{"title":"MFSSE: Multi-Keyword Fuzzy Ranked Symmetric Searchable Encryption With Pattern Hidden in Mobile Cloud Computing","authors":"Dajiang Chen;Zeyu Liao;Zhidong Xie;Ruidong Chen;Zhen Qin;Mingsheng Cao;Hong-Ning Dai;Kuan Zhang","doi":"10.1109/TCC.2024.3430237","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a novel Multi-keyword Fuzzy Symmetric Searchable Encryption (SSE) with patterns hidden, namely MFSSE. In MFSSE, the search trapdoor can be modified differently each time even if the keywords are the same when performing multi-keyword search to prevent the leakage of search patterns. Moreover, MFSSE modifies the search trapdoor by introducing random false negative and false positive errors to resist access pattern leakage. Furthermore, MFSSE utilizes efficient cryptographic algorithms (e.g., Locality-Sensitive Hashing) and lightweight operations (such as, integer addition, matrix multiplication, etc.) to minimize computational and communication, and storage overheads on mobile devices while meeting security and functional requirements. Specifically, its query process requires only a single round of communication, in which, the communication cost is linearly related to the number of the documents in the database, and is independent of the total number of keywords and the number of queried keywords; its computational complexity for matching a document is \n<inline-formula><tex-math>$O(1)$</tex-math></inline-formula>\n; and it requires only a small amount of fixed local storage (i.e., secret key) to be suitable for mobile scenarios. The experimental results demonstrate that MFSSE can prevent the leakage of access patterns and search patterns, while keeping a low communication and computation overheads.","PeriodicalId":13202,"journal":{"name":"IEEE Transactions on Cloud Computing","volume":"12 4","pages":"1042-1057"},"PeriodicalIF":5.3000,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Cloud Computing","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10605603/","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, we propose a novel Multi-keyword Fuzzy Symmetric Searchable Encryption (SSE) with patterns hidden, namely MFSSE. In MFSSE, the search trapdoor can be modified differently each time even if the keywords are the same when performing multi-keyword search to prevent the leakage of search patterns. Moreover, MFSSE modifies the search trapdoor by introducing random false negative and false positive errors to resist access pattern leakage. Furthermore, MFSSE utilizes efficient cryptographic algorithms (e.g., Locality-Sensitive Hashing) and lightweight operations (such as, integer addition, matrix multiplication, etc.) to minimize computational and communication, and storage overheads on mobile devices while meeting security and functional requirements. Specifically, its query process requires only a single round of communication, in which, the communication cost is linearly related to the number of the documents in the database, and is independent of the total number of keywords and the number of queried keywords; its computational complexity for matching a document is
$O(1)$
; and it requires only a small amount of fixed local storage (i.e., secret key) to be suitable for mobile scenarios. The experimental results demonstrate that MFSSE can prevent the leakage of access patterns and search patterns, while keeping a low communication and computation overheads.
期刊介绍:
The IEEE Transactions on Cloud Computing (TCC) is dedicated to the multidisciplinary field of cloud computing. It is committed to the publication of articles that present innovative research ideas, application results, and case studies in cloud computing, focusing on key technical issues related to theory, algorithms, systems, applications, and performance.