Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/6808
Title: Hiding Sequential and Spatiotemporal Patterns
Authors: Abul, Osman
Bonchi, Francesco
Giannotti, Fosca
Keywords: Sequential patterns
spatiotemporal patterns
knowledge hiding
data publishing
Issue Date: 2010
Publisher: IEEE Computer Soc
Abstract: The process of discovering relevant patterns holding in a database was first indicated as a threat to database security by O'Leary in [1]. Since then, many different approaches for knowledge hiding have emerged over the years, mainly in the context of association rules and frequent item sets mining. Following many real-world data and application 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 define the problem of hiding sequential patterns and show its NP-hardness. Thus, we devise heuristics and a polynomial sanitization algorithm. Starting from this framework, we specialize it to the more complex case of spatiotemporal patterns extracted from moving objects databases. Finally, we discuss a possible kind of attack to our model, which exploits the knowledge of the underlying road network, and enhance our model to protect from this kind of attack. An exhaustive experiential analysis on real-world data sets shows the effectiveness of our proposal.
URI: https://doi.org/10.1109/TKDE.2009.213
https://hdl.handle.net/20.500.11851/6808
ISSN: 1041-4347
1558-2191
Appears in Collections:Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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