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Automatic Control and Computer Sciences

Erschienen in:

01.12.2019

Application of an Artificial Neural Network for Detection of Attacks in VANETs

verfasst von: E. V. Malyshev, D. A. Moskvin, D. P. Zegzhda

Erschienen in: Automatic Control and Computer Sciences | Ausgabe 8/2019

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Abstract

This work contains results of developing an approach for detecting routing attacks in VANET networks using an artificial neural network. In the course of this work, such research methods as analysis and modeling were used to select the most promising approach for identifying routing attacks, as well as to develop a mock-up of a software system that detects Gray Hole attacks in VANETs. According to the results of experimental studies, the effectiveness of the developed software was evaluated.

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Number of passenger cars and commercial vehicles in use worldwide from 2006 to 2015 in (1,000 units). https://www.statista.com/statistics/281134/number-of-vehicles-in-use-worldwide. Accessed May 1, 2018.

How many cars in the world. https://www.drivesurfing.com/en/article/7/how-many-cars-are-there-in-the-world. Accessed April 23, 2018.

Statistics of car crashes for 2018 in Russia. http://avtopravozashita.ru/dtp/statistika-dtp-v-rossii-za-2016-god.html. Accessed May 10, 2018.

SON Networks—Bauman National Library. https://ru.bmstu.wiki/C%D0%B5%D1%82%D0%B8_SON. Accessed May 1, 2018.

Kalinin, M.O. and Minin, A.A., Security threats in mobile dynamic networks VANET/MANET, S.-Peterburgskaya Mezhdunarod. Konf. “Regional’naya Informatika (RI-2016) (St. Petersburg International Conf. Regional Informatics (RI-2016)), St. Petersburg, 2016, p. 180.

Demidov, R.A., Zegzhda, P.D., and Kalinin, M.O., Threat analysis of cyber security in wireless adhoc networks using hybrid neural network model, Autom. Control Comput. Sci., 2018, vol. 52, no. 8, pp. 971–976.CrossRef

Ad hoc On-Demand Distance Vector (AODV) Routing. https://tools.ietf.org/html/rfc3561. Accessed May 21, 2018.

Zegzhda, P., Zegzhda, D., Vasiliev, Y., and Belenko, V., Software defined security for vehicular ad hoc networks, Proceedings of 7th International Conference on Information and Communication Technology Convergence (ICTC2016), Jeju Island, 2016, pp. 533–537. https://doi.org/10.1109/ICTC.2016.7763528

Kalinin, M.O., Krundyshev, V.M., and Semianov, P.V., Architectures for building secure vehicular networks based on sdn technology, Autom. Control Comput. Sci., 2017, vol. 51, no. 8, pp. 907–914.CrossRef

10.

Kalinin, M.O., Zubkov, E.A., Suprun, A.F., and Pechenkin, A.I., Prevention of attacks on dynamic routing in self-organizing adhoc networks using swarm intelligence, Autom. Control Comput. Sci., 2018, vol. 52, no. 8, pp. 977–983.CrossRef

Titel: Application of an Artificial Neural Network for Detection of Attacks in VANETs
verfasst von: E. V. Malyshev
D. A. Moskvin
D. P. Zegzhda
Publikationsdatum: 01.12.2019
Verlag: Pleiades Publishing
Erschienen in: Automatic Control and Computer Sciences / Ausgabe 8/2019
Print ISSN: 0146-4116
Elektronische ISSN: 1558-108X
DOI: https://doi.org/10.3103/S0146411619080194

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