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 …
Tranad: Deep transformer networks for anomaly detection in multivariate time series data
Efficient anomaly detection and diagnosis in multivariate time-series data is of great
importance for modern industrial applications. However, building a system that is able to …
importance for modern industrial applications. However, building a system that is able to …
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 …
Smart anomaly detection in sensor systems: A multi-perspective review
Anomaly detection is concerned with identifying data patterns that deviate remarkably from
the expected behavior. This is an important research problem, due to its broad set of …
the expected behavior. This is an important research problem, due to its broad set of …
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 …
Anomaly detection in automated vehicles using multistage attention-based convolutional neural network
Connected and Automated Vehicles (CAVs), owing to their characteristics such as seamless
and real-time transfer of data, are imperative infrastructural advancements to realize the …
and real-time transfer of data, are imperative infrastructural advancements to realize the …
A novel rough numbers based extended MACBETH method for the prioritization of the connected autonomous vehicles in real-time traffic management
Digital transformation can help to make better use of existing transportation networks that
are congested. One solution to the road congestion problem is real-time traffic management …
are congested. One solution to the road congestion problem is real-time traffic management …
BTAD: A binary transformer deep neural network model for anomaly detection in multivariate time series data
M Ma, L Han, C Zhou - Advanced Engineering Informatics, 2023 - Elsevier
In the context of big data, if the task of multivariate time series data anomaly detection cannot
be performed efficiently and accurately, it will bring great security risks to industrial systems …
be performed efficiently and accurately, it will bring great security risks to industrial systems …
Ensemble adaboost classifier for accurate and fast detection of botnet attacks in connected vehicles
A Rehman Javed, Z Jalil… - Transactions on …, 2022 - Wiley Online Library
The key characteristic of smart cities (ie, connectivity and intelligence) has enabled
connected vehicles to work together to accomplish complex jobs that they are unable to …
connected vehicles to work together to accomplish complex jobs that they are unable to …