NOVEL PRIVACY PRESERVING ASSOCIATION RULE MINING FOR HORIZONTALLY PARTITIONED DATABASES

Abstract

Advancement in scientific research depends on the availability and sharing of information and ideas. Many authors proposed many methodologies for isolation preserving data mining for centralized as well as for distributed database. The core intend of this paper work is, to develop efficient methodologies to find privacy preserving association rule mining in centralized as well as in distributed database environment without violating any privacy constraints. The issue of privacy constraints for centralized database environment is entirely different from distributed database environment. So the approaches for privacy preserving association rule mining in centralized are also different from approaches in distributed environment. Achieving privacy preserving goals in both these environments in the process of mining is a challenging task.