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
关键词
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
收藏
页码:164 / 170
页数:7
相关论文
共 50 条
  • [1] Secure and Efficient Message Authentication Scheme for 6G-Enabled VANETs
    Liao, Longxia
    Zhao, Junhui
    Hu, Huanhuan
    Sun, Xiaoke
    ELECTRONICS, 2022, 11 (15)
  • [2] Blockchain-enabled Zero Trust-based Secure and Energy Efficient scheme for 6G-enabled UASNs
    Altaf Hussain
    Shuaiyong Li
    Tariq Hussain
    Razaz Waheeb Attar
    Ahmed Alhomoud
    Reem Alsagri
    Ahmad Ali Alzubi
    Journal of Cloud Computing, 14 (1)
  • [3] Blockchain and AI for Collaborative Intrusion Detection in 6G-enabled IoT Networks
    Chelghoum, Massinissa
    Bendiab, Gueltoum
    Labiod, Mohamed Aymen
    Benmohammed, Mohamed
    Shiaeles, Stavros
    Mellouk, Abdelhamid
    2024 IEEE 25TH INTERNATIONAL CONFERENCE ON HIGH PERFORMANCE SWITCHING AND ROUTING, HPSR 2024, 2024, : 179 - 184
  • [4] Federated learning for 6G-enabled secure communication systems: a comprehensive survey
    Sirohi, Deepika
    Kumar, Neeraj
    Rana, Prashant Singh
    Tanwar, Sudeep
    Iqbal, Rahat
    Hijjii, Mohammad
    ARTIFICIAL INTELLIGENCE REVIEW, 2023, 56 (10) : 11297 - 11389
  • [5] Federated learning for 6G-enabled secure communication systems: a comprehensive survey
    Deepika Sirohi
    Neeraj Kumar
    Prashant Singh Rana
    Sudeep Tanwar
    Rahat Iqbal
    Mohammad Hijjii
    Artificial Intelligence Review, 2023, 56 : 11297 - 11389
  • [6] A Zero-Trust Authentication Scheme With Access Control for 6G-Enabled IoT Environments
    Son, Seunghwan
    Kwon, Deokkyu
    Lee, Sangwoo
    Kwon, Hyeokchan
    Park, Youngho
    IEEE ACCESS, 2024, 12 : 154066 - 154079
  • [7] Attribute-Based Data Sharing Scheme Using Blockchain for 6G-Enabled VANETs
    Guo, Zhenzhen
    Wang, Gaoli
    Li, Yingxin
    Ni, Jianqiang
    Zhang, Guoyan
    IEEE TRANSACTIONS ON MOBILE COMPUTING, 2024, 23 (04) : 3343 - 3360
  • [8] AI-Driven Collaborative Resource Allocation for Task Execution in 6G-Enabled Massive IoT
    Lin, Kai
    Li, Yihui
    Zhang, Qiang
    Fortino, Giancarlo
    IEEE INTERNET OF THINGS JOURNAL, 2021, 8 (07) : 5264 - 5273
  • [9] A secure blockchain system for Internet of Vehicles based on 6G-enabled Network in Box
    Yi, Haibo
    COMPUTER COMMUNICATIONS, 2022, 186 : 45 - 50
  • [10] Trusted Explainable AI for 6G-Enabled Edge Cloud Ecosystem
    Garg, Sahil
    Kaur, Kuljeet
    Aujla, Gagangeet Singh
    Kaddoum, Georges
    Garigipati, Prasad
    Guizani, Mohsen
    IEEE WIRELESS COMMUNICATIONS, 2023, 30 (03) : 163 - 170