A Security Based Data Mining Approach in Data Grid

TL;DR

This paper presents a data mining approach integrated with grid computing to efficiently find frequent sequences across multiple users while enhancing security through trust management in data grids.

Contribution

It introduces a grid-based data mining technique utilizing probabilistic frequent sequence algorithms combined with a trust management architecture for improved security.

Findings

Efficient automatic allocation of resources based on probabilistic mining.

Fast and accurate discovery of frequent sequences for multiple users.

Enhanced security through trust management architecture.

Abstract

Grid computing is the next logical step to distributed computing. Main objective of grid computing is an innovative approach to share resources such as CPU usage; memory sharing and software sharing. Data Grids provide transparent access to semantically related data resources in a heterogeneous system. The system incorporates both data mining and grid computing techniques where Grid application reduces the time for sending results to several clients at the same time and Data mining application on computational grids gives fast and sophisticated results to users. In this work, grid based data mining technique is used to do automatic allocation based on probabilistic mining frequent sequence algorithm. It finds frequent sequences for many users at a time with accurate result. It also includes the trust management architecture for trust enhanced security.