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AEI
2007
91views more  AEI 2007»
13 years 5 months ago
MICF: An effective sanitization algorithm for hiding sensitive patterns on data mining
Data mining mechanisms have widely been applied in various businesses and manufacturing companies across many industry sectors. Sharing data or sharing mined rules has become a tr...
Yu-Chiang Li, Jieh-Shan Yeh, Chin-Chen Chang
COMPSAC
2004
IEEE
13 years 8 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
CIKM
2006
Springer
13 years 8 months ago
An integer programming approach for frequent itemset hiding
The rapid growth of transactional data brought, soon enough, into attention the need of its further exploitation. In this paper, we investigate the problem of securing sensitive k...
Aris Gkoulalas-Divanis, Vassilios S. Verykios
DKE
2008
124views more  DKE 2008»
13 years 4 months ago
A MaxMin approach for hiding frequent itemsets
In this paper, we are proposing a new algorithmic approach for sanitizing raw data from sensitive knowledge in the context of mining of association rules. The new approach (a) rel...
George V. Moustakides, Vassilios S. Verykios
DAWAK
2006
Springer
13 years 8 months ago
Two New Techniques for Hiding Sensitive Itemsets and Their Empirical Evaluation
Many privacy preserving data mining algorithms attempt to selectively hide what database owners consider as sensitive. Specifically, in the association-rules domain, many of these ...
Ahmed HajYasien, Vladimir Estivill-Castro