网络战争与常规作战建模的整合:一个贝叶斯框架

Zafer Şengül, Cengiz Acartürk
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引用次数: 0

摘要

恶意软件的传播能够在军事行动中引入不利影响,因为今天的高科技军事武器和指挥、控制和通信系统本质上是相互连接的ICT系统。常规战争模型最近已经升级为包括网络战争元素,以反映网络攻击的潜在影响。在本研究中,我们提出并评估了一个框架,用于模拟恶意软件通过计算机网络和动态战传播的综合影响。我们采用概率学习方法,即贝叶斯网络分析,来开发具有恶意软件传播特征的集成作战模型。这些模型的总体目标是预测哪一方在战争结束时可能拥有优势,考虑到在战争开始时解决战斗力量的动力和网络效应影响的参数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cyber Warfare Integration to Conventional Combat Modeling: A Bayesian Framework
Malware propagation is capable of introducing adverse effects in military operations since today’s high-tech military weapons and command, control, and communication systems are essentially interconnected ICT systems. Conventional warfare models have been recently upgraded to include cyber warfare elements to reflect the potential influence of cyber-attacks. In the present study, we propose and evaluate a framework for modeling the integrated effect of the spread of malware through computer networks and kinetic warfare. We employ a probabilistic learning approach, namely Bayesian Network analysis, to develop integrated combat models that characterize the spread of malware. The overall aim of the models is to predict which side will likely have the superiority at the end of the war, given the parameters that address the kinetic and cyber-effect influences of the fighting forces at the beginning.
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