DEEP LEARNING BASED DOS AND DDOS ATTACK DETECTION METHOD IN THE HIGHWAY MONITORING SYSTEM OF IOV

Faced with the increasingly complex traffic conditions, the internet of vehicle (IoV) has become an important guarantee for improving the performance to monitor the intelligent highway network, which can realize information exchange and sharing between vehicle network, Internet, vehicle and mobile Internet. However, the increase of DoS and DDoS attacks has one of the most serious threats to the availability of IoV. Aimed at the problems of traditional intrusion detection algorithms such as training difficulties, low classification accuracy, and poor generalization ability, an efficient deep learning model CNN-BiSRU is proposed. The experiment was performed for verification in the latest CICIDS2018 data set. The results show that the model achieves higher detection accuracy, and CNN-BiSRU has a faster detection speed compared with CNN-BiLSTM.