Abstract : Current approaches to privacy policy comparison use strict evaluation criteria (e.g. user preferences) and are unable to state how close a given policy is to fulfil these criteria. More flexible approaches for policy comparison is a prerequisite for a number of more advanced privacy services, e.g. improved privacy-enhanced search engines and automatic learning of privacy preferences. This paper describes the challenges related to policy comparison, and outlines what solutions are needed in order to meet these challenges in the context of preference learning privacy agents.
Type de document :
Communication dans un congrès
David Hutchison; Takeo Kanade; Madhu Sudan; Demetri Terzopoulos; Doug Tygar; Moshe Y. Vardi; Gerhard Weikum; Jan Camenisch; Dogan Kesdogan; Josef Kittler; Jon M. Kleinberg; Friedemann Mattern; John C. Mitchell; Moni Naor; Oscar Nierstrasz; C. Pandu Rangan; Bernhard Steffen. International Workshop on Open Problems in Network Security (iNetSec), Jun 2011, Lucerne, Switzerland. Springer, Lecture Notes in Computer Science, LNCS-7039, pp.89-103, 2012, Open Problems in Network Security. 〈10.1007/978-3-642-27585-2_8〉
https://hal.inria.fr/hal-01481509
Contributeur : Hal Ifip
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Soumis le : jeudi 2 mars 2017 - 16:38:14
Dernière modification le : vendredi 3 mars 2017 - 11:11:38
Document(s) archivé(s) le : mercredi 31 mai 2017 - 17:34:43
Inger Tøndel, Åsmund Nyre. Towards a Similarity Metric for Comparing Machine-Readable Privacy Policies. David Hutchison; Takeo Kanade; Madhu Sudan; Demetri Terzopoulos; Doug Tygar; Moshe Y. Vardi; Gerhard Weikum; Jan Camenisch; Dogan Kesdogan; Josef Kittler; Jon M. Kleinberg; Friedemann Mattern; John C. Mitchell; Moni Naor; Oscar Nierstrasz; C. Pandu Rangan; Bernhard Steffen. International Workshop on Open Problems in Network Security (iNetSec), Jun 2011, Lucerne, Switzerland. Springer, Lecture Notes in Computer Science, LNCS-7039, pp.89-103, 2012, Open Problems in Network Security. 〈10.1007/978-3-642-27585-2_8〉. 〈hal-01481509〉
