Parallel Privacy Preserving Association rule mining on pc Clusters

Association rules discovered by association rule mining may contain some sensitive rules, which may cause potential threats towards privacy and security. In this paper, we address the problem of privacy preserving association rule mining by proposing a Knowledge Sanitization to prevent the disclosure of sensitive rules. We also present parallel approach to generate a non-sensitive and sensitive rule mining. Our proposed solution key issue is to provide a high degree of parallelism for privacy to the data owner.