MOSAR: A Multi-Objective Strategy for Hiding Sensitive Association Rules Using Genetic Algorithm

It seems very realistic to find different aspects in a problem solution like rule hiding. Based on this point of view, Availability, Sensitivity, and Conflict are defined as the novel measurements to detect specific transactions in each transactional database in an effective way. At this point, it will be helpful for decision makers to consider such aspects on their solutions to hide sensitive association rules (ARs). Accordingly, the authors put forward a fitness function of genetic algorithm adjusted to the proposed measurements for hiding sensitive rules of the original database. Experimental study shows that the MOSAR algorithm outperforms traditional approach (Decrease Support of Right Hand Side algorithm) in view of reducing ARs in conflict with sensitive ARs, as a side effect in sensitive rule hiding process. Furthermore, this approach is applicable to do its best in banking systems, where database is to be shared through the networks, to protect strategic information after a serious attack.