Association Rule Hiding using Artificial Bee Colony Algorithm

Data mining is the process of extracting the previously unknown patterns from large amount of data. Privacy preserving data mining is one of the research areas in data mining. The main objective of privacy preserving data mining is to provide the privacy for personally identifiable information in the datasets. Many privacy preserving techniques are used for protecting the confidential data items. Some of them are Privacy preserving Association Rule Mining, Privacy Preserving Clustering, Privacy Preserving Classification, Statistical disclosure control, K-anonymity etc. In this research paper, we have discussed about the association rule hiding problem. Association rule mining is one of the very important data mining techniques. The process of discovering itemsets that frequently co-occur in a transactional database so as to produce significant association rules that hold for the data is known as Association rule mining. Association rule hiding is the process of modifying the original database by hiding the sensitive data to protect the sensitive association rules. In this paper, we have proposed Artificial Bee Colony optimization algorithm for hiding the sensitive association rules. We analyze the efficiency of the Artificial Bee Colony optimization technique by using various performance factors.