Fast Cryptographic Privacy Preserving Association Rules Mining on Distributed Homogenous Database

Privacy is one of the most important properties of an information system must satisfy, in which systems the need toshare information among different, not trusted entities, the protection of sensible information has a relevant role. A relativelynew trend shows that classical access control techniques are not sufficient to guarantee privacy when data mining techniquesare used in a malicious way. Privacy preserving data mining algorithms have been recently introduced with the aim ofpreventing the discovery of sensible information. In this paper we propose a modification to privacy preserving associationrule mining on distributed homogenous database algorithm. Our algorithm is faster than old one which modified withpreserving privacy and accurate results. Modified algorithm is based on a semi-honest model with negligible collisionprobability. The flexibility to extend to any number of sites without any change in implementation can be achieved. And alsoany increase doesn’t add more time to algorithm because all client sites perform the mining in the same time so the overheadin communication time only. The total bit-communication cost for our algorithm is function in (N) sites