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TSMC
2011
228views more  TSMC 2011»
14 years 4 months ago
Privacy-Preserving Outlier Detection Through Random Nonlinear Data Distortion
— Consider a scenario in which the data owner has some private/sensitive data and wants a data miner to access it for studying important patterns without revealing the sensitive ...
Kanishka Bhaduri, Mark D. Stefanski, Ashok N. Sriv...
ADC
2007
Springer
145views Database» more  ADC 2007»
15 years 4 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
ACSAC
2005
IEEE
15 years 3 months ago
Privacy-Preserving Alert Correlation: A Concept Hierarchy Based Approach
With the increasing security threats from infrastructure attacks such as worms and distributed denial of service attacks, it is clear that the cooperation among different organiza...
Dingbang Xu, Peng Ning
ADMA
2006
Springer
137views Data Mining» more  ADMA 2006»
15 years 1 months ago
SA-IFIM: Incrementally Mining Frequent Itemsets in Update Distorted Databases
Abstract. The issue of maintaining privacy in frequent itemset mining has attracted considerable attentions. In most of those works, only distorted data are available which may bri...
Jinlong Wang, Congfu Xu, Hongwei Dan, Yunhe Pan
COMPSAC
2004
IEEE
15 years 1 months ago
Hiding Sensitive Patterns in Association Rules Mining
Data mining techniques have been developed in many applications. However, it also causes a threat to privacy. We investigate to find an appropriate balance between a need for priv...
Guanling Lee, Chien-Yu Chang, Arbee L. P. Chen