Privacy protection frequent item set mining method for large-scale shopping mall transaction record

Abstract

The invention provides a privacy protection frequent item set mining method for a large-scale shopping mall transaction record, so as to solve the technical problem of a large amount of calculation during a frequent item set mining process under a high privacy protection level existing in the prior art. The method comprises steps: an evaluator acquires a public-private key pair, and any user generates a shared key; each user sends an encrypted transaction record to a cloud service provider, and a miner sends an encrypted mining query, a ciphertext with a goods number existing in the mining query and a support threshold ciphertext to the cloud service provider; and the cloud service provider acquires an encrypted false transaction record; and the cloud service and the evaluator interact tojudge whether the mining query is a frequent item set. The mining frequency is high.

Description

technical field [0001] The invention belongs to the technical field of information security, and in particular relates to a privacy-protected frequent item set mining method for transaction records of large shopping malls. Background technique [0002] With the rise of cloud services, many users choose to store their data on cloud servers in order to save storage space. Therefore, cloud servers have a large amount of data, and there may be some hidden relationship between some of the data. Relationships can be used for market forecasting, intrusion detection, and network traffic management, among others. In order to reveal this hidden relationship, data mining techniques have emerged. Association rule mining is an important method in data mining, and frequent item set mining is the basic step of association rule mining. Therefore, frequent item set mining is very important. In the process of mining frequent itemsets of transaction records in large shopping malls, a semi-ho...

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to overcome the above-mentioned defects in the prior art, and propose a privacy-protected frequent item set mining method for large-scale shopping mall transaction records, which is used to solve the problem of mining frequent items under high privacy protection levels in the prior art. The technical problem of large amount of calculation in the process of set

Images