Privacy, Security, and Trust in KDD First ACM SIGKDD International W
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Editorial Board David Hutchison Lancaster University, UK Takeo Kanade Carnegie Mellon University, Pittsburgh, PA, USA Josef Kittler University of Surrey, Guildford, UK Jon M. Kleinberg Cornell University, Ithaca, NY, USA Alfred Kobsa University of California, Irvine, CA, USA Friedemann Mattern ETH Zurich, Switzerland John C. Mitchell Stanford University, CA, USA Moni Naor Weizmann Institute of Science, Rehovot, Israel Oscar Nierstrasz University of Bern, Switzerland C. Pandu Rangan Indian Institute of Technology, Madras, India Bernhard Steffen University of Dortmund, Germany Madhu Sudan Massachusetts Institute of Technology, MA, USA Demetri Terzopoulos University of California, Los Angeles, CA, USA Doug Tygar University of California, Berkeley, CA, USA Gerhard Weikum Max-Planck Institute of Computer Science, Saarbruecken, Germany
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Francesco Bonchi Elena Ferrari Bradley Malin Yücel Saygin (Eds.)
Privacy, Security, and Trust in KDD First ACM SIGKDD International Workshop, PinKDD 2007 San Jose, CA, USA, August 12, 2007 Revised Selected Papers
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Volume Editors Francesco Bonchi Pisa KDD Laboratory ISTI - C.N.R, Pisa, Italy E-mail: [email protected] Elena Ferrari University of Insubria Department of Computer Science and Communication, Varese, Italy E-mail: [email protected] Bradley Malin Vanderbilt University Nashville, TN 37232, USA E-mail: [email protected] Yücel Saygin Sabanci University Istanbul, Turkey E-mail: [email protected]
Library of Congress Control Number: 2008922886 CR Subject Classification (1998): H.4, H.3, C.2, H.2, D.4.6, K.4-6 LNCS Sublibrary: SL 4 – Security and Cryptology ISSN ISBN-10 ISBN-13
0302-9743 3-540-78477-2 Springer Berlin Heidelberg New York 978-3-540-78477-7 Springer Berlin Heidelberg New York
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Preface
Vast amounts of data are collected by service providers and system administrators, and are available in public information systems. Data mining technologies provide an ideal framework to assist in analyzing such collections for computer security and surveillance-related endeavors. For instance, system administrators can apply data mining to summarize activity patterns in access logs so that
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