Real-Time Threat Intelligence Integration for Cybersecurity in Autonomous Vehicles-A Deep Learning Framework: Integrates real-time threat intelligence into …

M Akın - Journal of Artificial Intelligence Research and …, 2023 - aimlstudies.co.uk
The increasing dependence of Autonomous Vehicles (AVs) on complex software and
network connectivity makes them vulnerable to cyberattacks. These attacks can potentially …

[HTML][HTML] A survey of deep learning-based intrusion detection in automotive applications

B Lampe, W Meng - Expert Systems with Applications, 2023 - Elsevier
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 …

Stackelberg security game to mitigate the DoS attack in vehicular ad-hoc networks

A Ilavendhan, K Saruladha - Journal of Ambient Intelligence and …, 2023 - Springer
Smart communication systems improve VANETs with the assistance of intelligent software
systems. Such electronic tools allow automatic traffic control services to reduce road injuries …

CAN Intrusion Detection Using Long Short-Term Memory (LSTM)

SR Nandam, A Vamshi, I Sucharitha - … and IoT: Proceedings of 5th ICICC …, 2022 - Springer
Car hacking is becoming prevalent with new cyber techniques to hack any car by hacking its
internal network controller. Most internal networks of a car are being controlled by a …

A systematic comparison on prevailing intrusion detection models

J Liu, H Xue, J Wang, S Hong, H Fu, O Dib - International Conference on …, 2022 - Springer
Modern vehicles have become connected via On-Board Units (OBUs) involving many
complex embedded and networked devices with steadily increasing processing and …

TB-EDA: A trust-based event detection algorithm to detect false events in software-defined vehicular network

RP Nayak, S Sethi, SK Bhoi - Intelligent Systems: Proceedings of ICMIB …, 2021 - Springer
False event propagation is one of the main reasons of disruption of a network. So, false
events need to be detected early to protect the network from collapsing. In this paper, a trust …

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] An Effective Ensemble Learning-Based Real-Time Intrusion Detection Scheme for an In-Vehicle Network

E Alalwany, I Mahgoub - Electronics, 2024 - mdpi.com
The emergence of connected and autonomous vehicles has led to complex network
architectures for electronic control unit (ECU) communication. The controller area network …

Systematic evaluation of automotive intrusion detection datasets

A Vahidi, T Rosenstatter, NI Mowla - … of the 6th ACM Computer Science …, 2022 - dl.acm.org
Some current and next generation security solutions employ machine learning and related
technologies. Due to the nature of these applications, correct use of machine learning can …

An unsupervised learning approach for in-vehicle network intrusion detection

N Leslie - 2021 55th Annual Conference on Information …, 2021 - ieeexplore.ieee.org
In-vehicle networks remain largely unprotected from a myriad of vulnerabilities to failures
caused by adversarial activities. Remote attacks on the SAE J1939 protocol based on …