Using Neural Networks to Detect Internal Intruders in VANETs
- 作者: Ovasapyan T.D.1, Moskvin D.A.1, Kalinin M.O.1
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隶属关系:
- Peter the Great St.Petersburg Polytechnic University
- 期: 卷 52, 编号 8 (2018)
- 页面: 954-958
- 栏目: Article
- URL: https://journals.rcsi.science/0146-4116/article/view/175682
- DOI: https://doi.org/10.3103/S0146411618080199
- ID: 175682
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详细
This article considers ensuring protection of Vehicular Ad-Hoc Networks (VANET) against malicious nodes. Characteristic performance features of VANETs and threats are analyzed, and current attacks identified. The proposed approach to security provision relies on radial basis neural networks and makes it possible to identify malicious nodes by indicators of behavior.
作者简介
T. Ovasapyan
Peter the Great St.Petersburg Polytechnic University
编辑信件的主要联系方式.
Email: otd@ibks.spbstu.ru
俄罗斯联邦, St. Petersburg, 195251
D. Moskvin
Peter the Great St.Petersburg Polytechnic University
Email: max@ibks.spbstu.ru
俄罗斯联邦, St. Petersburg, 195251
M. Kalinin
Peter the Great St.Petersburg Polytechnic University
编辑信件的主要联系方式.
Email: max@ibks.spbstu.ru
俄罗斯联邦, St. Petersburg, 195251
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