Trusted Explainable AI for 6G-Enabled Edge Cloud Ecosystem

被引:7
作者
Garg, Sahil [1 ,2 ]
Kaur, Kuljeet [2 ]
Aujla, Gagangeet Singh [4 ]
Kaddoum, Georges [2 ,3 ]
Garigipati, Prasad [5 ]
Guizani, Mohsen [6 ]
机构
[1] Ultra Commun, Mont Royal, PQ, Canada
[2] Ecole Technol Super, Montreal, PQ, Canada
[3] Lebanese Amer Univ, Beirut, Lebanon
[4] Univ Durham, Durham, England
[5] Ericsson, Mississauga, ON, Canada
[6] Mohamed Bin Zayed Univ Artificial Intelligence, Abu Dhabi, U Arab Emirates
关键词
6G mobile communication; Privacy; Computer architecture; Telecommunications; Security; Artificial intelligence; Vehicle dynamics; INTELLIGENCE; SECURITY;
D O I
10.1109/MWC.016.220047
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
The journey to the next decade of smart cellular connectivity, sixth-generation (6G) networks, has already begun, even though 6G is still in its nascent stages and far from its deployment. In telecommunications, 6G networks have gained the attention of the industry and academia. 6G is planned to succeed the 5G standard with almost 100 times greater speed. One of the exciting features of 6G is Edge Intelligence (EI), which is the coupling of Edge Computing with Artificial Intelligence (AI). So far, EI has yet to be a component of the existing and predecessor communication standards; thus, 6G will open up many opportunities with its deployment in the future. Nonetheless, integration of 6G with EI, in other words, Edge and AI, is also susceptible to various challenges, particularly security and privacy. Therefore, this article proposes a trusted AI-enabled intelligent architecture for the 6G-envisioned Edge Computing platform. The proposed architecture is based on the Explainable AI concept and is mainly used to ensure the security and privacy of the future 6G networks at the Edge. Following this, the work presents a detailed case study of employing the proposed framework. The preliminary discussion indicates some exciting findings and lays the foundation for future research. In a nutshell, the proposed architecture can be extended to different verticals, including, but not limited to, life-critical systems, like e-healthcare, autonomous vehicles, and traffic monitoring.
引用
收藏
页码:163 / 170
页数:8
相关论文
共 50 条
  • [31] An intelligent edge enabled 6G-flying ad-hoc network ecosystem for precision agriculture
    Mukherjee, Amartya
    Panja, Ayan Kumar
    Dey, Nilanjan
    Crespo, Ruben Gonzalez
    EXPERT SYSTEMS, 2023, 40 (04)
  • [32] A Dispersed Federated Learning Framework for 6G-Enabled Autonomous Driving Cars
    Khan, Latif U.
    Tun, Yan Kyaw
    Alsenwi, Madyan
    Imran, Muhammad
    Han, Zhu
    Hong, Choong Seon
    IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING, 2024, 11 (06): : 5656 - 5667
  • [33] Designing Authenticated Key Management Scheme in 6G-Enabled Network in a Box Deployed for Industrial Applications
    Wazid, Mohammad
    Das, Ashok Kumar
    Kumar, Neeraj
    Alazab, Mamoun
    IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2021, 17 (10) : 7174 - 7184
  • [34] Energy-Efficient Fog Computing for 6G-Enabled Massive IoT: Recent Trends and Future Opportunities
    Malik, Usman Mahmood
    Javed, Muhammad Awais
    Zeadally, Sherali
    ul Islam, Saif
    IEEE INTERNET OF THINGS JOURNAL, 2022, 9 (16) : 14572 - 14594
  • [35] A Novel Hybrid Quantum-Crypto Standard to Enhance Security and Resilience in 6G-Enabled IoT Networks
    Singamaneni, Kranthi Kumar
    Budati, Anil Kumar
    Islam, Shayla
    Kolandaisamy, Raenu A. L.
    Muhammad, Ghulam
    IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2025, 18 : 7876 - 7891
  • [36] Cost-Effective Authenticated Solution (CAS) for 6G-Enabled Artificial Intelligence of Medical Things (AIoMT)
    Mahmood, Khalid
    Obaidat, Mohammad S.
    Shamshad, Salman
    Alenazi, Mohammed J. F.
    Kumar, Gulshan
    Anisi, Mohammad Hossein
    Conti, Mauro
    IEEE INTERNET OF THINGS JOURNAL, 2024, 11 (13): : 23977 - 23984
  • [37] Hierarchical Aerial Computing for Task Offloading and Resource Allocation in 6G-Enabled Vehicular Networks
    Men, Rui
    Fan, Xiumei
    Yau, Kok-Lim Alvin
    Shan, Axida
    Yuan, Gang
    IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING, 2024, 11 (04): : 3891 - 3904
  • [38] 6G-Enabled Mobile Access Point Placement via Dynamic Federated Learning Strategies
    Mirdita, Paul
    Bello, Yahuza
    Refaey, Ahmed
    Radwan, Ayman
    IEEE OPEN JOURNAL OF THE COMMUNICATIONS SOCIETY, 2023, 4 : 2093 - 2103
  • [39] Open-Source Edge AI for 6G Wireless Networks
    Zhao, Liqiang
    Wang, Yunfeng
    Chu, Xiaoli
    Song, Shenghui
    Deng, Yansha
    Nallanathan, Arumugam
    Karagiannidis, George K.
    IEEE NETWORK, 2025, 39 (01): : 181 - 188
  • [40] Millimeter-Wave and Sub-6-GHz Aperture-Shared Antenna and Array for Mobile Terminals Accessing 5G/6G-Enabled IoT Scenarios
    Xia, Xiaoyue
    Wu, Fan
    Yu, Chao
    Jiang, Zhihao
    Xu, Jun
    Tang, Si-Yuan
    Wang, Zuojun
    Yao, Yu
    Hong, Wei
    IEEE INTERNET OF THINGS JOURNAL, 2024, 11 (10): : 18808 - 18823