Articolo in rivista, 2010, ENG, 10.1109/TKDE.2009.213
Giannotti F.; Bonchi F.; Abul O.
CNR-ISTI, Pisa, Italy; Yahoo! Research, Barcelona, Spain; TOBB University of Economics and Technology
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.
IEEE transactions on knowledge and data engineering (Print) 22 (12), pp. 1709–1723
Sequential patterns, Spatiotemporal patterns, Knowledge hiding, Data publishing
ISTI – Istituto di scienza e tecnologie dell'informazione "Alessandro Faedo"
ID: 185279
Year: 2010
Type: Articolo in rivista
Creation: 2012-05-06 00:39:24.000
Last update: 2018-01-31 19:04:09.000
CNR authors
External IDs
CNR OAI-PMH: oai:it.cnr:prodotti:185279
DOI: 10.1109/TKDE.2009.213
Scopus: 2-s2.0-78149260852
ISI Web of Science (WOS): WOS:000283133800005