ROBUST ZERO TRUST SYSTEMS BASED ON COLLABORATIVE AI TO SECURE THE 6G-ENABLED VANETS

被引：0

作者：

Sedjelmaci, Hichem ^{[1
]}

Ayaida, Marwane ^{[2
]}

机构：

[1] EricssonRD, Massy, France

[2] Univ Polytech Hauts De France, Valenciennes, France

来源：

IEEE WIRELESS COMMUNICATIONS | 2025年 / 32卷 / 02期

关键词：

Adversarial machine learning - Generative adversarial networks - Vehicular ad hoc networks;

D O I：

10.1109/MWC.003.2300571

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

The research in cyber security for vehicular ad-hoc networks (VANETs) has received great attention from the scientific community. However, the intrusion detection and prevention for Sixth Generation (6G)-enabled VANETs has not attracted much attention up to this point. In this research article, we propose new robust zero trust agents based on collaborative artificial intelligence (AI) algorithms to protect the 6G-enabled VANETs from attacks targeting simultaneously the VANETs and 6G infrastructure. Collaborative AI is based on generative AI and transfer learning (TL) algorithms. Two kinds of zero trust agents are proposed - local zero trust systems (LZTS) and global zero trust systems (GZTS) - that monitor the network and infrastructure with the goal of detecting malicious behaviors promptly.

引用

页码：164 / 170

页数：7