Threat Analysis of Cyber Security in Wireless Adhoc Networks Using Hybrid Neural Network Model
Roman Demidov, Peter D. Zegzhda, Maxim Kalinin · Automatic Control and Computer Sciences · 2018
Abstract The article discusses the problem of analysis of cybersecurity threats in wireless ad hoc networks—VANET, FANET, MARINET, MANET, WSN. The problem of neural network approximation of the function of cyber threat existence in the system is formulated. The parameters of the neural network model were optimized according to the likelihood maximization criterion on the training data set. A hybrid neural network based on recurrent and graph convolutional neural networks is proposed as a solution architecture.