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USS
2010
13 years 2 months ago
P4P: Practical Large-Scale Privacy-Preserving Distributed Computation Robust against Malicious Users
In this paper we introduce a framework for privacypreserving distributed computation that is practical for many real-world applications. The framework is called Peers for Privacy ...
Yitao Duan, NetEase Youdao, John Canny, Justin Z. ...
KDD
2002
ACM
214views Data Mining» more  KDD 2002»
14 years 5 months ago
Privacy preserving association rule mining in vertically partitioned data
Privacy considerations often constrain data mining projects. This paper addresses the problem of association rule mining where transactions are distributed across sources. Each si...
Jaideep Vaidya, Chris Clifton
SDMW
2004
Springer
13 years 10 months ago
Experimental Analysis of Privacy-Preserving Statistics Computation
The recent investigation of privacy-preserving data mining and other kinds of privacy-preserving distributed computation has been motivated by the growing concern about the privacy...
Hiranmayee Subramaniam, Rebecca N. Wright, Zhiqian...
SIGMOD
2010
ACM
243views Database» more  SIGMOD 2010»
13 years 5 months ago
Non-homogeneous generalization in privacy preserving data publishing
Most previous research on privacy-preserving data publishing, based on the k-anonymity model, has followed the simplistic approach of homogeneously giving the same generalized val...
Wai Kit Wong, Nikos Mamoulis, David Wai-Lok Cheung
CIKM
2008
Springer
13 years 6 months ago
Towards privacy-preserving integration of distributed heterogeneous data
More and more applications rely heavily on large amounts of data in the distributed storages collected over time or produced by large scale scientific experiments or simulations. ...
Pawel Jurczyk, Li Xiong