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Proceedings Article, Paper
@InProceedings
Beitrag in Tagungsband, Workshop

Author, Editor
Author(s):
Bredereck, Robert
Nichterlein, Andr{\'e}
Niedermeier, Rolf
Philip, Geevarghese
dblp
dblp
dblp
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Not MPG Author(s):
Bredereck, Robert
Nichterlein, Andr{\'e}
Niedermeier, Rolf
Editor(s):
Murlak, Filip
Sankowski, Piotr
dblp
dblp
Not MPII Editor(s):
Murlak, Filip
Sankowski, Piotr
BibTeX cite key*:
brederecknichterleinniedermeierphilip2011a
Title, Booktitle
Title*:
Pattern-Guided Data Anonymization and Clustering
patternClustering.pdf (447.62 KB)
Booktitle*:
Mathematical Foundations of Computer Science 2011 - 36th International Symposium, MFCS 2011, Warsaw, Poland, August 22-26, 2011. Proceedings
Event, URLs
Conference URL::
http://mfcs.mimuw.edu.pl/
Downloading URL:
http://www.springerlink.com/content/k3q036770up07x70/fulltext.pdf
Event Address*:
Warsaw, Poland
Language:
English
Event Date*
(no longer used):
Organization:
Event Start Date:
22 August 2011
Event End Date:
26 August 2011
Publisher
Name*:
Springer
URL:
http://www.springer.com
Address*:
Berlin
Type:
Vol, No, Year, pp.
Series:
Lecture Notes in Computer Science
Volume:
6907
Number:
Month:
Pages:
182-193
Year*:
2011
VG Wort Pages:
ISBN/ISSN:
978-3-642-22992-3
Sequence Number:
DOI:
10.1007/978-3-642-22993-0
Note, Abstract, ©
(LaTeX) Abstract:
A matrix~$M$ over a fixed alphabet is $k$-anonymous if every row
in~$M$ has at least~$k-1$ identical copies in~$M$. Making a matrix
$k$-anonymous by replacing a minimum number of entries with an additional
$\star$-symbol (called ``suppressing entries'') is known to be
NP-hard. This task arises in the context of privacy-preserving
publishing. We propose and analyze the computational complexity
of an enhanced anonymization model where the user of the
$k$-anonymized data may additionally ``guide'' the selection of
the candidate matrix entries to be suppressed. The basic idea is
to express this by means of ``pattern vectors'' which are part
of the input. This can also be interpreted as a sort of
clustering process. It is motivated by the observation that
the ``value'' of matrix entries may significantly differ, and
losing one (by suppression) may be more harmful than losing
the other, which again may very much depend on the intended use of the
anonymized data. We show that already very basic special cases
of our new model lead to NP-hard problems while others allow for
(fixed-parameter) tractability results.
URL for the Abstract:
http://www.springerlink.com/content/k3q036770up07x70/
Keywords:
Parameterized Algorithms, $k$-anonymous, suppressions
Copyright Message:
Copyright Springer Berlin 2011. This work is subject to copyright. All rights are reserved, whether the whole or part of the material is
concerned, specifically the rights of translation, reprinting, re-use of illustrations, recitation, broadcasting, reproduction on microfilms or in any other way, and storage in data banks. Duplication of this publication or parts thereof is permitted only under the provisions of the German Copyright Law of September 9, 1965,
in its current version, and permission for use must always be obtained from Springer. Violations are liable to prosecution under the German Copyright Law.


Published in the Proceedings of MFCS 2011, Warsaw, Poland, August 22-26, 2011. Lecture Notes in Computer Science, Volume 6907. The original publication is available at www.springerlink.com : http://www.springerlink.com/content/k3q036770up07x70/
Download
Access Level:
Public

Correlation
MPG Unit:
Max-Planck-Institut für Informatik
MPG Subunit:
Algorithms and Complexity Group
Audience:
experts only
Appearance:
MPII WWW Server, MPII FTP Server, MPG publications list, university publications list, working group publication list, Fachbeirat, VG Wort



BibTeX Entry:

@INPROCEEDINGS{brederecknichterleinniedermeierphilip2011a,
AUTHOR = {Bredereck, Robert and Nichterlein, Andr{\'e} and Niedermeier, Rolf and Philip, Geevarghese},
EDITOR = {Murlak, Filip and Sankowski, Piotr},
TITLE = {Pattern-Guided Data Anonymization and Clustering},
BOOKTITLE = {Mathematical Foundations of Computer Science 2011 - 36th International Symposium, MFCS 2011, Warsaw, Poland, August 22-26, 2011. Proceedings},
PUBLISHER = {Springer},
YEAR = {2011},
VOLUME = {6907},
PAGES = {182--193},
SERIES = {Lecture Notes in Computer Science},
ADDRESS = {Warsaw, Poland},
ISBN = {978-3-642-22992-3},
DOI = {10.1007/978-3-642-22993-0},
}


Entry last modified by Geevarghese Philip, 07/08/2014
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Editor(s)
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Created
04/22/2012 01:29:57 PM
Revision
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Editor
Geevarghese Philip
Geevarghese Philip


Edit Date
04/22/2012 03:25:42 PM
04/22/2012 01:29:57 PM



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