STOC '87 Proceedings of the nineteenth annual ACM symposium on Theory of computing
Multiparty unconditionally secure protocols
STOC '88 Proceedings of the twentieth annual ACM symposium on Theory of computing
A communication-privacy tradeoff for modular addition
Information Processing Letters
Fair exchange with a semi-trusted third party (extended abstract)
Proceedings of the 4th ACM conference on Computer and communications security
Privacy-preserving data mining
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Designs, Codes and Cryptography - Special issue on towards a quarter-century of public key cryptography
Data mining: concepts and techniques
Data mining: concepts and techniques
A fast distributed algorithm for mining association rules
DIS '96 Proceedings of the fourth international conference on on Parallel and distributed information systems
Advances in Distributed and Parallel Knowledge Discovery
Advances in Distributed and Parallel Knowledge Discovery
A Secure Fault-Tolerant Conference-Key Agreement Protocol
IEEE Transactions on Computers
Parallel Mining of Association Rules
IEEE Transactions on Knowledge and Data Engineering
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Tools for privacy preserving distributed data mining
ACM SIGKDD Explorations Newsletter
k-anonymity: a model for protecting privacy
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Privacy preserving mining of association rules
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Privacy preserving association rule mining in vertically partitioned data
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
On the Privacy Preserving Properties of Random Data Perturbation Techniques
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Privacy-preserving k-means clustering over vertically partitioned data
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
IEEE Transactions on Knowledge and Data Engineering
Privacy-preserving Bayesian network structure computation on distributed heterogeneous data
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Privacy-Preserving Distributed Mining of Association Rules on Horizontally Partitioned Data
IEEE Transactions on Knowledge and Data Engineering
Privacy-Preserving Data Mining: Why, How, and When
IEEE Security and Privacy
Identity-Based Fault-Tolerant Conference Key Agreement
IEEE Transactions on Dependable and Secure Computing
Maintaining data privacy in association rule mining
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Public-key cryptosystems based on composite degree residuosity classes
EUROCRYPT'99 Proceedings of the 17th international conference on Theory and application of cryptographic techniques
An improved algorithm for computing logarithms over and its cryptographic significance (Corresp.)
IEEE Transactions on Information Theory
A public key cryptosystem and a signature scheme based on discrete logarithms
IEEE Transactions on Information Theory
Testing terrorism theory with data mining
International Journal of Data Analysis Techniques and Strategies
OTM'11 Proceedings of the 2011th Confederated international conference on On the move to meaningful internet systems - Volume Part I
Optimized two party privacy preserving association rule mining using fully homomorphic encryption
ICA3PP'11 Proceedings of the 11th international conference on Algorithms and architectures for parallel processing - Volume Part I
Arbitrarily distributed data-based recommendations with privacy
Data & Knowledge Engineering
Secure Two-Party Association Rule Mining Based on One-Pass FP-Tree
International Journal of Information Security and Privacy
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Distributed data mining applications, such as those dealing with health care, finance, counter-terrorism and homeland defence, use sensitive data from distributed databases held by different parties. This comes into direct conflict with an individual's need and right to privacy. In this paper, we come up with a privacy-preserving distributed association rule mining protocol based on a new semi-trusted mixer model. Our protocol can protect the privacy of each distributed database against the coalition up to n-2 other data sites or even the mixer if the mixer does not collude with any data site. Furthermore, our protocol needs only two communications between each data site and the mixer in one round of data collection.