An Improved Algorithm for Hiding Sensitive Association Rules Using Exact Approach

Many algorithms are proposed by researchers to find association rules which help the users to make strategic decisions to improve the performance of the business or any qualitative organizations. The threat occurs to association rule mining when data or information is required to share to many users to get mutual benefits. Among the existing techniques the exact hiding approaches provides best solutions with minimum side effects. A modified inline algorithm is proposed in this paper to hide sensitive rules by formulating constraint satisfaction problem without any side effects with the concepts of positive and negative border sets.

Subscribe to the Data Insider Newsletter

Learn the latest news and best practices about data science, big data analytics, artificial intelligence, data security, and more. Delivered Mondays and Thursdays

Subscribe to the Data Insider Newsletter

Learn the latest news and best practices about data science, big data analytics, artificial intelligence, data security, and more. Delivered Mondays and Thursdays

Resource Details

Provided by:
International Journal of Computer Science and Information Technology & Security (IJCSITS)
Topic:
Data Management
Format:
PDF