Using Neural Networks to Detect Internal Intruders in VANETs

被引：14

作者：

Ovasapyan, T. D. ^{[1
]}

Moskvin, D. A. ^{[1
]}

Kalinin, M. O. ^{[1
]}

机构：

[1] Peter Great St Petersburg Polytech Univ, St Petersburg 195251, Russia

来源：

AUTOMATIC CONTROL AND COMPUTER SCIENCES | 2018年 / 52卷 / 08期

关键词：

Vehicular Ad-Hoc Networks; VANET; radial basis networks; Ad hoc;

D O I：

10.3103/S0146411618080199

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页码：954 / 958

页数：5

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