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ICDM
2009
IEEE
172views Data Mining» more  ICDM 2009»
14 years 4 months ago
Fine-Grain Perturbation for Privacy Preserving Data Publishing
— Recent work [12] shows that conventional privacy preserving publishing techniques based on anonymity-groups are susceptible to corruption attacks. In a corruption attack, if th...
Rhonda Chaytor, Ke Wang, Patricia Brantingham
NCA
2011
IEEE
13 years 5 months ago
Privacy preserving Back-propagation neural network learning over arbitrarily partitioned data
—Neural Networks have been an active research area for decades. However, privacy bothers many when the training dataset for the neural networks is distributed between two parties...
Ankur Bansal, Tingting Chen, Sheng Zhong
SIGMOD
2012
ACM
220views Database» more  SIGMOD 2012»
12 years 13 days ago
GUPT: privacy preserving data analysis made easy
It is often highly valuable for organizations to have their data analyzed by external agents. However, any program that computes on potentially sensitive data risks leaking inform...
Prashanth Mohan, Abhradeep Thakurta, Elaine Shi, D...
FC
2009
Springer
150views Cryptology» more  FC 2009»
14 years 4 months ago
Privacy-Preserving Information Markets for Computing Statistical Data
Abstract. Consider an “information market” where private and potentially sensitive data are collected, treated as commodity and processed into aggregated information with comme...
Aggelos Kiayias, Bülent Yener, Moti Yung
ICDE
2008
IEEE
157views Database» more  ICDE 2008»
14 years 11 months ago
OptRR: Optimizing Randomized Response Schemes for Privacy-Preserving Data Mining
The randomized response (RR) technique is a promising technique to disguise private categorical data in Privacy-Preserving Data Mining (PPDM). Although a number of RR-based methods...
Zhengli Huang, Wenliang Du