A survey on machine learning-based misbehavior detection systems for 5g and beyond vehicular networks

A Boualouache, T Engel - IEEE Communications Surveys & …, 2023 - ieeexplore.ieee.org
Advances in Vehicle-to-Everything (V2X) technology and onboard sensors have significantly
accelerated deploying Connected and Automated Vehicles (CAVs). Integrating V2X with 5G …

Towards cyber security for low-carbon transportation: Overview, challenges and future directions

Y Cao, S Li, C Lv, D Wang, H Sun, J Jiang… - … and Sustainable Energy …, 2023 - Elsevier
In recent years, low-carbon transportation has become an indispensable part as sustainable
development strategies of various countries, and plays a very important responsibility in …

A Comprehensive review on limitations of autonomous driving and its impact on accidents and collisions

A Chougule, V Chamola, A Sam… - IEEE Open Journal of …, 2023 - ieeexplore.ieee.org
The emergence of autonomous driving represents a pivotal milestone in the evolution of the
transportation system, integrating seamlessly into the daily lives of individuals due to its …

Social Psychology Inspired Distributed Ledger Technique for Anomaly Detection in Connected Vehicles

H Rathore, S Sai, A Gundewar - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Connected Vehicles (CVs), an integral part of the future of intelligent transportation systems,
use communication and sensing technologies to communicate among vehicles and …

Federated learning based IDS approach for the IoV

A Hbaieb, S Ayed, L Chaari - … of the 17th international conference on …, 2022 - dl.acm.org
The Internet of Vehicles (IoV) is an Internet of Things (IoT) application that offers several
utilities such as traffic analysis, safe driving, road optimization, and travel comfort. Software …

[HTML][HTML] The dichotomy of neural networks and cryptography: war and peace

B Zolfaghari, T Koshiba - Applied System Innovation, 2022 - mdpi.com
In recent years, neural networks and cryptographic schemes have come together in war and
peace; a cross-impact that forms a dichotomy deserving a comprehensive review study …

Software-defined radio-based 5G physical layer experimental platform for highly mobile environments

S Mori, K Mizutani, H Harada - IEEE Open Journal of Vehicular …, 2023 - ieeexplore.ieee.org
In this study, we developed a 5th generation mobile communication (5G) physical layer
(PHY) experimental platform based on software-defined radio (SDR), which makes it easy to …

Machine un-learning: an overview of techniques, applications, and future directions

S Sai, U Mittal, V Chamola, K Huang, I Spinelli… - Cognitive …, 2024 - Springer
ML applications proliferate across various sectors. Large internet firms employ ML to train
intelligent models using vast datasets, including sensitive user information. However, new …

[HTML][HTML] Vehicular network intrusion detection using a cascaded deep learning approach with multi-variant metaheuristic

A Manderna, S Kumar, U Dohare, M Aljaidi… - Sensors, 2023 - mdpi.com
Vehicle malfunctions have a direct impact on both human and road safety, making vehicle
network security an important and critical challenge. Vehicular ad hoc networks (VANETs) …

From anomaly detection to novel fault discrimination for wind turbine gearboxes with a sparse isolation encoding forest

W Du, Z Guo, C Li, X Gong, Z Pu - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
As vital renewable energy devices, wind turbines suffer from gearbox failures due to harsh
speed increasing operations. Therefore, gearbox fault diagnosis is crucial for wind turbine …