A Survey on Data Mining Privacy Protection Algorithms

doi:10.3969/j.issn.1671-1122.2017.02.002

Abstract

Abstract:

Nowadays the increasing of massive data in various fields has promoted the development of data mining, but the storage and mining of user data brings about threat of privacy leakage, so the user privacy needs to be protected in data mining process. Research on privacy protection data mining algorithms has become an important research area. This article introduces three main privacy protection data mining algorithms, which are perturbation algorithm, k-anonymity algorithm and association rules hiding algorithm. The perturbation algorithms include randomization protection algorithm and multiplicative perturbation algorithm. The two main techniques for k-anonymity are generalization and suppression. The usual association rules hiding algorithms include heuristic algorithm, boundary-based algorithm and precise algorithm. This article introduces and summarizes the new research works for these algorithms, and describes the research trends for privacy protection data mining algorithms.

Key words: data mining, privacy protection, perturbation, k-anonymity, association rules hiding

CLC Number:

TP309

Yuejian FANG, Jinzhong ZHU, Wen ZHOU, Tongliang LI. A Survey on Data Mining Privacy Protection Algorithms[J]. Netinfo Security, 2017, 17(2): 6-11.

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