A method for obtaining digital signatures and public-key cryptosystems
Communications of the ACM
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
A fast distributed algorithm for mining association rules
DIS '96 Proceedings of the fourth international conference on on Parallel and distributed information systems
Efficient Mining of Association Rules in Distributed Databases
IEEE Transactions on Knowledge and Data Engineering
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Privacy-Preserving Distributed Mining of Association Rules on Horizontally Partitioned Data
IEEE Transactions on Knowledge and Data Engineering
A Framework for Evaluating Privacy Preserving Data Mining Algorithms*
Data Mining and Knowledge Discovery
Optimized two party privacy preserving association rule mining using fully homomorphic encryption
ICA3PP'11 Proceedings of the 11th international conference on Algorithms and architectures for parallel processing - Volume Part I
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Privacy is one of the most important properties of an information system must satisfy. In which systems the need to share information among different, not trusted entities, the protection of sensible information has a relevant role. A relatively new trend shows that classical access control techniques are not sufficient to guarantee privacy when data mining techniques are used in a malicious way. Privacy preserving data mining algorithms have been recently introduced with the aim of preventing the discovery of sensible information. In this paper we propose a modification to privacy preserving association rule mining on distributed homogenous database algorithm. Our algorithm is faster than old one which modified with preserving privacy and accurate results. Modified algorithm is based on a semi-honest model with negligible collision probability. The flexibility to extend to any number of sites without any change in implementation can be achieved. And also any increase doesn't add more time to algorithm because all client sites perform the mining in the same time so the overhead in communication time only. The total bit-communication cost for our algorithm is function in (N) sites.