Algorithms for clustering data
Algorithms for clustering data
BIRCH: an efficient data clustering method for very large databases
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
Oblivious transfer and polynomial evaluation
STOC '99 Proceedings of the thirty-first annual ACM symposium on Theory of computing
Efficient private bidding and auctions with an oblivious third party
CCS '99 Proceedings of the 6th ACM conference on Computer and communications security
Privacy-preserving data mining
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Privacy and security: an ethical analysis
ACM SIGCAS Computers and Society
Privacy Preserving Data Mining
CRYPTO '00 Proceedings of the 20th Annual International Cryptology Conference on Advances in Cryptology
PKC '01 Proceedings of the 4th International Workshop on Practice and Theory in Public Key Cryptography: Public Key Cryptography
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 k-means clustering over arbitrarily partitioned data
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Implementing Database Security and Auditing: Includes Examples for Oracle, SQL Server, DB2 UDB, Sybase
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
Public-key cryptosystems based on composite degree residuosity classes
EUROCRYPT'99 Proceedings of the 17th international conference on Theory and application of cryptographic techniques
ESORICS'05 Proceedings of the 10th European conference on Research in Computer Security
On private scalar product computation for privacy-preserving data mining
ICISC'04 Proceedings of the 7th international conference on Information Security and Cryptology
Privacy preserving BIRCH algorithm for clustering over vertically partitioned databases
SDM'06 Proceedings of the Third VLDB international conference on Secure Data Management
Arbitrarily distributed data-based recommendations with privacy
Data & Knowledge Engineering
Estimating NBC-based recommendations on arbitrarily partitioned data with privacy
Knowledge-Based Systems
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BIRCH algorithm [22] is a well known algorithm for clustering for effectively computing clusters in a large data set. As the data is typically distributed over several sites, clustering over distributed data is an important problem. The data can be distributed in horizontal, vertical or arbitrarily partitioned databases. But, because of privacy issues no party may share its data to other parties. The problem is how the parties can cluster the distributed data without breaching privacy of others data. The solutions in arbitrarily partitioned database setting generally work for both horizontal and vertically partitioned databases. In our work we give a procedure for securely running BIRCH algorithm over arbitrarily partitioned database. We introduce secure protocols for distance metrics and give a procedure for using these metrics in securely computing clusters over arbitrarily partitioned database.