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
Machine Learning
Privacy Preserving Data Mining
CRYPTO '00 Proceedings of the 20th Annual International Cryptology Conference on Advances in Cryptology
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
Building decision tree classifier on private data
CRPIT '14 Proceedings of the IEEE international conference on Privacy, security and data mining - Volume 14
Information sharing across private databases
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
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
Privacy-Preserving Distributed Mining of Association Rules on Horizontally Partitioned Data
IEEE Transactions on Knowledge and Data Engineering
Privacy-preserving clustering with distributed EM mixture modeling
Knowledge and Information Systems
Secure set intersection cardinality with application to association rule mining
Journal of Computer Security
Maintaining data privacy in association rule mining
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Privacy-preservation for gradient descent methods
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Privacy-preserving Naïve Bayes classification
The VLDB Journal — The International Journal on Very Large Data Bases
Privacy Preserving Data Mining Research: Current Status and Key Issues
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007
Secure Multi-party Protocols for Privacy Preserving Data Mining
WASA '08 Proceedings of the Third International Conference on Wireless Algorithms, Systems, and Applications
Secure two and multi-party association rule mining
CISDA'09 Proceedings of the Second IEEE international conference on Computational intelligence for security and defense applications
Using cryptography for privacy protection in data mining systems
WImBI'06 Proceedings of the 1st WICI international conference on Web intelligence meets brain informatics
Towards privacy-preserving model selection
PinKDD'07 Proceedings of the 1st ACM SIGKDD international conference on Privacy, security, and trust in KDD
An efficient cacheable secure scalar product protocol for privacy-preserving data mining
DaWaK'11 Proceedings of the 13th international conference on Data warehousing and knowledge discovery
k-Anonymous Decision Tree Induction
PKDD'06 Proceedings of the 10th European conference on Principle and Practice of Knowledge Discovery in Databases
Privacy-preserving ranking over vertically partitioned data
Proceedings of the 2012 Joint EDBT/ICDT Workshops
Privacy-preserving back-propagation and extreme learning machine algorithms
Data & Knowledge Engineering
Approximate privacy-preserving data mining on vertically partitioned data
DBSec'12 Proceedings of the 26th Annual IFIP WG 11.3 conference on Data and Applications Security and Privacy
Privacy-preserving self-organizing map
DaWaK'07 Proceedings of the 9th international conference on Data Warehousing and Knowledge Discovery
Bands of privacy preserving objectives: classification of PPDM strategies
AusDM '11 Proceedings of the Ninth Australasian Data Mining Conference - Volume 121
Distributed and Parallel Databases
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Privacy and security concerns can prevent sharing of data, derailing data mining projects.Distributed knowledge discovery, if done correctly, can alleviate this problem. In this paper, we tackle the problem of classification. We introduce a generalized privacy preserving variant of the ID3 algorithm for vertically partitioned data distributed over two or more parties. Along with the algorithm, we give a complete proof of security that gives a tight bound on the information revealed.