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Experts can create precise queries due to their prior knowledge, while non-experts struggle with specific terms and concepts, making their queries less precise. Cloud infrastructure offers a practical and scalable platform for data owners to upload their data, making it accessible to intended data users. However, the contemporary single-owner\/single-user (S\/S) approach to DLSS schemes falls short of effectively leveraging the inherent multi-user capabilities of cloud infrastructure. Furthermore, most of these schemes delegate the dissemination of secret keys to a single trust point within the mutual distrust scenario in cloud infrastructure. This paper proposes a Secure Semantic Search using Deep Learning in a Blockchain-Assisted Multi-User Setting <jats:inline-formula><jats:alternatives><jats:tex-math>$$(S^3DBMS)$$<\/jats:tex-math><mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\">\n                  <mml:mrow>\n                    <mml:mo>(<\/mml:mo>\n                    <mml:msup>\n                      <mml:mi>S<\/mml:mi>\n                      <mml:mn>3<\/mml:mn>\n                    <\/mml:msup>\n                    <mml:mi>D<\/mml:mi>\n                    <mml:mi>B<\/mml:mi>\n                    <mml:mi>M<\/mml:mi>\n                    <mml:mi>S<\/mml:mi>\n                    <mml:mo>)<\/mml:mo>\n                  <\/mml:mrow>\n                <\/mml:math><\/jats:alternatives><\/jats:inline-formula>. Specifically, the seamless integration of attribute-based encryption with transfer learning allows the construction of DLSS in multi-owner\/multi-user (M\/M) settings. Further, blockchain\u2019s smart contract mechanism allows a multi-attribute authority consensus-based generation of user private keys and system-wide global parameters in a mutual distrust M\/M scenario. Finally, our scheme achieves privacy requirements and offers improved security and accuracy.<\/jats:p>","DOI":"10.1186\/s13677-023-00578-5","type":"journal-article","created":{"date-parts":[[2024,1,30]],"date-time":"2024-01-30T10:03:07Z","timestamp":1706608987000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Secure semantic search using deep learning in a blockchain-assisted multi-user setting"],"prefix":"10.1186","volume":"13","author":[{"given":"Shahzad","family":"Khan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haider","family":"Abbas","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Muhammad","family":"Binsawad","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,1,30]]},"reference":[{"issue":"3","key":"578_CR1","first-page":"9","volume":"8","author":"X Sun","year":"2014","unstructured":"Sun X, Zhu Y, Xia Z, Chen L (2014) Privacy-preserving keyword-based semantic search over encrypted cloud data. 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