Data sanitization in association rule mining: An analytical review

作者：

Highlights：

• We present an analytical review of trends and directions in association rule hiding.

• Fifty four sanitization algorithms are collected and summarized.

• We analyze algorithms according to strategy, technique, approach, and method.

• Advantages and disadvantages of each aspect of sanitization process are described.

摘要

•We present an analytical review of trends and directions in association rule hiding.•Fifty four sanitization algorithms are collected and summarized.•We analyze algorithms according to strategy, technique, approach, and method.•Advantages and disadvantages of each aspect of sanitization process are described.

论文关键词：Privacy preserving in data mining,Association rule mining,Association rule hiding,Data sanitization

论文评审过程：Received 20 March 2017, Revised 21 October 2017, Accepted 22 October 2017, Available online 24 October 2017, Version of Record 5 January 2018.

论文官网地址：https://doi.org/10.1016/j.eswa.2017.10.048