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Hypothesis Testing in Presence of Adversaries

Author

Listed:
  • J. González-Ortega
  • D. Ríos Insua
  • F. Ruggeri
  • R. Soyer

Abstract

We present an extension to the classical problem of hypothesis testing by incorporating actions of an adversary who intends to mislead the decision-maker and attain a certain benefit. After presenting the general problem within an adversarial statistical decision theory framework, we consider the cases of adversaries who can either perturb the data received or modify the underlying data-generating process parametrically. Supplemental materials for this article are available online.

Suggested Citation

  • J. González-Ortega & D. Ríos Insua & F. Ruggeri & R. Soyer, 2021. "Hypothesis Testing in Presence of Adversaries," The American Statistician, Taylor & Francis Journals, vol. 75(1), pages 31-40, January.
    • Handle: RePEc:taf:amstat:v:75:y:2021:i:1:p:31-40
    DOI: 10.1080/00031305.2019.1630001
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    Cited by:

    1. Antonio Pievatolo & Fabrizio Ruggeri & Refik Soyer & Simon Wilson, 2021. "Decisions in Risk and Reliability: An Explanatory Perspective," Stats, MDPI, vol. 4(2), pages 1-23, March.

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