An assessment method for automotive intrusion detection system performance

S Stachowski, R Gaynier, DJ LeBlanc - 2019 - deepblue.lib.umich.edu
In response to the increased attack surfaces on modern vehicles due to expanded use of
software and the introduction of wireless interfaces, a new market has emerged for intrusion …

Artificial intelligence (AI)-empowered intrusion detection architecture for the internet of vehicles

T Alladi, V Kohli, V Chamola, FR Yu… - IEEE Wireless …, 2021 - ieeexplore.ieee.org
Recent advances in the Internet of Things (IoT) and the adoption of IoT in vehicular networks
have led to a new and promising paradigm called the Internet of Vehicles (IoV). However …

Candito: improving payload-based detection of attacks on controller area networks

S Longari, CA Pozzoli, A Nichelini, M Carminati… - … Symposium on Cyber …, 2023 - Springer
Over the years, the increasingly complex and interconnected vehicles raised the need for
effective and efficient Intrusion Detection Systems against on-board networks. In light of the …

Securing CAN bus in connected and autonomous vehicles using supervised machine learning approaches

R Gundu, M Maleki - 2022 IEEE International Conference on …, 2022 - ieeexplore.ieee.org
Connected and Autonomous Vehicles (CAVs) are becoming a promising solution in
Intelligent Transportation Systems (ITS). Despite these advancements, vehicles still use a …

Towards a lightweight intrusion detection framework for in-vehicle networks

D Basavaraj, S Tayeb - Journal of Sensor and Actuator Networks, 2022 - mdpi.com
With the emergence of networked devices, from the Internet of Things (IoT) nodes and
cellular phones to vehicles connected to the Internet, there has been an ever-growing …

VitroBench: Manipulating in-vehicle networks and COTS ECUs on your bench: A comprehensive test platform for automotive cybersecurity research

AKT Yeo, ME Garbelini, S Chattopadhyay… - Vehicular …, 2023 - Elsevier
With the increasing connectivity employed in automotive systems, remote cyber attacks have
now become a possibility and concrete threat. Prior works on automotive cyber security …

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 …

Deep learning-based anomaly detection for connected autonomous vehicles using spatiotemporal information

P Mansourian, N Zhang, A Jaekel… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Although connected mymargin autonomous vehicles (CAVs) hold great potential to improve
driving safety and experience significantly, cybersecurity remains a critical concern. As the …

In-vehicle network attack detection across vehicle models: A supervised-unsupervised hybrid approach

S Nakamura, K Takeuchi, H Kashima… - 2021 IEEE …, 2021 - ieeexplore.ieee.org
Recent studies have demonstrated that the injection of malicious messages into in-vehicle
networks can cause unintended operation of the controls of vehicles, which has been …

[PDF][PDF] Context-aware intrusion detection in automotive control systems

A Wasicek, MD Pesé, A Weimerskirch… - Proc. 5th ESCAR USA …, 2017 - mpese.com
This paper describes a method and framework to detect manipulations in automotive control
systems. As the automotive industry is shifting towards employing software-based solutions …