Multi-Layer Perceptron Based Fuzzy Logic Technique for Detection of Attacks in VANETS

Shubham Shetty, M. D H
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Abstract

Vehicles are imparting messages with other vehicles in ad hoc network, which is referred as VANET communication. Due to the emerging of new technologies as part of industry 4.0 the VANET as frequently used in communication applications. But in this cyber attacks are increased in the VANETS communications. Scholars have proposed different solutions and algorithms to find the attacks. Here we have proposed a method that uses artificial intelligence. The proposed method is the combination of Neural Network based Multilayer Perceptron (MLP) trained Fuzzy Logic System procedure to spot unusual behavior of automobiles in the ad hoc network. To validate the results time of detection, positive rate, and ratio of detection is used. The outcome will giv the better performance existing methods.
基于多层感知机的模糊逻辑VANETS攻击检测技术
车辆在自组织网络中与其他车辆传递信息,这被称为VANET通信。由于作为工业4.0一部分的新技术的出现,VANET在通信应用中被频繁使用。但在这种情况下,VANETS通信中的网络攻击有所增加。学者们提出了不同的解决方案和算法来寻找攻击。这里我们提出了一种使用人工智能的方法。该方法结合基于神经网络的多层感知器(MLP)训练的模糊逻辑系统程序来识别自组织网络中的汽车异常行为。用检测时间、阳性率和检出率来验证结果。结果表明,现有方法具有更好的性能。
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