A Chaos-based Multiplicative Perturbation Scheme for Privacy Preserving Data Mining

被引：0

作者：

Luo, Zhifeng ^{[1
]}

Wen, Congmin ^{[1
]}

机构：

[1] S China Univ Technol, Sch Elect & Informat Engn, Guangzhou 510641, Guangdong, Peoples R China

来源：

2014 5TH IEEE INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING AND SERVICE SCIENCE (ICSESS) | 2014年

关键词：

privacy preserving data mining; multiplicative perturbation; logistic map; K-ANONYMITY;

D O I：

暂无

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

The multiplicative perturbation is a popular scheme for privacy preserving data mining. It transforms the original data with the projection matrix. The security of projection matrix is a main concern in the multiplicative perturbation scheme. In this paper, we propose a novel multiplicative perturbation scheme which has a large key space. And we utilize the special property of chaotic systems, i.e., sensitivity to the initial condition and parameter, to design a new projection matrix generation algorithm. The experiment results show that the proposed scheme can preserve the privacy and maintain the utility for data miming.

引用

页码：941 / 944

页数：4

共 11 条

[1]

Agrawal R, 2000, SIGMOD REC, V29, P439, DOI 10.1145/335191.335438

[2] Generation of quasi-normal variables using chaotic maps [J].

Flores, BC ;

Verdin, B ;

Thomas, G ;

Ashtari, A .

Radar Sensor Technology 1X, 2005, 5788 :108-115

[3] Privacy-preserving data publishing for cluster analysis [J].

Fung, Benjamin C. M. ;

Wang, Ke ;

Wang, Lingyu ;

Hung, Patrick C. K. .

DATA & KNOWLEDGE ENGINEERING, 2009, 68 (06) :552-575

[4]

Kargupta H, 2003, THIRD IEEE INTERNATIONAL CONFERENCE ON DATA MINING, PROCEEDINGS, P99

[5]

Lindenstrauss W. J. J., 1984, Contemp. Math, V26, P189

[6] Random projection-based multiplicative data perturbation for privacy preserving distributed data mining [J].

Liu, K ;

Kargupta, H ;

Ryan, J .

IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2006, 18 (01) :92-106

[7]

Pinkas Pinkas B. B., KDD Explorations, V4 4, P12, DOI DOI 10.1145/772862.772865

[8]

Sang YP, 2009, LECT NOTES ARTIF INT, V5782, P334, DOI 10.1007/978-3-642-04174-7_22

[9] k-anonymity:: A model for protecting privacy [J].

Sweeney, L .

INTERNATIONAL JOURNAL OF UNCERTAINTY FUZZINESS AND KNOWLEDGE-BASED SYSTEMS, 2002, 10 (05) :557-570

[10]

Vlad A, 2009, LECT NOTES COMPUT SC, V5593, P703, DOI 10.1007/978-3-642-02457-3_59

← 1 2 →