Computer Science

Computer Science ›› 2021, Vol. 48 ›› Issue (6A): 518-523.doi: 10.11896/jsjkx.200700129

• Information Security • Previous Articles     Next Articles

Distributed Combination Deep Learning Intrusion Detection Method for Internet of Vehicles Based on Spark

YU Jian-ye1, QI Yong1, WANG Bao-zhuo2   

  1. 1 School of Computer Science and Engineering,Nanjing University of Science & Technology,Nanjing 210094,China
    2 Jiangsu Zhongda Intelligent Transportation Industry Research Institute Co.Ltd,Changzhou,Jiangsu 213000,China
  • Online:2021-06-10 Published:2021-06-17
  • About author:YU Jian-ye,born in 1993,postgraduate.His main research interests include information security.
    QI Yong,born in 1970,Ph.D,professor,Ph.D supervisor,is a member of China Computer Federation.His main research interests include traffic bigdata,security of internet of vehicles.
  • Supported by:
    National Key Research and Development Program Intergovernmental Key Items for International Science and Technology Innovation Cooperation of China(2016YFE0108000),Ministry of Industry and Information Technology Network Security Technology Application Pilot Demonstration Project:Intelligent Networked Vehicle-road Cooperative Communication Safety Research Application Platform,Key Research and Development Program of Jiangsu Province China(BE2017163) and JiangSu Transportation Technology Project(2018Y45).

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Abstract: With the application of 5G and other technologies in the field of Internet of vehicles,intrusion detection as an important detection tool for information security of Internet of vehicles plays an increasingly important role.Due to the rapid change of the structure of the Internet of vehicles,large data flow,complex and diverse forms of intrusion,traditional detection unable ensure the accuracy and real-time requirements,and unable be directly applied to the Internet of vehicles.To solve these problems,this paper proposes a distributed combination deep learning intrusion detection method for Internet of vehicles based on Apache spark framework.By constructing spark cluster,the deep learning CNN and LSTM are combined to extract intrusion features and detect data,and find abnormal behaviors from large-scale Internet of vehicles data traffic.Experimental results show that,compared with other existing models,the proposed method can achieve 20.1s in time and 99.7% in accuracy.

Key words: Apache Spark, CNN, Internet of vehicles, Intrusion detection, LSTM

CLC Number: 

  • TP302.7
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