Privacy-preserving data mining
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Privacy Preserving Data Mining
CRYPTO '00 Proceedings of the 20th Annual International Cryptology Conference on Advances in Cryptology
Introduction to Secure Computation
Lectures on Data Security, Modern Cryptology in Theory and Practice, Summer School, Aarhus, Denmark, July 1998
Building decision tree classifier on private data
CRPIT '14 Proceedings of the IEEE international conference on Privacy, security and data mining - Volume 14
State-of-the-art in privacy preserving data mining
ACM SIGMOD Record
Foundations of Cryptography: Volume 2, Basic Applications
Foundations of Cryptography: Volume 2, Basic Applications
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Privacy Preserving ID3 Algorithm over Horizontally Partitioned Data
PDCAT '05 Proceedings of the Sixth International Conference on Parallel and Distributed Computing Applications and Technologies
Protocols for secure computations
SFCS '82 Proceedings of the 23rd Annual Symposium on Foundations of Computer Science
How to generate and exchange secrets
SFCS '86 Proceedings of the 27th Annual Symposium on Foundations of Computer Science
Multiparty computation with full computation power and reduced overhead
HASE'04 Proceedings of the Eighth IEEE international conference on High assurance systems engineering
Privacy-Preserving decision trees over vertically partitioned data
DBSec'05 Proceedings of the 19th annual IFIP WG 11.3 working conference on Data and Applications Security
Bands of privacy preserving objectives: classification of PPDM strategies
AusDM '11 Proceedings of the Ninth Australasian Data Mining Conference - Volume 121
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People are more and more concerned with privacy protection while performing data mining. ID3 is a very popular decision tree building method in data mining. Entropy and Gini index are two different criteria used in ID3. While there is quite some work in privacy preserving ID3 using entropy, not much has been done for Gini index.In this paper, we present protocols based on secure multiparty computation for privacy preserving ID3 using Gini index over both vertically and horizontally partitioned data. Our protocols don't require any third party server. However, some communication overhead is necessary so that the parties can carry out the secure protocols.