论文标题
一种新颖的对策技术，可保护WSN免受使用Firefly和Hopfield神经网络（HNN）算法的拒绝拒绝攻击
A novel countermeasure technique to protect WSN against denial-of-sleep attacks using firefly and Hopfield neural network (HNN) algorithms
论文作者
论文摘要
无线传感器网络（WSN）包含许多节点，其主要目标是监视和控制环境。此外，传感器节点根据网络使用分布。在这种类型的网络中，最重要的问题之一是传感器节点的能耗。在固定链接网络中，接近水槽的节点是传递其他节点数据下沉的接口。这会导致传感器的能耗迅速减少。因此，网络的寿命下降。由于其弱点，传感器节点容易受到几种威胁的影响，其中之一是拒绝下滑攻击（DOSA）威胁WSN。因此，DOSA是指从输入节能和睡眠模式的节点来维持这些节点中的能量损失。在本文中，基于移动水槽，基于Leach的萤火虫算法和Hopfield神经网络（WSN-FAHN）提出了一种混合方法。因此，移动水槽既应用于改善能源消耗又会增加网络寿命。提出了萤火虫算法以群集节点并在两个级别进行认证以防止DOSA。此外，Hopfield神经网络检测到接收器移动的方向路线以发送CH的数据。此外，这里通过在NS-2环境中进行的广泛模拟来评估WSN-FAHN技术。与基于绩效指标（例如数据包输送率（PDR），平均吞吐量，检测率和网络寿命）相比，模拟结果与当代方案相比，WSN-FAHN程序优越性与当代方案相比证明了优势。
Wireless sensor networks (WSNs) contain numerous nodes that their main goals are to monitor and control environments. Also, sensor nodes distribute based on network usage. One of the most significant issues in this type of network is the energy consumption of sensor nodes. In fixed-sink networks, nodes which are near the sink act as an interface to transfer data of other nodes to sink. This causes the energy consumption of sensors reduces rapidly. Therefore, the lifetime of the network declines. Sensor nodes owing to their weaknesses are susceptible to several threats, one of which is denial-of-sleep attack (DoSA) threatening WSN. Hence, the DoSA refers to the energy loss in these nodes by maintaining the nodes from entering energy-saving and sleep mode. In this paper, a hybrid approach is proposed based on mobile sink, firefly algorithm based on leach, and Hopfield neural network (WSN-FAHN). Thus, mobile sink is applied to both improve energy consumption and increase network lifetime. Firefly algorithm is proposed to cluster nodes and authenticate in two levels to prevent from DoSA. In addition, Hopfield neural network detects the direction route of the sink movement to send data of CH. Furthermore, here WSN-FAHN technique is assessed through wide simulations performed in the NS-2 environment. The WSN-FAHN procedure superiority is demonstrated by simulation outcomes in comparison with contemporary schemes based on performance metrics like packet delivery ratio (PDR), average throughput, detection ratio, and network lifetime while decreasing the average residual energy.
