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Creators/Authors contains: "Qiao, Yifan"

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  1. ; ; ; ; ( , Information Retrieval Journal)
    Abstract

    Previous work on privacy-aware ranking has addressed the minimization of information leakage when scoring topkdocuments, and has not studied on how to retrieve these top documents and their features for ranking. This paper proposes a privacy-aware document retrieval scheme with a two-level inverted index structure. In this scheme, posting records are grouped with bucket tags and runtime query processing produces query-specific tags in order to gather encoded features of matched documents with a privacy protection during index traversal. To thwart leakage-abuse attacks, our design minimizes the chance that a server processes unauthorized queries or identifies document sharing across posting lists through index inspection or across-query association. This paper presents the evaluation and analytic results of the proposed scheme to demonstrate the tradeoffs in its design considerations for privacy, efficiency, and relevance.

     
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  2. ; ; ; ( , Proc. of ACM SIGIR conference on Research and Development in Information Retrieval (SIGIR 2023))
    Free, publicly-accessible full text available July 18, 2024
  3. ; ; ; ; ( , Proc. of the 9th ACM SIGIR/Th13th International Conference on the Theory of Information Retrieval (ICTIR 2023))
    Free, publicly-accessible full text available July 23, 2024
  4. ; ; ; ( , Proc. of the ACM Web Conference 2023 (WWW ’23))
    Free, publicly-accessible full text available April 30, 2024
  5. ; ; ; ; ; ; ; ( , 20th USENIX Symposium on Networked Systems Design and Implementation)
    Accepted Manuscript Full Text Available
  6. ; ; ; ; ; ; ; ( , 20th USENIX Symposium on Networked Systems Design and Implementation)
    Accepted Manuscript Full Text Available
  7. ; ; ; ; ; ; ; ( , 20th USENIX Symposium on Networked Systems Design and Implementation)
    Accepted Manuscript Full Text Available
  8. ; ; ; ; ; ; ; ( , NSDI)
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  10. ; ; ; ; ; ; ; ; ( , NSDI)