Deep learning in the fast lane: A survey on advanced intrusion detection systems for intelligent vehicle networks
The rapid evolution of modern automobiles into intelligent and interconnected entities
presents new challenges in cybersecurity, particularly in Intrusion Detection Systems (IDS) …
presents new challenges in cybersecurity, particularly in Intrusion Detection Systems (IDS) …
Deep learning-based fault diagnosis of servo motor bearing using the attention-guided feature aggregation network
This paper introduces a novel approach to fault detection in the servo motor bearings of
industrial robots within the context of Industry 4.0 prognostics and health management. The …
industrial robots within the context of Industry 4.0 prognostics and health management. The …
[HTML][HTML] A survey on intrusion detection system in IoT networks
M Rahman, S Al Shakil, MR Mustakim - Cyber Security and Applications, 2024 - Elsevier
Abstract As the Internet of Things (IoT) expands, the security of IoT networks has becoming
more critical. Intrusion Detection Systems (IDS) are essential for protecting these networks …
more critical. Intrusion Detection Systems (IDS) are essential for protecting these networks …
Transformer-based attention network for in-vehicle intrusion detection
Despite the significant advantages of communication systems between electronic control
units, the controller area network (CAN) protocol is vulnerable to attacks owing to its weak …
units, the controller area network (CAN) protocol is vulnerable to attacks owing to its weak …
Multi-classification in-vehicle intrusion detection system using packet-and sequence-level characteristics from time-embedded transformer with autoencoder
In recent years, the increased application of controller area network (CAN) protocols has
made it the de facto standard for communication between electronic control units (ECUs) in …
made it the de facto standard for communication between electronic control units (ECUs) in …
CANPerFL: improve in-vehicle intrusion detection performance by sharing knowledge
The Controller Area Network (CAN) is a widely used communication protocol in
automobiles, but it is vulnerable to various types of attacks. To address this issue …
automobiles, but it is vulnerable to various types of attacks. To address this issue …
An evolutionary deep learning method based on improved heap-based optimization for medical image classification and diagnosis
L Zhang, Z Qiao, L Li - IEEE Access, 2024 - ieeexplore.ieee.org
With the continuous advancement of deep neural networks, leveraging deep learning for the
classification and diagnosis of medical images to aid physicians in patient diagnosis has …
classification and diagnosis of medical images to aid physicians in patient diagnosis has …
Enhancing real-time intrusion detection system for in-vehicle networks by employing novel feature engineering techniques and lightweight modeling
W Aljabri, MA Hamid, R Mosli - Ad Hoc Networks, 2025 - Elsevier
Autonomous vehicles are built using a variety of electronic control units (ECUs) that
communicate over a controller area network (CAN). A CAN enables the communication of …
communicate over a controller area network (CAN). A CAN enables the communication of …
Metaheuristic optimized complex-valued dilated recurrent neural network for attack detection in internet of vehicular communications
Abstract The Internet of Vehicles (IoV) is a specialized iteration of the Internet of Things (IoT)
tailored to facilitate communication and connectivity among vehicles and their environment …
tailored to facilitate communication and connectivity among vehicles and their environment …
Semi-supervised intrusion detection system for in-vehicle networks based on variational autoencoder and adversarial reinforcement learning
Despite the affordability, simplicity, and efficiency of controller area network (CAN) protocols,
the security vulnerability remains a major challenge. Currently, a machine learning-based …
the security vulnerability remains a major challenge. Currently, a machine learning-based …