Hiding Sequences

The process of discovering relevant patterns holding in a database, was first indicated as a threat to database security by O' Leary. Since then, many different approaches for knowledge hiding have emerged over the years, mainly in the context of association rules and frequent itemsets mining. Following many real-world data and applications demands, in this paper we shift the problem of knowledge hiding to contexts where both the data and the extracted knowledge have a sequential structure. We provide problem statement, some theoretical issues including NP-hardness of the problem, a polynomial sanitization algorithm and an experimental evaluation. Finally we discuss possible extensions that will allow to use this work as a basic building block formore complex kinds of patterns and applications.