Paillier based Privacy-Preserving Mining of Association Rules from Outsourced Transaction Databases

The Cloud computing is computing in which massive assembling of remote servers are managed to authorized centralized data storage and online access to computer resources , while Privacy-preserving data mining (PPDM) is one of the latest inclination in privacy and security studies. It is determined by one of the important positioning issues of the information era - the right to privacy. With the use of cloud computing services, an organization lack in computational resources can deploy its mining requires to an outsider service provider. However, both the elements and the association rules of the deployed database are observed as private property of the organization. The data owner converts its data and sends it to the server, ships mining queries to the server, and recoup the actual design from the extricate designs received from the outsider server for corporate privacy prevention. In this theory, we study the problems of outsourcing the association rule mining mechanisms within a corporate privacy-preserving framework. The Rob Frugal method is founded with defeat the security obligations of outsourced data. This method is an encryption plan which is based on one to one substitution ciphers for items and fake pattern from the database. In this system attacker discovers data by guessing attack, also man in the middle attack which is possible on Rob Frugal encryption to conquer this problem, the proposed technique encompasses Paillier encryption for enhancing the security level for outsourced data with the less complexity and to protect against the forging the contents of the correspondence. FP-growth algorithm is used for generating association rules for improving the performance and for preserving a homomorphic encryption algorithm Paillier cryptosystem is being used