Strategies for Sensitive Association Rule Hiding

Abstract:

Data mining technologies are used widely while the side effects it incurred are concerned so seriously. Privacy preserving data mining is so important for data and knowledge security during data mining applications. Association rule extracted from data mining is one kind of the most popular knowledge. It is challenging to hide sensitive association rules extracted by data mining process and make less affection on non-sensitive rules and the original database. In this work, we focus on specific association rule automatic hiding. Novel strategies are proposed which are based on increasing the support of the left hand and decreasing the support of the right hand. Quality measurements for sensitive association rules hiding are presented.

• Periodical: Applied Mechanics and Materials (Volumes 336-338)
• Pages: 2203-2206
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.336-338.2203
• Online since: July 2013
• Authors: Hui Wang
• Keywords: Data Mining (DM), Hiding Strategies, Privacy Preserving, Quality Measurements, Sensitive Association Rule

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