Recognition of grey hole attacks in wireless sensor networks using fuzzy logic in IoT
Recognition of grey hole attacks in wireless sensor networks using fuzzy logic in IoT
复制标题
使用物联网中的模糊逻辑识别无线传感器网络中的灰洞攻击
DOI：
10.1002/ett.3873
复制
发表时间：
2020
影响因子：
3.6
通讯作者：
Yulan Tang
中科院分区：
文献类型：
--
作者：
Q. Ye;Yufei Wang;Maolong Xi;Yulan Tang
由于物联网（IoT）中的设备始终与稳定的互联网连接互连，因此它们很容易受到攻击。在灰洞攻击中，恶意节点充当中央控制器，从所有节点获取数据，并根据自己的意愿丢弃和更改数据包。通过这种方式，灰洞攻击改变了物联网的核心概念，使不同的设备能够相互通信。为了防止灰洞攻击并实现物联网设备之间的有效通信，本文引入了模糊概念。以前的方法不能很好地识别出不计其数的灰洞攻击。模糊引擎通过生成的规则识别网络中发生的可疑活动，识别恶意节点并立即停止其功能。仿真实验进行了准确性，延迟，能量消耗，分组投递率和吞吐量，并与所提出的算法，模拟行为建模（ABM），和其他以前的技术进行了对比。所提出的系统提供了一个准确率为45%，数据包交付率为78%，并减少了35.6%的能源消耗相比，以前的ABM方法。仿真结果表明，提出的模糊灰色检测技术是检测灰洞攻击和提高网络性能的有效方案。
Since the devices in Internet of Things (IoT) are always interconnected with a stable Internet connection, they are prone to attacks. In the grey hole attack, a malicious node acts as a central controller to obtain data from all the nodes and it drops and alters the data packets as per its wish. In this way, the grey hole attack alters the core concept of the IoT, which enables different devices to communicate with each other. To prevent the grey hole attack and enable efficient communication between the IoT devices, a fuzzy concept is introduced in this article. Previous methods have not proficient in spotting uncountable kinds of grey hole attacks. The fuzzy engine identifies the suspicious activity that takes place in the network by the rules generated and identifies the malicious node and stops its function immediately. The simulation experimentation is carried out for accuracy, delay, energy consumption, packet delivery ratio and throughput, and the simulation contrasts with the proposed algorithm, analog behavioral modeling (ABM), and other previous techniques. The proposed system provides an accuracy rate of 45%, a packet delivery ratio of 78%, and reduced energy consumption of 35.6% compared to the previous ABM approach. Simulation outputs showed that the proposed fuzzy grey detection technique is a proficient scheme for detecting grey hole attacks and improving network capability.