Vehicular ad hoc networks (VANETs) enable wireless communication among Vehicles and Infrastructures. Connected vehicles are promising in Intelligent Transportation Systems (ITSs) and smart cities. The main ob-jective of VANET is to improve the safety, comfort, driving efficiency and waiting time on the road. VANET is unlike other ad hoc networks due to its unique characteristics and high mobility. However, it is vulnerable to various security attacks due to the lack of centralized infrastructure. This is a serious threat to the safety of road traffic. The Controller Area Network (CAN) is a bus communication protocol which defines a standard for reliable and efficient transmission between in-vehicle parts simultaneously. The message moves through CAN bus from one node to another node, but it does not have information about the source and destination address for authentication. Thus, the attacker can easily inject any message to lead to system faults. In this paper, we present machine learning techniques to cluster and classify the intrusions in VANET by KNN and SVM algorithms. The intrusion detection technique relies on the analysis of the offset ratio and time interval between the messages request and the response in the CAN.
References
[1]
Qu, F.Z., Wu, Z.H., Wang, F.-Y. and Cho, W. (2015) A Security and Privacy Review of VANETs. IEEE Transactions on Intelligent Transportation Systems, 16, 2985-2996. https://doi.org/10.1109/TITS.2015.2439292
[2]
Razzaque, M.A., A. S.S. and Cheraghi, S.M. (2013) Security and Privacy in Vehicular Ad-Hoc Networks: Survey and the Road Ahead. Springer, Berlin, Heidelberg, 107-132.
[3]
Rivas, D.A., Barceló-Ordinas, J.M., Zapata, M.G. and Morillo-Pozo, J.D. (2011) Security on VANETs: Privacy, Misbehaving Nodes, False Information and Secure Data Aggregation. Journal of Network and Computer Applications, 34, 1942-1955. https://doi.org/10.1016/j.jnca.2011.07.006
[4]
Sakiz, F. and Sen, S. (2017) A Survey of Attacks and Detection Mechanisms on Intelligent Transportation Systems: VANETs and IoV. Ad Hoc Networks, 61, 33-50. https://doi.org/10.1016/j.adhoc.2017.03.006
[5]
Abboud, K., Omar, H.A. and Zhuang, W. (2016) Interworking of DSRC and Cellular Network Technologies for V2X Communications: A Survey. IEEE Transactions on Vehicular Technology, 65, 9457-9470. https://doi.org/10.1109/TVT.2016.2591558
[6]
Engoulou, R.G., Bellaïche, M., Pierre, S. and Quintero, A. (2014) VANET Security Surveys. Computer Communications, 44, 1-13. https://doi.org/10.1016/j.comcom.2014.02.020
[7]
Knapik, P., Schoch, E. and Kargl, F. (2013) Electronic Decal: A Security Function Based on V2X Communication. Proceedings of VTC, Dresden, 2-5 June 2013, 1-14.
[8]
Wedel, J.W., Schünemann, B. and Radusch, I. (2009) V2X-Based Traffic Congestion Recognition and Avoidance. 10th International Symposium on Pervasive Systems, Algorithms, and Networks (ISPAN), Kaohsiung, 14-16 December 2009, 637-641.
[9]
Hong, J. (2016) Cyber Security Issues in Connected Vehicle of Intelligent Transport System. Indian Journal of Science and Technology, 9, No. 24. https://doi.org/10.17485/ijst/2016/v9i24/96027
[10]
Kleberger, P., Olovsson, T. and Jonsson, E. (2011) Security Aspects of the In-Vehicle Network in the Connected Car. Proceedings of IEEE IV, Baden-Baden, 5-9 June 2011, 528-533. https://doi.org/10.1109/IVS.2011.5940525
[11]
Miller, C. and Valasek, C. (2015) Remote Exploitation of an Unaltered Passenger Vehicle. Black Hat USA.
[12]
Kelion, L. (2016) Nissan Leaf electric Cars Hack Vulnerability Disclosed. BBC News.
[13]
Kong, F., Zhang, L., Zeng, J. and Zhang, Y. (2007) Automatic Measurement and Control System for Vehicle ECU Based on CAN Bus. IEEE International Conference on Automation and Logistics, Jinan, 18-21 August 2007, 964-968.
[14]
Lawrenz, W. (1997) CAN System Engineering. From Theory to Practical Applications, New York. https://doi.org/10.1007/978-1-4612-1834-0
[15]
Cebi, A., Guvenc, L., Demirci, M., Karadeniz, C.K., Kanar, K. and Guraslan, E. (2005) A Low Cost, Portable Engine Electronic Control Unit Hardware-in-the-Loop Test System. Proceedings of the IEEE International Symposium on Industrial Electronics, 1, 293-298.
[16]
Tuohy, S., Glavin, M., Hughes, C., Jones, E., Trivedi, M. and Kilmartin, L. (2015) Intra-Vehicle Networks: A Review. IEEE Transactions on Intelligent Transportation Systems, 2, 534-554. https://doi.org/10.1109/TITS.2014.2320605
[17]
Torrent-Moreno, M., Mittag, J., Santi, P. and Hartenstein, H. (2009) Vehicle-to-Vehicle Communication: Fair Transmit Power Control for Safety-Critical Information. IEEE Transactions on Vehicular Technology, 58, 3684-3703. https://doi.org/10.1109/TVT.2009.2017545
[18]
Tchamna, R. and Youn, I. (2013) Yaw Rate and Side-Slip Control Considering Vehicle Longitudinal Dynamics. International Journal of Automotive Technology, 14, 53-60. https://doi.org/10.1007/s12239-013-0007-1
[19]
Tsugawa, S. (2002) Inter-Vehicle Communications and Their Applications to Intelligent Vehicles: An Overview. Intelligent Vehicle Symposium, Versailles, 17-21 June 2002, 564-569.
[20]
Jin, W.L. and Recker, W.W. (2006) Instantaneous Information Propagation in a Traffic Stream through Inter-Vehicle Communication. Transportation Research Part B: Methodological, 40, 230-250.
[21]
Kesting, A., Treiber, M. and Helbing, D. (2010) Connectivity Statistics of Store-and-Forward Intervehicle Communication. IEEE Transactions on Intelligent Transportation System, 11, 172-181. https://doi.org/10.1109/TITS.2009.2037924
[22]
Johansson, K.H., Aurngren, M. and Nielsen, L. (2005) Vehicle Applications of Controller Area Network. In: Hristu-Varsakelis, D. and Levine, W.S., Eds., Handbook of Networked and Embedded Control Systems, Springer, Berlin, 741-765.
Bhatia, N. (2010) Survey of Nearest Neighbor Techniques.
[25]
Song, H.M., Kim, H.R. and Kim, H.K. (2016) Intrusion Detection System Based on the Analysis of Time Intervals of Can Messages for In-Vehicle Network. International Conference on Information Networking, Kota Kinabalu, 13-15 January 2016, 63-68. https://doi.org/10.1109/ICOIN.2016.7427089
[26]
Miller, C. and Valasek, C. (2013) Adventures in Automotive Networks and Control Units. Tech. Rep., IOActive Labs Research.
[27]
Miller, C. and Valasek, C. (2014) A Survey of Remote Automotive Attack Surfaces. Tech. Rep., IOActive Labs Research.
[28]
Marchetti, M. and Stabili, D. (2017) Anomaly Detection of CAN Bus Messages through Analysis of ID Sequences. IEEE Intelligent Vehicles Symposium (IV), Los Angeles, CA, 1577-1583.
[29]
Taylor, A., Japkowicz, N. and Leblanc, S. (2015) Frequency-Based Anomaly Detection for the Automotive CAN Bus. World Congress on Industrial Control Systems Security, London, 14-16 December 2015, 45-49. https://doi.org/10.1109/WCICSS.2015.7420322
[30]
Larson, U.E., Nilsson, D.K. and Jonsson, E. (2008) An Approach to Specification-Based Attack Detection for In-Vehicle Networks. The IEEE Intelligent Vehicles Symposium, Eindhoven, 4-6 June 2008, 220-225.
[31]
Wang, C., Zhao, Z., Gong, L., Zhu, L., Liu, Z. and Cheng, X. (2018) A Distributed Anomaly Detection System for In-Vehicle Network Using HTM. IEEE Access, 6, 9091-9098.
[32]
Abbott-McCune, S. and Shay, L.A. (2016) Intrusion Prevention System of Automotive Network CAN Bus. IEEE International Carnahan Conference on Security Technology (ICCST), Orlando, FL, 1-8.
[33]
Farsi, M., Ratcliff, K. and Barbosa, M. (1999) An Overview of Controller Area Network. Computing and Control Engineering Journal, 10, 113-120. https://doi.org/10.1049/cce:19990304
[34]
Kyong-Tak, C. and Shin, K.G. (2016) Fingerprinting Electronic Control Units for Vehicle Intrusion Detection. 25th USENIX Security Symposium, Austin, TX, 911-927.
[35]
Wang, Q. and Sawhney, S. (2014) VeCure: A Practical Security Framework to Protect the CAN Bus of Vehicles. International Conference on the Internet of Things, Cambridge, 13-18. https://doi.org/10.1109/IOT.2014.7030108
[36]
Hu, J., Yu, X., Qiu, D. and Chen, H. (2009) A Simple and Efficient Hidden Markov Model Scheme for Host-Based Anomaly Intrusion Detection. IEEE Network, 23, 42-47.
[37]
Muter, M. and Asaj, N. (2011) Entropy-Based Anomaly Detection for In-Vehicle Networks. Intelligent Vehicles Symposium, Baden-Baden, 5-9 June 2011, 1110-1115. https://doi.org/10.1109/IVS.2011.5940552
[38]
Markovitz, M. and Wool, A. (2015) Field Classification, Modeling and Anomaly Detection in Unknown CAN Bus Networks.
[39]
Taylor, S.L. and Japckowicz, N. (2016) Anomaly Detection in Automobile Control Network Data with Long Short-Term Memory Networks. IEEE International Conference on Data Science and Advanced Analytics, Montreal, QC, 130-139.
[40]
Hoppe, T., Kiltz, S. and Dittmann, J. (2008) Security Threats to Automotive CAN Networks—Practical Examples and Selected Short-Term Countermeasures. International Conference on Computer Safety, Reliability, and Security, Newcastle upon Tyne, 22-25 September 2008, 235-248.
[41]
Muter, M., Groll, A. and Freiling, F.C. (2010) A Structured Approach to Anomaly Detection for In-Vehicle Networks. 6th Information Assurance and Security, Atlanta, GA, 92-98.
[42]
Ghaleb, F.A., Zainal, A., Rassam, M.A. and Mohammed, F. (2017) An Effective Misbehavior Detection Model Using Artificial Neural Network for Vehicular Ad Hoc Network Applications. IEEE Conference on Application, Information and Network Security, Miri, 13-14 December 2017, 13-18.
[43]
Hortelano, J., Ruiz, J.C. and Manzoni, P. (2010) Evaluating the Usefulness of Watchdogs for Intrusion Detection in VANETs.
[44]
Van Herrewege, A., Singelee, D. and Verbauwhede, I. (2011) Canauth-a Simple, backward Compatible Broadcast Authentication Protocol for Can Bus. ECRYPT Workshop on Lightweight Cryptography, November 2011, 229-235.
[45]
Matsumoto, T., Hata, M., Tanabe, M., Yoshioka, K. and Oishi, K. (2012) A Method of Preventing Unauthorized Data Transmission in Controller Area Network. 75th Vehicular Technology Conference, Yokohama, 1-5.
[46]
Hacking and Countermeasure Research Lab (2017) CAN-Intrusion-Dataset. http://ocslab.hksecurity.net/Dataset/CAN-intrusion-dataset
[47]
Joachims, T. (2002) Learning to Classify Text Using Support Vector Machines: Methods, Theory and Algorithms (Vol. 186). Kluwer Academic Publishers, Norwell. https://doi.org/10.1007/978-1-4615-0907-3
[48]
Ben-Hur, A. and Weston, J. (2010) A User’s Guide to Support Vector Machines. In: Data Mining Techniques for the Life Sciences, Humana Press, 223-239. https://doi.org/10.1007/978-1-60327-241-4_13
