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» Privacy preserving mining of association rules
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KDD
2004
ACM
160views Data Mining» more  KDD 2004»
14 years 7 months ago
k-TTP: a new privacy model for large-scale distributed environments
Secure multiparty computation allows parties to jointly compute a function of their private inputs without revealing anything but the output. Theoretical results [2] provide a gen...
Bobi Gilburd, Assaf Schuster, Ran Wolff
ICDM
2005
IEEE
139views Data Mining» more  ICDM 2005»
14 years 18 days ago
Approximate Inverse Frequent Itemset Mining: Privacy, Complexity, and Approximation
In order to generate synthetic basket data sets for better benchmark testing, it is important to integrate characteristics from real-life databases into the synthetic basket data ...
Yongge Wang, Xintao Wu
FC
2009
Springer
150views Cryptology» more  FC 2009»
14 years 1 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
ISI
2005
Springer
14 years 15 days ago
Link Analysis Tools for Intelligence and Counterterrorism
Association rule mining is an important data analysis tool that can be applied with success to a variety of domains. However, most association rule mining algorithms seek to discov...
Antonio Badia, Mehmed M. Kantardzic
VLDB
2008
ACM
147views Database» more  VLDB 2008»
14 years 7 months ago
Providing k-anonymity in data mining
In this paper we present extended definitions of k-anonymity and use them to prove that a given data mining model does not violate the k-anonymity of the individuals represented in...
Arik Friedman, Ran Wolff, Assaf Schuster