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Malicious node and malicious observer node detection system in MANETs

机译:恶意节点和恶意观察者节点检测系统在船只中

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Mobile ad-hoc networks (MANETs) are generally organized without infrastructure. Hence, they are moderately defenseless to malicious active and passive attackers that target to damage and trace the data transmission direction. Therefore, the malicious node (MN) (active attacker) and malicious observer node (MON) (passive attacker) detection system (MODS) is an important challenge in MANETs. It is quite easy to observe a node that induces malicious activities in other nodes, but it is very difficult to identify a node that passively observes and misuses network data. In this work, we propose context-free grammar (CFG) and Fibonacci-Pascal triangle (FPT) methods are in MANETs. Here, the MODS used CFG and FPT methods. The CFG is used to isolate the MN, and FPT conceals the real information of the mobile nodes. The data path is protected from mobile MONs by sending a secret message to the destination. The significant application of this scheme is enhancing military security. The simulation results demonstrate that the dynamic estimation of the quality-of-service metrics improves the 45% throughput in the network.
机译:移动ad-hoc网络(MANET)通常在没有基础架构的情况下组织。因此,他们对恶意活跃和被动攻击者的恶意无政可无于迫切,这些攻击者旨在损坏和跟踪数据传输方向。因此,恶意节点(MN)(主动攻击者)和恶意观察者节点(MON)检测系统(MODS)是舰队中的重要挑战。很容易观察在其他节点中诱导恶意活动的节点,但是很难识别被动地观察和误用网络数据的节点。在这项工作中,我们提出了无内容语法(CFG)和斐波纳契 - Pascal三角形(FPT)方法是船只。在这里,MODS使用CFG和FPT方法。 CFG用于隔离Mn,FPT隐藏移动节点的真实信息。通过向目的地发送秘密消息来保护数据路径从移动MONS保护。该计划的重大应用正在提高军事安全。仿真结果表明,服务质量指标的动态估计可以提高网络中的45%吞吐量。

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