Self Protecting Pirates and Black-Box Traitor Tracing

  • Aggelos Kiayias
  • Moti Yung
Conference paper
First Online:
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2139)

Abstract

We present a new generic black-box traitor tracing model in which the pirate-decoder employs a self-protection technique. This mechanism is simple, easy to implement in any (software or hardware) device and is a natural way by which a pirate (an adversary) which is black-box accessible, may try to evade detection. We present a necessary combinatorial condition for black-box traitor tracing of self-protecting devices. We constructively prove that any system that fails this condition, is incapable of tracing pirate-decoders that contain keys based on a superlogarithmic number of traitor keys. We then combine the above condition with specific properties of concrete systems. We show that the Boneh-Franklin (BF) scheme as well as the Kurosawa-Desmedt scheme have no black-box tracing capability in the self-protecting model when the number of traitors is superlogarithmic, unless the ciphertext size is as large as in a trivial system, namely linear in the number of users. This partially settles in the negative the open problem of Boneh and Franklin regarding the general black-box traceability of the BF scheme: at least for the case of superlogarithmic traitors. Our negative result does not apply to the Chor-Fiat-Naor (CFN) scheme (which, in fact, allows tracing in our self-protecting model); this separates CFN black-box traceability from that of BF. We also investigate a weaker form of black-box tracing called single-query “black-box confirmation.” We show that, when suspicion is modeled as a confidence weight (which biases the uniform distribution of traitors), such single-query confirmation is essentially not possible against a self-protecting pirate-decoder that contains keys based on a superlogarithmic number of traitor keys.

Keywords

User Population Concrete System Overwhelming Probability Probabilistic Polynomial Time Broadcast Encryption 
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 2001

Authors and Affiliations

  • Aggelos Kiayias
    • 1
  • Moti Yung
    • 2
  1. 1.Graduate CenterCUNYNYUSA
  2. 2.CertCoNYUSA

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