An efficient solution for hiding sensitive rules with updates

作者：Zhang, Junwei^*; Yang, Jing; Zhang, Jianpei; Zhang, Lejun

来源：ICIC Express Letters, 2012, 6(7): 1767-1773.

• Application area
• Association rules hiding
• Data mining techniques
• Data sets
• Data stream
• Mine association rules
• Rule hiding
• Side effect
• Sliding Window
• Streaming data
• Tree structures

Data mining techniques played an important role in many application areas. However, the misuse of these techniques may lead to the disclosed of sensitive knowledge. Researchers have made efforts at hiding sensitive association rules. Meanwhile, the widespread presence of streaming data also poses a new challenge to hide sensitive rules. We propose an algorithm DHSR that adopts sliding window to achieve the sensitive association rules hiding base on updates of data, tree structure SNFP-Tree as transitional structure between original data set and sanitized data set, not only solve problem of once scan for data stream, but also can be used to mine association rules and hide strong sensitive rules. We set two constraint parameters to minimize side effects, in order to hide all of sensitive association rules, and meanwhile keep the typicality of the original data to maximum. Experimental results show that our proposed algorithm completed the sensitive rules hiding with lower side effect well.

• 出版日期2012
• 单位哈尔滨工程大学