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Attacking Unlinkability: The Importance of Context

  • Matthias Franz
  • Bernd Meyer
  • Andreas Pashalidis
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4776)

Abstract

A system that protects the unlinkability of certain data items (e. g. identifiers of communication partners, messages, pseudonyms, transactions, votes) does not leak information that would enable an adversary to link these items. The adversary could, however, take advantage of hints from the context in which the system operates. In this paper, we introduce a new metric that enables one to quantify the (un)linkability of the data items and, based on this, we consider the effect of some simple contextual hints.

Keywords

Equivalence Class Random Graph Communication Session Anonymous Communication Privacy Breach 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Matthias Franz
    • 1
  • Bernd Meyer
    • 1
  • Andreas Pashalidis
    • 2
  1. 1.Siemens AG, Corporate Technology, Otto-Hahn-Ring 6, 81739 MünchenGermany
  2. 2.NEC Europe Ltd, Network Laboratories, Kurfürsten-Anlage 36, 69115 HeidelbergGermany

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