2020 IEEE International Symposium
on Information Theory
21-26 June 2020 • Los Angeles, California, USA
| Paper ID | E.1.5 | ||
| Paper Title | A Game-Theoretic Approach to Sequential Detection in Adversarial Environments | ||
| Authors | Ruizhi Zhang, University of Nebraska-Lincoln, United States; Shaofeng Zou, University at Buffalo, the State University of New York, United States | ||
| Session | E.1: Detection Theory | ||
| Presentation | Lecture | ||
| Track | Detection and Estimation | ||
| Manuscript | Click here to download the manuscript | ||
| Virtual Presentation | Click here to watch in the Virtual Symposium | ||
| Abstract | The problem of sequential binary hypothesis testing in an adversarial environment is investigated. Specifically, if there is no adversary, the samples are generated independently by a distribution $p$; and if the adversary is present, the samples are generated independently by another distribution $q$. The adversary picks a distribution $q\in\mathcal Q$ with cost $c(q)$. The goal of the defender is to decide whether there is an adversary using samples as few as possible; and the goal of the adversary is to fool the defender. The problem is formulated as a non-zero-sum game between the adversary and the defender. A pair of strategies (attack strategy from the adversary and the sequential hypothesis testing scheme from the detector) is proposed and proved to be a Nash equilibrium pair for the non-zero-sum game asymptotically. Numerical experiments are provided to validate our results. | ||
Plan Ahead
2021 IEEE International Symposium on Information Theory
11-16 July 2021 | Melbourne, Victoria, Australia
