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 …
communication has improved, helping the vehicles transition from completely machine-to …
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 …
improvement of both the mobility of people and the efficiency of transportation systems. The …
In-vehicle network intrusion detection using deep convolutional neural network
The implementation of electronics in modern vehicles has resulted in an increase in attacks
targeting in-vehicle networks; thus, attack detection models have caught the attention of the …
targeting in-vehicle networks; thus, attack detection models have caught the attention of the …
Can-bus attack detection with deep learning
Modern cars include a huge number of sensors and actuators, which continuously exchange
data and control commands. The most used protocol for communication of different …
data and control commands. The most used protocol for communication of different …
Retracted: An Evolutionary Deep Learning Anomaly Detection Framework for In-Vehicle Networks-CAN Bus
Y Lin, C Chen, F Xiao, O Avatefipour… - IEEE transactions on …, 2020 - ieeexplore.ieee.org
Modern vehicles are no longer considered as mere mechanical-based device, instead, they
have been hugely replaced by sophisticated electric devices known as Electronic Control …
have been hugely replaced by sophisticated electric devices known as Electronic Control …
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 …
enhance the security of in-vehicular network. The parameters building the DNN structure are …
An effective in-vehicle CAN bus intrusion detection system using CNN deep learning approach
The modern car is increasingly connected. That connection is magnified by the presence of
a large number of electronic control units (ECUs). The communication between the ECUs of …
a large number of electronic control units (ECUs). The communication between the ECUs of …
An intelligent secured framework for cyberattack detection in electric vehicles' CAN bus using machine learning
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 …
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
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 …
made controller area network (CAN) a de facto standard in the automotive industry. CAN …
[HTML][HTML] A survey of deep learning-based intrusion detection in automotive applications
Modern automobiles depend on internal vehicle networks (IVNs) to control systems from the
anti-lock brakes to the transmission to the locks on the doors. Many IVNs, particularly the …
anti-lock brakes to the transmission to the locks on the doors. Many IVNs, particularly the …