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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.

This study is based on the assumption that correct interpretation of the concept of waiting for Mahdi (pbuh) the savior and understanding its functions and challenges can play an important role in developing ideal religiosity and pave the way for the widespread belief in the question of waiting for the savior because this question promotes hope in the society, a hope that is deeply rooted in man’s soul.