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Selection of Optimal Strategy for Moving Target Defense Based on Signal Game

Published: 04 January 2021 Publication History

Abstract

This paper analyzes the dynamic and incomplete information characteristics of network offensive and defensive confrontation. In this paper, a signal game is used as the framework, and the defender is used as the signal initiator. The defensive behavior model that induces the signal to interfere with the attack is used to construct the moving target defense of the signal game. Considering the unavoidable misdetection defects of the defense detection system itself, a method for quantifying the benefits of the attack strategy and the defense strategy is proposed, and a refined Bayesian equilibrium algorithm and a prior belief correction algorithm are given. The optimal defense strategy and the optimal induced signal strategy were selected through the relative defense gains and refined Bayesian equilibrium results, respectively. Finally, an example is used to illustrate and verify the feasibility and effectiveness of the model and method. Based on the analysis of experimental data, general rules are summarized.

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Cited By

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  • (2023)Q-learning based strategy analysis of cyber-physical systems considering unequal costIntelligent and Converged Networks10.23919/ICN.2023.00124:2(116-126)Online publication date: Jun-2023
  • (2023)Moving Target Defense Strategy Selection against Malware in Resource-Constrained Devices2023 IEEE International Conference on Cyber Security and Resilience (CSR)10.1109/CSR57506.2023.10224824(123-129)Online publication date: 31-Jul-2023

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  1. Selection of Optimal Strategy for Moving Target Defense Based on Signal Game

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    cover image ACM Other conferences
    CIAT 2020: Proceedings of the 2020 International Conference on Cyberspace Innovation of Advanced Technologies
    December 2020
    597 pages
    ISBN:9781450387828
    DOI:10.1145/3444370
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

    In-Cooperation

    • Sun Yat-Sen University
    • CARLETON UNIVERSITY: INSTITUTE FOR INTERDISCIPLINARY STUDIES
    • Beijing University of Posts and Telecommunications
    • Guangdong University of Technology: Guangdong University of Technology
    • Deakin University

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 04 January 2021

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    Author Tags

    1. Cyberspace security
    2. Moving target defense
    3. Optimal strategy selection
    4. Signal game

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    CIAT 2020

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    CIAT 2020 Paper Acceptance Rate 94 of 232 submissions, 41%;
    Overall Acceptance Rate 94 of 232 submissions, 41%

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    Cited By

    View all
    • (2023)Q-learning based strategy analysis of cyber-physical systems considering unequal costIntelligent and Converged Networks10.23919/ICN.2023.00124:2(116-126)Online publication date: Jun-2023
    • (2023)Moving Target Defense Strategy Selection against Malware in Resource-Constrained Devices2023 IEEE International Conference on Cyber Security and Resilience (CSR)10.1109/CSR57506.2023.10224824(123-129)Online publication date: 31-Jul-2023

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