工业数据关联规则挖掘隐私保护研究综述

A Review on Privacy-Preserving Association Rule Mining of Industrial Data

针对工业数据关联规则挖掘隐私保护问题,本文梳理总结了已有研究成果,并分别对云计算环境下工业数据关联规则挖掘安全外包、工业大数据关联规则挖掘隐私保护、多用户协同工业数据关联规则挖掘隐私保护这三种应用场景进行了深入分析探讨,指出现有方案在安全性、高效性和实用性等方面仍存在一定的不足。文章最后探讨了未来解决工业数据挖掘隐私保护问题的研究方向,强调了解决该问题对实现工业4.0时代下工业数据安全具有重要的意义。

To solve the privacy-preserving association rule mining of industrial data,existing research works are summarized.Three different scenarios are carefully discussed,i.e.,the secure outsourcing of association rule mining of industrial data over cloud computing environment,the privacy-preserving association rule mining of big industrial data,and the multi-client collaborative privacy-preserving association rule mining of industrial data.Existing works have some deficiencies on safety,efficiency and practicability.At last,the paper discusses the future research direction of solving the privacy-preserving problem of industrial data mining,emphasizing that solving this problem has great significance to realize the industrial data security in the era of industry 4.0.