The Internet of Vehicles (IoV) is an emerging concept in Intelligent Transportation Systems (ITS) that aims to improve pedestrian and driver safety and traffic monitoring, But the IoV is vulnerable to various attacks. Therefore, security in the IoV is a serious issue because it directly affects the lives of the users. One of the most important attacks in the IoV is the Denial of Service (DoS) attack, which prevents access to the services of IoV and most importantly causes traffic and road accidents and the safety of users. endangers Therefore, a solution based on deep learning is proposed to detect DoS attacks in the IoV. The proposed model consists of a 10-layer convolutional neural network that can effectively detect different types of denial of service attacks. The performance of the proposed model is evaluated with real and new VDoS-LRS dataset. Experimental results show that the proposed intrusion detection system has reached a 100% accuracy rate.
janfada, Z., & Hosseini Seno, S. A. (2022). DoS attack detection in the IoV using convolutional neural network. Digital Transformation, 2(4), 1-18. doi: 10.22034/dtj.2023.394376.1087
MLA
zahra janfada; Seyed Amin Hosseini Seno. "DoS attack detection in the IoV using convolutional neural network". Digital Transformation, 2, 4, 2022, 1-18. doi: 10.22034/dtj.2023.394376.1087
HARVARD
janfada, Z., Hosseini Seno, S. A. (2022). 'DoS attack detection in the IoV using convolutional neural network', Digital Transformation, 2(4), pp. 1-18. doi: 10.22034/dtj.2023.394376.1087
VANCOUVER
janfada, Z., Hosseini Seno, S. A. DoS attack detection in the IoV using convolutional neural network. Digital Transformation, 2022; 2(4): 1-18. doi: 10.22034/dtj.2023.394376.1087