شبکه عصبی کانولوشن

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.

The main reason that data mining has become the focus of attention in the information industry is the availability of large volumes of data and the urgent need to extract useful information and knowledge from this data. In data cleaning operation, the problem of data quality is solved. One of the problems that affects the quality of data is skewed data or abnormal data. These are records whose attribute values are very different from other records. In this research, a method based on deep learning and 14-layer deep neural network on the tensorflow and cross package has been used to diagnose the abnormality and improve its performance. The data set used in this research is a data set with 2% anomalies. The accuracy of the proposed method was 97.08 and the readability and accuracy criteria were 97%. The proposed method was compared with 5 other models based on convolutional neural network and LSTM recursive network. The value of the classification evaluation criteria showed a very good improvement over the proposed method compared to traditional methods and even methods based on deep learning.