An efficient modifying scheme for Hiding Sensitive Association Rules (HSAR)

Large number of database contains sensitive information that must be secured against unauthorized accesses. Recent advances in data mining techniques have increased the disclosure risks that one may encounter when releasing data to outside parties. This work focused on a new approach that strategically modifies a few transactions in the transaction database to decrease the supports or confidences of sensitive rules without producing the side effects. Since the correlation among rules can make it impossible to achieve this goal. This paper proposed heuristic methods for increasing the number of hidden sensitive rules and reducing the number of modified entries. Undesired side effects are avoided in the rule hiding process. All the sensitive rules are hidden without spurious rules falsely generated. Keyword- Apriori algorithm, Association rule mining, Sensitive rule hiding