Privacy Preserving Data Mining
CRYPTO '00 Proceedings of the 20th Annual International Cryptology Conference on Advances in Cryptology
Tools for privacy preserving distributed data mining
ACM SIGKDD Explorations Newsletter
Building decision tree classifier on private data
CRPIT '14 Proceedings of the IEEE international conference on Privacy, security and data mining - Volume 14
Privacy preserving frequent itemset mining
CRPIT '14 Proceedings of the IEEE international conference on Privacy, security and data mining - Volume 14
Ontologies: A Silver Bullet for Knowledge Management and Electronic Commerce
Ontologies: A Silver Bullet for Knowledge Management and Electronic Commerce
Privacy Preserving Association Rule Mining
RIDE '02 Proceedings of the 12th International Workshop on Research Issues in Data Engineering: Engineering E-Commerce/E-Business Systems (RIDE'02)
Ontology-based distributed autonomous knowledge systems
Information Systems - Special issue on web data integration
How to generate and exchange secrets
SFCS '86 Proceedings of the 27th Annual Symposium on Foundations of Computer Science
Privacy Aware Data Management and Chase
Fundamenta Informaticae - Special issue ISMIS'05
Privacy Aware Data Management and Chase
Fundamenta Informaticae - Special issue ISMIS'05
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This paper contributes strategies that minimize the number of values which should be hidden in an Information System to guarantee that values of attributes containing sensitive information cannot be reconstructed by either Distributed or Local Chase within a Distributed Information System (DIS). The notion of the hidden attribute reconstruction by Knowledge Discovery and corresponding obstruction strategy was introduced in [1] where a minimal number of attribute values are additionally hidden to block the reconstruction of sensitive data by the rules extracted from DIS. The problem is particularly troublesome when locally generated rules restore those additionally hidden attribute values, and form a cycle of implications. The strategies in this paper complement existing Distributed Chase obstruction and work over widely used information systems.