Hiding Sensitive Rules Based on Transaction Grouping

• Main Authors: Jei-Hung Yang, 楊介宏
• Other Authors: Yi-Hung Wu
• Format: Others
• Language: zh-TW
• Published: 2010
• Online Access: http://ndltd.ncl.edu.tw/handle/58538882177123969090

碩士 === 中原大學 === 資訊工程研究所 === 98 === As the prevalent development of network technology, information sharing and communication is frequent in daily life. Although data mining techniques help people find the important rules among data, people also have to take the risk of sensitive information disclosed. In addition to hiding sensitive rules, recent researches also start discussing the reduction or avoidance of unexpected side effects, including the hiding of non-sensitive rules (lost rules) and the creation of non-existent rules (false rules). This thesis aims at a small amount of transaction modifications and proposes a method of rule hiding. The method can recover lost rules and keep sensitive rules hidden. Besides, we propose an efficient index structure for a quick retrieval of transactions during the hiding process. The experiments verify that our method can hide all sensitive rules and recover at most 40% lost rules. The index structure reduces about 85% retrieval time on average.