Elements of information theory
Elements of information theory
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
Building decision tree classifier on private data
CRPIT '14 Proceedings of the IEEE international conference on Privacy, security and data mining - Volume 14
On the Privacy Preserving Properties of Random Data Perturbation Techniques
ICDM '03 Proceedings of the Third IEEE International Conference on 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
A new scheme on privacy preserving association rule mining
PKDD '04 Proceedings of the 8th European Conference on Principles and Practice of Knowledge Discovery in Databases
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
A privacy-preserving collaborative filtering scheme with two-way communication
EC '06 Proceedings of the 7th ACM conference on Electronic commerce
Space adaptation: privacy-preserving multiparty collaborative mining with geometric perturbation
Proceedings of the twenty-sixth annual ACM symposium on Principles of distributed computing
Enhancing privacy and preserving accuracy of a distributed collaborative filtering
Proceedings of the 2007 ACM conference on Recommender systems
Guided perturbation: towards private and accurate mining
The VLDB Journal — The International Journal on Very Large Data Bases
Privacy-preserving classification of vertically partitioned data via random kernels
ACM Transactions on Knowledge Discovery from Data (TKDD)
Hiding Sensitive Associative Classification Rule by Data Reduction
ADMA '07 Proceedings of the 3rd international conference on Advanced Data Mining and Applications
Generalization-Based Privacy-Preserving Data Collection
DaWaK '08 Proceedings of the 10th international conference on Data Warehousing and Knowledge Discovery
Accurate and large-scale privacy-preserving data mining using the election paradigm
Data & Knowledge Engineering
Privacy-preserving backpropagation neural network learning
IEEE Transactions on Neural Networks
Towards comprehensive privacy protection in data clustering
PAKDD'07 Proceedings of the 11th Pacific-Asia conference on Advances in knowledge discovery and data mining
PinKDD'07 Proceedings of the 1st ACM SIGKDD international conference on Privacy, security, and trust in KDD
Fuzzy based clustering algorithm for privacy preserving data mining
International Journal of Business Information Systems
TrustBus'11 Proceedings of the 8th international conference on Trust, privacy and security in digital business
Privacy preserving neural networks in iris signature feature extraction
Proceedings of the 5th International Conference on PErvasive Technologies Related to Assistive Environments
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We address privacy-preserving classification problem in a distributed system. Randomization has been the approach proposed to preserve privacy in such scenario. However, this approach is now proven to be insecure as it has been discovered that some privacy intrusion techniques can be used to reconstruct private information from the randomized data tuples. We introduce an algebraic-technique-based scheme. Compared to the randomization approach, our new scheme can build classifiers more accurately but disclose less private information. Furthermore, our new scheme can be readily integrated as a middleware with existing systems.