STOC '87 Proceedings of the nineteenth annual ACM symposium on Theory of computing
Privacy-preserving data mining
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
On the design and quantification of privacy preserving data mining algorithms
PODS '01 Proceedings of the twentieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
A One Round Protocol for Tripartite Diffie-Hellman
ANTS-IV Proceedings of the 4th International Symposium on Algorithmic Number Theory
The Weil and Tate Pairings as Building Blocks for Public Key Cryptosystems
ANTS-V Proceedings of the 5th International Symposium on Algorithmic Number Theory
Revealing information while preserving privacy
Proceedings of the twenty-second ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Limiting privacy breaches in privacy preserving data mining
Proceedings of the twenty-second ACM SIGMOD-SIGACT-SIGART symposium on Principles of database 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
Using randomized response techniques for privacy-preserving data mining
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
k-TTP: a new privacy model for large-scale distributed environments
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Privacy-preserving Bayesian network structure computation on distributed heterogeneous data
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
The Weil Pairing, and Its Efficient Calculation
Journal of Cryptology
Deriving private information from randomized data
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Anonymity-preserving data collection
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Privacy-preserving distributed k-means clustering over arbitrarily partitioned data
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Privacy-Preserving Frequent Pattern Mining across Private Databases
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
Maintaining data privacy in association rule mining
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
How to generate and exchange secrets
SFCS '86 Proceedings of the 27th Annual Symposium on Foundations of Computer Science
Collusion-Resistant protocol for privacy-preserving distributed association rules mining
ICICS'09 Proceedings of the 11th international conference on Information and Communications Security
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In recent years, a large number of data mining tools were developed, which may reveal costumers' privacy if proper protection measure is not taken. On the other hand, customers are becoming increasingly concerned about privacy. They are reluctant to provide personal information unless privacy-preserving techniques are used. In this paper, we propose a privacy-preserving protocol for mining support counts, which maintains high accuracy and strong privacy while achieving very good efficiency. Compared with existing works with similar privacy and accuracy guarantees, our solution is much more efficient. We use identity-based cryptography, which has an additional advantage that no public key certificate is needed. Further, our evaluation results show that the protocol is very efficient and practical.