A survey on attack detection and resilience for connected and automated vehicles: From vehicle dynamics and control perspective
Z Ju, H Zhang, X Li, X Chen, J Han… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Recent advances in attack/anomaly detection and resilience strategies for connected and
automated vehicles (CAVs) are reviewed from vehicle dynamics and control perspective …
automated vehicles (CAVs) are reviewed from vehicle dynamics and control perspective …
Potential sources of sensor data anomalies for autonomous vehicles: An overview from road vehicle safety perspective
Outstanding steps towards intelligent transportation systems with autonomous vehicles have
been taken in the past few years. Nevertheless, the safety issue in autonomous vehicles is …
been taken in the past few years. Nevertheless, the safety issue in autonomous vehicles is …
[HTML][HTML] Predictive maintenance enabled by machine learning: Use cases and challenges in the automotive industry
A Theissler, J Pérez-Velázquez, M Kettelgerdes… - Reliability engineering & …, 2021 - Elsevier
Recent developments in maintenance modelling fueled by data-based approaches such as
machine learning (ML), have enabled a broad range of applications. In the automotive …
machine learning (ML), have enabled a broad range of applications. In the automotive …
Resilient and safe platooning control of connected automated vehicles against intermittent denial-of-service attacks
Connected automated vehicles (CAVs) serve as a promising enabler for future intelligent
transportation systems because of their capabilities in improving traffic efficiency and driving …
transportation systems because of their capabilities in improving traffic efficiency and driving …
Edge intelligence: Empowering intelligence to the edge of network
Edge intelligence refers to a set of connected systems and devices for data collection,
caching, processing, and analysis proximity to where data are captured based on artificial …
caching, processing, and analysis proximity to where data are captured based on artificial …
A survey on deep learning for cybersecurity: Progress, challenges, and opportunities
As the number of Internet-connected systems rises, cyber analysts find it increasingly difficult
to effectively monitor the produced volume of data, its velocity and diversity. Signature-based …
to effectively monitor the produced volume of data, its velocity and diversity. Signature-based …
Comparative research on network intrusion detection methods based on machine learning
C Zhang, D Jia, L Wang, W Wang, F Liu, A Yang - Computers & Security, 2022 - Elsevier
Network intrusion detection system is an essential part of network security research. It
detects intrusion behaviors through active defense technology and takes emergency …
detects intrusion behaviors through active defense technology and takes emergency …
A fault diagnosis framework for autonomous vehicles with sensor self-diagnosis
Fault diagnosis for autonomous vehicles aims to provide available information about the
operation status of the vehicle to avoid potential risks, and sensor data provide the …
operation status of the vehicle to avoid potential risks, and sensor data provide the …
Deep learning-based anomaly detection in cyber-physical systems: Progress and opportunities
Anomaly detection is crucial to ensure the security of cyber-physical systems (CPS).
However, due to the increasing complexity of CPSs and more sophisticated attacks …
However, due to the increasing complexity of CPSs and more sophisticated attacks …
A survey on network security for cyber–physical systems: From threats to resilient design
Cyber-physical systems (CPS) are considered the integration of physical systems in the real
world and control software in computing systems. In CPS, the real world and the computing …
world and control software in computing systems. In CPS, the real world and the computing …