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KDD
2007
ACM
152views Data Mining» more  KDD 2007»
15 years 9 months ago
Privacy-Preserving Sharing of Horizontally-Distributed Private Data for Constructing Accurate Classifiers
Data mining tasks such as supervised classification can often benefit from a large training dataset. However, in many application domains, privacy concerns can hinder the construc...
Vincent Yan Fu Tan, See-Kiong Ng
ICDE
2009
IEEE
132views Database» more  ICDE 2009»
15 years 11 months ago
Using Anonymized Data for Classification
In recent years, anonymization methods have emerged as an important tool to preserve individual privacy when releasing privacy sensitive data sets. This interest in anonymization t...
Ali Inan, Murat Kantarcioglu, Elisa Bertino
JCP
2007
148views more  JCP 2007»
14 years 9 months ago
P3ARM-t: Privacy-Preserving Protocol for Association Rule Mining with t Collusion Resistance
— The ability to mine large volumes of distributed datasets enables more precise decision making. However, privacy concerns should be carefully addressed when mining datasets dis...
Iman Saleh, Mohamed Eltoweissy
KES
2008
Springer
14 years 9 months ago
Privacy Risks in Trajectory Data Publishing: Reconstructing Private Trajectories from Continuous Properties
Abstract. Location and time information about individuals can be captured through GPS devices, GSM phones, RFID tag readers, and by other similar means. Such data can be pre-proces...
Emre Kaplan, Thomas Brochmann Pedersen, Erkay Sava...
ADC
2007
Springer
145views Database» more  ADC 2007»
15 years 3 months ago
The Privacy of k-NN Retrieval for Horizontal Partitioned Data -- New Methods and Applications
Recently, privacy issues have become important in clustering analysis, especially when data is horizontally partitioned over several parties. Associative queries are the core retr...
Artak Amirbekyan, Vladimir Estivill-Castro