliation":[{"name":"Beijing Academy of Blockchain and Edge Computing"}]}],"member":"320","published-online":{"date-parts":[[2024,11,8]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"2022. 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