manet中的信誉路由

P. Singh, K. Kar, C. Kamhoua
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引用次数: 3

摘要

在这项工作中,我们提出了一种信任计算方法,直接信任计算,并利用它来设计一个面向manet的声誉路由模型(RRM)。我们利用该路由框架在不改变原始协议或增加其开销的情况下减轻OLSR中黑洞攻击的影响。我们的解决方案可以隔离网络中的不良节点,并选择最可信的路径来路由数据包。我们通过在公共开放研究仿真器(CORE)上模拟静态和动态拓扑的网络场景来评估我们模型的性能。从我们的发现中可以观察到,在存在恶意节点的情况下,RRM在数据包传输速率方面大大优于原始OLSR协议,除非移动性非常高。因此,RRM对于减轻黑洞攻击在manet中的影响非常有用,特别是在低移动性的情况下。
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Reputation Routing in MANETs
In this work we present a trust computation method, Direct Trust Computation, and utilize it to design a Reputation Routing Model (RRM) for MANETs. We utilize this routing framework to mitigate the effect of blackhole attacks in OLSR without altering the original protocol or increasing its overhead. Our solution can isolate bad nodes in the network and select the most trusted path to route packets. We evaluate the performance of our model by emulating network scenarios on Common Open Research Emulator (CORE) for static as well as dynamic topologies. From our findings, it is observed that RRM substantially outperforms the original OLSR protocol in terms of packet delivery rates in presence of a malicious node, unless the mobility rate is quite high. RRM is therefore useful in mitigating the effect of blackhole attacks in MANETs, particularly in low mobility scenarios.
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