Wireless sensor networks (WSNs) comprise tiny devices known as sensors. These devices are frequently employed in short-range communications and can perform various operations such as monitoring, collecting, analyzing, and processing data. WSNs do not require any infrastructure, are reliable, and can withstand adverse conditions. Sensor networks are autonomous structures in which the sensor nodes can enter or leave the network at any time instant. If the entering node is attacker node it will monitor the network operation and can cause security issues in the network that can affect communication. Existing literature presents security improvements in such networks in the form of cryptography, asymmetric techniques, key distribution, and various protocols. However, these techniques may not be effective in the case of autonomous structures and can increase computational complexity. In this paper, a convolutional technique (CT) is proposed that generates security bits using convolutional codes to prevent malicious node attacks on WSNs. Different security codes are generated at different hops and the simulation results demonstrate that the proposed technique enhances network security and reduces computational complexity compared to existing approaches.

中文翻译：

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用于增强无线传感器网络中针对恶意节点的安全性的卷积技术

无线传感器网络（WSN）包含称为传感器的微型设备。这些设备经常用于短距离通信中，并且可以执行各种操作，例如监视，收集，分析和处理数据。WSN不需要任何基础设施，是可靠的，并且可以承受不利条件。传感器网络是自治结构，传感器节点可以在其中随时进入或离开网络。如果进入节点是攻击者节点，它将监视网络运行，并可能导致网络中的安全问题，从而影响通信。现有文献以密码学，非对称技术，密钥分发和各种协议的形式提出了这种网络中的安全性改进。然而，这些技术在自主结构的情况下可能无效，并且可能会增加计算复杂性。在本文中，提出了一种卷积技术（CT），该技术使用卷积码生成安全位，以防止对WSN进行恶意节点攻击。在不同的跃点处生成不同的安全代码，并且仿真结果表明，与现有方法相比，该技术增强了网络安全性并降低了计算复杂性。