{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T03:59:09Z","timestamp":1760241549923,"version":"build-2065373602"},"reference-count":24,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2018,5,1]],"date-time":"2018-05-01T00:00:00Z","timestamp":1525132800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Future Internet"],"abstract":"<jats:p>To enhance the efficiency of data searching, most data owners store their data files in different cloud servers in the form of cipher-text. Thus, efficient search using fuzzy keywords becomes a critical issue in such a cloud computing environment. This paper proposes a method that aims at improving the efficiency of cipher-text retrieval and lowering storage overhead for fuzzy keyword search. In contrast to traditional approaches, the proposed method can reduce the complexity of Min-Hash-based fuzzy keyword search by using Min-Hash fingerprints to avoid the need to construct the fuzzy keyword set. The method will utilize Jaccard similarity to rank the results of retrieval, thus reducing the amount of calculation for similarity and saving a lot of time and space overhead. The method will also take consideration of multiple user queries through re-encryption technology and update user permissions dynamically. Security analysis demonstrates that the method can provide better privacy preservation and experimental results show that efficiency of cipher-text using the proposed method can improve the retrieval time and lower storage overhead as well.<\/jats:p>","DOI":"10.3390\/fi10050038","type":"journal-article","created":{"date-parts":[[2018,5,3]],"date-time":"2018-05-03T03:20:27Z","timestamp":1525317627000},"page":"38","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["MinHash-Based Fuzzy Keyword Search of Encrypted Data across Multiple Cloud Servers"],"prefix":"10.3390","volume":"10","author":[{"given":"Jingsha","family":"He","sequence":"first","affiliation":[{"name":"Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7136-8492","authenticated-orcid":false,"given":"Jianan","family":"Wu","sequence":"additional","affiliation":[{"name":"Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China"}]},{"given":"Nafei","family":"Zhu","sequence":"additional","affiliation":[{"name":"Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0210-3121","authenticated-orcid":false,"given":"Muhammad Salman","family":"Pathan","sequence":"additional","affiliation":[{"name":"Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China"}]}],"member":"1968","published-online":{"date-parts":[[2018,5,1]]},"reference":[{"key":"ref_1","unstructured":"Song, D.X., Wagner, D., and Perrig, A. (2000, January 14\u201317). Practical techniques for searches on encrypted data. Proceedings of the IEEE Symposium on Security and Privacy, Berkeley, CA, USA."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Chang, Y.C., and Mitzenmacher, M. (2005, January 7\u201310). Privacy preserving keyword search on remote encrypted data. Proceedings of the International Conference on Applied Cryptography and Network Security, New York, NY, USA.","DOI":"10.1007\/11496137_30"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1467","DOI":"10.1109\/TPDS.2011.282","article-title":"Enabling secure and efficient ranked keyword search over outsourced cloud data","volume":"23","author":"Wang","year":"2012","journal-title":"IEEE Trans. Parallel Distrib. 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