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Revenue Maximizing Markets for Zero-Day Exploits

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Part of the book series:Lecture Notes in Computer Science ((LNAI,volume 9862))

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Abstract

Markets for zero-day exploits (software vulnerabilities unknown to the vendor) have a long history and a growing popularity. We study these markets from a revenue-maximizing mechanism design perspective. We first propose a theoretical model for zero-day exploits markets. In our model, one exploit is being sold to multiple buyers. There are two kinds of buyers, which we call the defenders and the offenders. The defenders are buyers who buy vulnerabilities in order to fix them (e.g., software vendors). The offenders, on the other hand, are buyers who intend to utilize the exploits (e.g., national security agencies and police). Our model is more than a single-item auction. First, an exploit is a piece of information, so one exploit can be sold to multiple buyers. Second, buyers have externalities. If one defender wins, then the exploit becomes worthless to the offenders. Third, if we disclose the details of the exploit to the buyers before the auction, then they may leave with the information without paying. On the other hand, if we do not disclose the details, then it is difficult for the buyers to come up with their private valuations. Considering the above, our proposed mechanism discloses the details of the exploit to all offenders before the auction. The offenders then pay to delay the exploit being disclosed to the defenders.

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Notes

  1. 1.

    Example such companies include ZeroDium and Vupen [6].

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Author information

Authors and Affiliations

  1. School of Computer Science, University of Adelaide, Adelaide, Australia

    Mingyu Guo & Ali Babar

  2. Graduate School of Information Science, Nara Institute of Science Technology, Ikoma, Japan

    Hideaki Hata

Authors
  1. Mingyu Guo

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  2. Hideaki Hata

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  3. Ali Babar

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Corresponding author

Correspondence toMingyu Guo.

Editor information

Editors and Affiliations

  1. Dipartimento di Informatica, Università degli Studi di Torino , Torino, Italy

    Matteo Baldoni

  2. Computing and Communications, Lancaster University, Lancaster, United Kingdom

    Amit K. Chopra

  3. Department of Computer Science, New Mexico State University, Las Cruces, New Mexico, USA

    Tran Cao Son

  4. Graduate School of Maritime Sciences, Kobe University, Kobe, Japan

    Katsutoshi Hirayama

  5. Dept. di Informatica: Sci. e Ingegneria, Universitá di Bologna, Bologna, Italy

    Paolo Torroni

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Guo, M., Hata, H., Babar, A. (2016). Revenue Maximizing Markets for Zero-Day Exploits. In: Baldoni, M., Chopra, A., Son, T., Hirayama, K., Torroni, P. (eds) PRIMA 2016: Principles and Practice of Multi-Agent Systems. PRIMA 2016. Lecture Notes in Computer Science(), vol 9862. Springer, Cham. https://doi.org/10.1007/978-3-319-44832-9_15

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Price includes VAT (Japan)
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Price includes VAT (Japan)
  • Compact, lightweight edition
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Tax calculation will be finalised at checkout

Purchases are for personal use only


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