Optimizing Affine Maximizer Auctions via Linear Programming: An Application to Revenue Maximizing Mechanism Design for Zero-Day Exploits Markets

  • Mingyu GuoEmail author
  • Hideaki Hata
  • Ali Babar
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10621)


Optimizing within the affine maximizer auctions (AMA) is an effective approach for revenue maximizing mechanism design. The AMA mechanisms are strategy-proof and individually rational (if the agents’ valuations for the outcomes are nonnegative). Every AMA mechanism is characterized by a list of parameters. By focusing on the AMA mechanisms, we turn mechanism design into a value optimization problem, where we only need to adjust the parameters. We propose a linear programming based heuristic for optimizing within the AMA family. We apply our technique to revenue maximizing mechanism design for zero-day exploit markets. We show that due to the nature of the zero-day exploit markets, if there are only two agents (one offender and one defender), then our technique generally produces a near optimal mechanism: the mechanism’s expected revenue is close to the optimal revenue achieved by the optimal strategy-proof and individually rational mechanism (not necessarily an AMA mechanism).


Automated mechanism design Revenue maximization Mechanism design Security economics Bug bounty 


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© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.School of Computer ScienceUniversity of AdelaideAdelaideAustralia
  2. 2.Graduate School of Information ScienceNara Institute of Science and TechnologyIkomaJapan

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