Association Rule Hiding by Heuristic Approach to Reduce Side Effects & Hide Multiple R.H.S. Items
Association rule mining is a powerful model of data mining used for finding hidden patterns in large databases. One of the great challenges of data mining is to protect the confidentiality of sensitive patterns when releasing database to third parties. Association rule hiding algorithms sanitize database such that certain sensitive association rules cannot be discovered through association rule mining techniques. In this study, the authors propose two algorithms, ADSRRC (Advanced Decrease Support of R.H.S. items of Rule Cluster) and RRLR (Remove and Reinsert L.H.S. of Rule), for hiding sensitive association rules.