[HTML][HTML] Cyber attack detection for self-driving vehicle networks using deep autoencoder algorithms

FW Alsaade, MH Al-Adhaileh - Sensors, 2023 - mdpi.com
Connected and autonomous vehicles (CAVs) present exciting opportunities for the
improvement of both the mobility of people and the efficiency of transportation systems. The …

[HTML][HTML] Attacks to automatous vehicles: A deep learning algorithm for cybersecurity

THH Aldhyani, H Alkahtani - Sensors, 2022 - mdpi.com
Rapid technological development has changed drastically the automotive industry. Network
communication has improved, helping the vehicles transition from completely machine-to …

An enhanced multi-stage deep learning framework for detecting malicious activities from autonomous vehicles

IA Khan, N Moustafa, D Pi, W Haider… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Intelligent Transportation Systems (ITS), particularly Autonomous Vehicles (AVs), are
susceptible to safety and security concerns that impend people's lives. Nothing like manually …

Deep contractive autoencoder-based anomaly detection for in-vehicle controller area network (CAN)

SF Lokman, AT Othman, S Musa… - Progress in Engineering …, 2019 - Springer
With the emerging wireless technology integrated into modern vehicles, this introduces an
enormous number of vulnerabilities for adversaries to compromise the vehicle internal …

An intelligent secured framework for cyberattack detection in electric vehicles' CAN bus using machine learning

O Avatefipour, AS Al-Sumaiti, AM El-Sherbeeny… - Ieee …, 2019 - ieeexplore.ieee.org
Electric Vehicles' Controller Area Network (CAN) bus serves as a legacy protocol for in-
vehicle network communication. Simplicity, robustness, and suitability for real-time systems …

A hybrid deep learning based intrusion detection system using spatial-temporal representation of in-vehicle network traffic

W Lo, H Alqahtani, K Thakur, A Almadhor… - Vehicular …, 2022 - Elsevier
A significant increase in the use of electronics control units (ECUs) in modern vehicles has
made controller area network (CAN) a de facto standard in the automotive industry. CAN …

[HTML][HTML] Using deep learning networks to identify cyber attacks on intrusion detection for in-vehicle networks

HC Lin, P Wang, KM Chao, WH Lin, JH Chen - Electronics, 2022 - mdpi.com
With rapid advancements in in-vehicle network (IVN) technology, the demand for multiple
advanced functions and networking in electric vehicles (EVs) has recently increased. To …

Intelligent intrusion detection in external communication systems for autonomous vehicles

KM Ali Alheeti, K McDonald-Maier - Systems Science & Control …, 2018 - Taylor & Francis
Self-driving vehicles are known to be vulnerable to different types of attacks due to the type
of communication systems which are utilized in these vehicles. These vehicles are …

An evolutionary deep learning-based anomaly detection model for securing vehicles

A Kavousi-Fard, M Dabbaghjamanesh… - IEEE Transactions …, 2020 - ieeexplore.ieee.org
This article proposes a deep learning based approach for cyber attack detection in the
vehicles. The proposed method is constructed based on generative adversarial network …

[HTML][HTML] Intrusion detection system using deep neural network for in-vehicle network security

MJ Kang, JW Kang - PloS one, 2016 - journals.plos.org
A novel intrusion detection system (IDS) using a deep neural network (DNN) is proposed to
enhance the security of in-vehicular network. The parameters building the DNN structure are …