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Partially Observable Games for Secure Autonomy

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Název: Partially Observable Games for Secure Autonomy
Autoři: Ahmadi, Mohamadreza, Viswanathan, Arun A., Ingham, Michel D., Tan, Kymie, Ames, Aaron D.
Zdroj: 2020 IEEE Security and Privacy Workshops (SPW), San Francisco, CA, 21 May 2020
Informace o vydavateli: IEEE
Rok vydání: 2020
Sbírka: Caltech Authors (California Institute of Technology)
Popis: Technology development efforts in autonomy and cyber-defense have been evolving independently of each other, over the past decade. In this paper, we report our ongoing effort to integrate these two presently distinct areas into a single framework. To this end, we propose the two-player partially observable stochastic game formalism to capture both high-level autonomous mission planning under uncertainty and adversarial decision making subject to imperfect information. We show that synthesizing sub-optimal strategies for such games is possible under finite-memory assumptions for both the autonomous decision maker and the cyber-adversary. We then describe an experimental testbed to evaluate the efficacy of the proposed framework. ; © 2020, Mohamadreza Ahmadi. Under license to IEEE. The work described in this paper was performed at the California Institute of Technology, and at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration (NASA). ; Submitted - 2002.01969.pdf
Druh dokumentu: book part
Jazyk: unknown
Relation: https://doi.org/10.1109/spw50608.2020.00046; https://arxiv.org/abs/2002.01969; https://authors.library.caltech.edu/communities/caltechauthors/; eprintid:107466
DOI: 10.1109/spw50608.2020.00046
Dostupnost: https://doi.org/10.1109/spw50608.2020.00046
Rights: info:eu-repo/semantics/openAccess ; Other
Přístupové číslo: edsbas.24F13BC6
Databáze: BASE
Popis
Abstrakt:Technology development efforts in autonomy and cyber-defense have been evolving independently of each other, over the past decade. In this paper, we report our ongoing effort to integrate these two presently distinct areas into a single framework. To this end, we propose the two-player partially observable stochastic game formalism to capture both high-level autonomous mission planning under uncertainty and adversarial decision making subject to imperfect information. We show that synthesizing sub-optimal strategies for such games is possible under finite-memory assumptions for both the autonomous decision maker and the cyber-adversary. We then describe an experimental testbed to evaluate the efficacy of the proposed framework. ; © 2020, Mohamadreza Ahmadi. Under license to IEEE. The work described in this paper was performed at the California Institute of Technology, and at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration (NASA). ; Submitted - 2002.01969.pdf
DOI:10.1109/spw50608.2020.00046