Li Feng, Yang Yinying, Wu Jie
School of Engineering and Technology, Indiana University-Purdue University Indianapolis, Indianapolis, IN 46022, USA.
IEEE Trans Syst Man Cybern B Cybern. 2010 Jun;40(3):612-22. doi: 10.1109/TSMCB.2009.2035929. Epub 2009 Dec 22.
In mobile ad hoc networks, nodes have the inherent ability to move. Aside from conducting attacks to maximize their utility and cooperating with regular nodes to deceive them, malicious nodes get better payoffs with the ability to move. In this paper, we propose a game theoretic framework to analyze the strategy profiles for regular and malicious nodes. We model the situation as a dynamic Bayesian signaling game and analyze and present the underlining connection between nodes' best combination of actions and the cost and gain of the individual strategy. Regular nodes consistently update their beliefs based on the opponents' behavior, while malicious nodes evaluate their risk of being caught to decide when to flee. Some possible countermeasures for regular nodes that can impact malicious nodes' decisions are presented as well. An extensive analysis and simulation study shows that the proposed equilibrium strategy profile outperforms other pure or mixed strategies and proves the importance of restricting malicious nodes' advantages brought by the flee option.
在移动自组织网络中，节点具有固有的移动能力。除了发动攻击以最大化自身效用以及与正常节点协作以欺骗它们之外，恶意节点凭借移动能力能获得更好的收益。在本文中，我们提出一个博弈论框架来分析正常节点和恶意节点的策略概况。我们将这种情况建模为一个动态贝叶斯信号博弈，并分析并呈现节点最佳行动组合与个体策略的成本和收益之间的潜在联系。正常节点根据对手的行为持续更新其信念，而恶意节点评估被捕获的风险以决定何时逃离。还提出了一些可能影响恶意节点决策的正常节点应对措施。广泛的分析和仿真研究表明，所提出的均衡策略概况优于其他纯策略或混合策略，并证明了限制恶意节点因逃离选项带来的优势的重要性。
