[HTML][HTML] Deep learning in food category recognition

Y Zhang, L Deng, H Zhu, W Wang, Z Ren, Q Zhou… - Information …, 2023 - Elsevier
Integrating artificial intelligence with food category recognition has been a field of interest for
research for the past few decades. It is potentially one of the next steps in revolutionizing …

Neuro-symbolic explainable artificial intelligence twin for zero-touch ioe in wireless network

MS Munir, KT Kim, A Adhikary, W Saad… - IEEE Internet of …, 2023 - ieeexplore.ieee.org
Explainable artificial intelligence (XAI) twin systems will be a fundamental enabler of zero-
touch network and service management (ZSM) for sixth-generation (6G) wireless networks …

An In-Depth Survey on Virtualization Technologies in 6G Integrated Terrestrial and Non-Terrestrial Networks

S Ammar, CP Lau, B Shihada - arXiv preprint arXiv:2312.01895, 2023 - arxiv.org
6G networks are envisioned to deliver a large diversity of applications and meet stringent
quality of service (QoS) requirements. Hence, integrated terrestrial and non-terrestrial …

A novel federated edge learning approach for detecting cyberattacks in IoT infrastructures

S Abbas, A Al Hejaili, GA Sampedro, M Abisado… - IEEE …, 2023 - ieeexplore.ieee.org
The advancement of the communications system has resulted in the rise of the Internet of
Things (IoT), which has increased the importance of cybersecurity research. IoT, which …

A federated-ANFIS for collaborative intrusion detection in securing decentralized autonomous organizations

YP Tsang, CH Wu, N Dong - IEEE Transactions on Engineering …, 2023 - ieeexplore.ieee.org
Blockchain has facilitated the emergence of automation and decentralization concepts,
leading to significant organizational and operational changes in businesses, eg …

[HTML][HTML] A federated learning-based zero trust intrusion detection system for Internet of Things

D Javeed, MS Saeed, M Adil, P Kumar, A Jolfaei - Ad Hoc Networks, 2024 - Elsevier
The exponential growth of Internet of Things (IoT) devices poses distinctive challenges to
safeguarding the security and privacy of interconnected systems. As the frequency of …

Exploring the Landscape of AI-SDN: A Comprehensive Bibliometric Analysis and Future Perspectives

F Sahran, HHM Altarturi, NB Anuar - Electronics, 2023 - mdpi.com
The rising influence of artificial intelligence (AI) enables widespread adoption of the
technology in every aspect of computing, including Software-Defined Networking (SDN) …

Advancing Security and Efficiency in Federated Learning Service Aggregation for Wireless Networks

Z Abou El Houda, D Nabousli… - 2023 IEEE 34th Annual …, 2023 - ieeexplore.ieee.org
Federated Learning (FL) is a distributed machine learning technique where multiple devices
can collaboratively train a model without sharing their data. As a result, FL ensures distinct …

A Semi-Federated Active Learning Framework for Unlabeled Online Network Data

Y Zhou, Y Hu, J Sun, R He, W Kang - Mathematics, 2023 - mdpi.com
Federated Learning (FL) is a newly emerged federated optimization technique for distributed
data in a federated network. The participants in FL that train the model locally are classified …

FLID: Intrusion Attack and Defense Mechanism for Federated Learning Empowered Connected Autonomous Vehicles (CAVs) Application

MZ Hossain, A Imteaj, S Zaman… - … IEEE Conference on …, 2023 - ieeexplore.ieee.org
Connected autonomous vehicles (CAVs) are transforming the transportation business by
incorporating advanced technology such as sensors, communication systems, and artificial …