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 …

Demystifying in-vehicle intrusion detection systems: A survey of surveys and a meta-taxonomy

G Karopoulos, G Kambourakis, E Chatzoglou… - Electronics, 2022 - mdpi.com
Breaches in the cyberspace due to cyber-physical attacks can harm the physical space, and
any type of vehicle is an alluring target for wrongdoers for an assortment of reasons …

An artificial intelligence lightweight blockchain security model for security and privacy in IIoT systems

S Selvarajan, G Srivastava, AO Khadidos… - Journal of Cloud …, 2023 - Springer
Abstract The Industrial Internet of Things (IIoT) promises to deliver innovative business
models across multiple domains by providing ubiquitous connectivity, intelligent data …

Machine learning for enhancing transportation security: A comprehensive analysis of electric and flying vehicle systems

H Alqahtani, G Kumar - Engineering Applications of Artificial Intelligence, 2024 - Elsevier
This paper delves into the transformative role of machine learning (ML) techniques in
revolutionizing the security of electric and flying vehicles (EnFVs). By exploring key domains …

A conjugate self-organizing migration (CSOM) and reconciliate multi-agent Markov learning (RMML) based cyborg intelligence mechanism for smart city security

S Shitharth, AM Alshareef, AO Khadidos, KH Alyoubi… - Scientific Reports, 2023 - nature.com
Ensuring the privacy and trustworthiness of smart city—Internet of Things (IoT) networks
have recently remained the central problem. Cyborg intelligence is one of the most popular …

TCAN-IDS: intrusion detection system for internet of vehicle using temporal convolutional attention network

P Cheng, K Xu, S Li, M Han - Symmetry, 2022 - mdpi.com
Intrusion detection systems based on recurrent neural network (RNN) have been considered
as one of the effective methods to detect time-series data of in-vehicle networks. However …

LCCDE: a decision-based ensemble framework for intrusion detection in the internet of vehicles

L Yang, A Shami, G Stevens… - GLOBECOM 2022-2022 …, 2022 - ieeexplore.ieee.org
Modern vehicles, including autonomous vehicles and connected vehicles, have adopted an
increasing variety of functionalities through connections and communications with other …

[HTML][HTML] Machine learning methods for intrusive detection of wormhole attack in mobile ad hoc network (MANET)

M Abdan, SAH Seno - Wireless Communications and Mobile …, 2022 - hindawi.com
A wormhole attack is a type of attack on the network layer that reflects routing protocols. The
classification is performed with several methods of machine learning consisting of K-nearest …

A systematic literature review of flying ad hoc networks: State‐of‐the‐art, challenges, and perspectives

F Pasandideh, JPJ Costa, R Kunst… - Journal of Field …, 2023 - Wiley Online Library
Unmanned aerial vehicles (UAVs), also known as drones, communicate, collaborate, and
form flying ad hoc networks (FANETs) to perform many different missions, ranging from …

An intrusion detection method for industrial control system based on machine learning

Y Cao, L Zhang, X Zhao, K Jin, Z Chen - Information, 2022 - mdpi.com
The integration of communication networks and the internet of industrial control in Industrial
Control System (ICS) increases their vulnerability to cyber attacks, causing devastating …