A Privacy Preserving Data Mining Scheme Based on Network User’s Behavior

The privacy preserving data mining has become a research hot issue in the data mining field. The server log of the Web site has preserved the page information visited by users. If the page information is not protected, the user’s privacy data would be leaked. Aiming at the problem, it discusses the privacy preserving problem based on the user’s behavior in the Web data mining, and then introduces a method which converts the Web server log information into the relational data table, produces the information which disturbs the data sheets with a randomized responding method. It offers the data users a discovery algorithm of the frequent itemsets and the strong association rules, then it receives the real private association rule among the online shopping basket goods. The experiments prove that the introduced privacy of the privacy preserving association rule mining algorithm in the Web data mining is good, and it has definite applicability.