Verifiable privacy-preserving outsourced frequent itemset mining on vertically partitioned databases

HIGHLIGHTS

  • who: Zhen Zhao et al. from the State Key Laboratory of Integrated Service Networks, Xidian University, Xi`an, China have published the paper: Verifiable Privacy-Preserving Outsourced Frequent Itemset Mining on Vertically Partitioned Databases, in the Journal: Electronics 2023, 12, 1952. of /2023/
  • what: The authors implement the protocol and give a detailed analysis in terms of verification accuracy which shows that the dishonest behaviors of the cloud server can be detected with a probability close to 1 and a sacrifice of only a 1% increase in database size. In this paper, to solve the . . .

     

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