View in EDS HTML Full Text PDF Full Text

Encrypted Search Method for Cloud Computing Data Under Attack Based on TF-IDF and Apriori Algorithm.

Saved in:
Bibliographic Details
Title: Encrypted Search Method for Cloud Computing Data Under Attack Based on TF-IDF and Apriori Algorithm.
Authors: Mao, Demei1 (AUTHOR), Wang, Mingzhu2 (AUTHOR) wangmingz1216@163.com
Source: Applied Artificial Intelligence. Dec2025, Vol. 39 Issue 1, p1-22. 22p.
Subjects: Apriori algorithm, Data security, Cloud computing, Data integrity, Information retrieval, Feature extraction, Data structures
Abstract: This paper designs the MKSE and SEMSS methods. Among them, MKSE uses an improved TF-IDF weight calculation method to extract keywords and applies virtual keywords to construct inverted indexes, making it difficult for malicious attackers to infer the index content easily. SEMSS uses the Apriori algorithm to mine the co-occurrence relationship between words and find the keyword set that meets the minimum support threshold to improve the recall rate of search results. Finally, the security of the scheme is verified from the aspects of semantic security, effici this paper designsency, data integrity, etc. The results showed that the data encryption time of MKSE and TRSE methods increased gradually with the increase in document collection storage. The index build time was increased as the document set grew. The accuracy of the improved TF-IDF method was 63.8%. The running time of Apriori decreased with the increase of minimum support. When the minimum support was 12.0%, the Apriori algorithm ran for 211 seconds. The MKSE method was more efficient than the TRSE method in searching documents by query keywords. When the document set size was 3000, the SEMSS method had a full search rate of 81.09%. This research realizes the semantic security of outsourced data, which can efficiently and comprehensively carry out cryptographic retrieval based on keyword sorting. [ABSTRACT FROM AUTHOR]
Copyright of Applied Artificial Intelligence is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
Text:
  Availability: 1
Header DbId: egs
DbLabel: Engineering Source
An: 189934059
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Encrypted Search Method for Cloud Computing Data Under Attack Based on TF-IDF and Apriori Algorithm.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Mao%2C+Demei%22">Mao, Demei</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wang%2C+Mingzhu%22">Wang, Mingzhu</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> wangmingz1216@163.com</i>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Applied+Artificial+Intelligence%22">Applied Artificial Intelligence</searchLink>. Dec2025, Vol. 39 Issue 1, p1-22. 22p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Apriori+algorithm%22">Apriori algorithm</searchLink><br /><searchLink fieldCode="DE" term="%22Data+security%22">Data security</searchLink><br /><searchLink fieldCode="DE" term="%22Cloud+computing%22">Cloud computing</searchLink><br /><searchLink fieldCode="DE" term="%22Data+integrity%22">Data integrity</searchLink><br /><searchLink fieldCode="DE" term="%22Information+retrieval%22">Information retrieval</searchLink><br /><searchLink fieldCode="DE" term="%22Feature+extraction%22">Feature extraction</searchLink><br /><searchLink fieldCode="DE" term="%22Data+structures%22">Data structures</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: This paper designs the MKSE and SEMSS methods. Among them, MKSE uses an improved TF-IDF weight calculation method to extract keywords and applies virtual keywords to construct inverted indexes, making it difficult for malicious attackers to infer the index content easily. SEMSS uses the Apriori algorithm to mine the co-occurrence relationship between words and find the keyword set that meets the minimum support threshold to improve the recall rate of search results. Finally, the security of the scheme is verified from the aspects of semantic security, effici this paper designsency, data integrity, etc. The results showed that the data encryption time of MKSE and TRSE methods increased gradually with the increase in document collection storage. The index build time was increased as the document set grew. The accuracy of the improved TF-IDF method was 63.8%. The running time of Apriori decreased with the increase of minimum support. When the minimum support was 12.0%, the Apriori algorithm ran for 211 seconds. The MKSE method was more efficient than the TRSE method in searching documents by query keywords. When the document set size was 3000, the SEMSS method had a full search rate of 81.09%. This research realizes the semantic security of outsourced data, which can efficiently and comprehensively carry out cryptographic retrieval based on keyword sorting. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Applied Artificial Intelligence is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=189934059
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1080/08839514.2024.2449303
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 22
        StartPage: 1
    Subjects:
      – SubjectFull: Apriori algorithm
        Type: general
      – SubjectFull: Data security
        Type: general
      – SubjectFull: Cloud computing
        Type: general
      – SubjectFull: Data integrity
        Type: general
      – SubjectFull: Information retrieval
        Type: general
      – SubjectFull: Feature extraction
        Type: general
      – SubjectFull: Data structures
        Type: general
    Titles:
      – TitleFull: Encrypted Search Method for Cloud Computing Data Under Attack Based on TF-IDF and Apriori Algorithm.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Mao, Demei
      – PersonEntity:
          Name:
            NameFull: Wang, Mingzhu
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 12
              Text: Dec2025
              Type: published
              Y: 2025
          Identifiers:
            – Type: issn-print
              Value: 08839514
          Numbering:
            – Type: volume
              Value: 39
            – Type: issue
              Value: 1
          Titles:
            – TitleFull: Applied Artificial Intelligence
              Type: main
ResultId 1