Localized differential privacy protection frequent item set mining method based on frequent pattern tree

[0095] Such as figure 1 As shown, in this embodiment, a localized differential privacy-protected frequent itemset mining method based on frequent pattern trees is applied to an untrustworthy third-party data aggregator A, n users U, and privacy records V. In the scenario, the i-th user u i The privacy record of v i ,and I represents the set of known privacy items, denoted as I={x 1 ,x 2 ,...,x d ,...,x D}, x d Indicates the dth private item, 1≤i≤n, 1≤d≤D, D is the total number of private data; the frequent itemset mining method includes the following steps:

[0096] S1. Initialization phase:

[0097] Assuming that the frequent itemset mining method is applied to a shopping mall to mine the collection of frequently purchased commodities by users, and the user's transaction records are private and unknown to the mall; given the support count threshold σ, the frequent itemsets of n user privacy transaction records Mining, you will get all the commodity sets with occurre...