A Novel Optimization based Algorithm to Hide Sensitive Item-sets through Sanitization Approach

Association rule hiding an important issue in recent years due to the development of privacy preserving data mining techniques for hiding the association rules. One of the mostly used techniques to hide association rules is the sanitization of the database. In this paper, a novel algorithm MPSO2DT has been proposed based on the Particle Swarm Optimization (PSO) in order to reduce the side effects. The aim is to reduce the side effects such as Sensitive item-set hiding failure, Non-sensitive misses, extra item-set generations and Database dissimilarities along with the reduction of running time and complexities through transaction deletion.