Privacy preserving itemset mining through fake transactions

  title={Privacy preserving itemset mining through fake transactions},
  author={Jun-Lin Lin and Julie Yu-Chih Liu},
This work investigates the problem of privacy-preserving mining of association rules. Specifically, a fake transaction randomization method is presented to protect the privacy of data. This method ensures the privacy of data by mixing real transactions with fake transactions. An algorithm for reconstructing frequent itemsets from the mixture of both fake transactions and real transactions is then proposed. The proposed algorithm can use any off-the-shelf tool to mine frequent itemsets without… CONTINUE READING
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