Hiding sequential patterns using FP growth technique

Data mining deals with discovering useful and unknown information from databases. Databases may contain some sensitive information. This information need to be hidden from outside world, i.e. when we extract useful information, sensitive information should not be leaked. To deal with such situation, privacy preservation data mining comes into play. The aim of privacy preservation is to hide sensitive information while extracting information from databases. Privacy preservation data mining has been applied in the context of association rules and mining frequent item sets. In this paper we propose a scheme to hide sensitive sequential patterns. Our approach is based on FP Growth technique. We then apply anti-monotone and monotone constraints on FP tree to hide sensitive sequential patterns.