Data Perturbation Methods Implementation Using Matlab

被引:0
作者
Al-Ahmadi, Mohammad Saad [1 ]
机构
[1] King Fahd Univ Petr & Minerals, Dhahran 31261, Saudi Arabia
来源
INNOVATION AND KNOWLEDGE MANAGEMENT: A GLOBAL COMPETITIVE ADVANTAGE, VOLS 1-4 | 2011年
关键词
Statistical Disclosure Limitation (SDL); Perturbation Methods; Privacy Preserving Data Mining; Matlab;
D O I
暂无
中图分类号
F [经济];
学科分类号
02 ;
摘要
One important class of data perturbation methods is the class of additive data perturbation methods for masking sensitive datasets containing linear relationships among their variables. Theses methods try to maintain original linear relationships in masked datasets while preserving data security and privacy. Three important methods under this class are GADP (Muralidhar et al. 1999), IPSO (Burridge 2003) and EGADP (Muralidhar and Sarathy 2005). To facilitate the work in this important area of research, we provide brief discussion of each of the three methods along with their Matlab implementations.
引用
收藏
页码:2170 / 2178
页数:9
相关论文
共 14 条