Distributed Data Access Control Algorithm Using Mining Association Rules

In this paper, we present a new algorithm called Distributed data access control algorithm using association rules in large database respectively. The large amounts of data, the high scalability of distributed systems, and the easy partition and distribution of a centralized database, it is important to investigate efficient methods for distributed mining of generalized association rules [3,4]. This study discloses some interesting relationships between locally and globally large itemsets [6,7]. The proposed algorithm, which distributes a data with various databases and participate in a network using mining association rules. In this paper, efficient algorithm for mining generalized association rules in distributed database has been proposed and is based on FDM algorithm. Concepts of data mining with distribution law can improve the finite set. Every entry redirected into a FAK to simplify the next cycle of operation. Hit Count can also measure in a FAK by means of succeeded value. Time study divided into two phases according to a nature of data. Former one is frequently accessed data and the later one is ordinary data set. The FDM algorithm is combined with partition algorithm to give fast distributed data access control algorithm called DDACA.