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

共 50 条

[1] Link State Estimator for VANETs Using Neural Networks
Hamida Ikhlef
Soumia Bourebia
Ali Melit
Journal of Network and Systems Management, 2024, 32
[2] Link State Estimator for VANETs Using Neural Networks
Ikhlef, Hamida
Bourebia, Soumia
Melit, Ali
JOURNAL OF NETWORK AND SYSTEMS MANAGEMENT, 2024, 32 (01)
[3] Detect smart intruders in sensor networks by creating network dynamics
Tian, Jie
Wang, Guiling
Yan, Tan
Zhang, Wensheng
COMPUTER NETWORKS, 2014, 62 : 182 - 196
[4] Using Neural Networks to Detect Emotions in Documents
Kumar, Keshav
Mittra, Yash
PROCEEDINGS OF SECOND INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTER ENGINEERING AND COMMUNICATION SYSTEMS, ICACECS 2021, 2022, : 191 - 198
[5] Using of Neural Networks to Detect Intrusion in Business
Grediaga, Angel
Brotons, Francisco
Ledesma, Bernardo
Ivorra, Adrian
BUSINESS TRANSFORMATION THROUGH INNOVATION AND KNOWLEDGE MANAGEMENT: AN ACADEMIC PERSPECTIVE, VOLS 3 AND 4, 2010, : 2220 - 2225
[6] Kernel Methods to detect Intruders
Beghdad, Rachid
Ziraoui, Youcef
Kouache, Nassim
3RD INTERNATIONAL CONFERENCE ON CONTROL, ENGINEERING & INFORMATION TECHNOLOGY (CEIT 2015), 2015,
[7] Using convolutional neural networks to detect GNSS multipath
Guillard, Anthony
Thevenon, Paul
Milner, Carl
FRONTIERS IN ROBOTICS AND AI, 2023, 10
[8] Detect Surface Cracks Using Explainable Neural Networks
Bolliger, Christine
Lenzi, Vasco
e-Journal of Nondestructive Testing, 2022, 27 (09):
[9] Using Neural Networks to Detect Errors in Coding Exams
Stando, Jacek
INFORMATICS ENGINEERING AND INFORMATION SCIENCE, PT II, 2011, 252 : 329 - 336
[10] Predictive Modeling of Signal Degradation in Urban VANETs Using Artificial Neural Networks
Muktar, Bappa
Fono, Vincent
Zongo, Meyo
ELECTRONICS, 2023, 12 (18)

← 1 2 3 4 5 →