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Machine Learning-Based Intrusion Detection System for Automotive Ethernet: Detecting Cyber-Attacks with a Low-Cost Platform
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Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1016/j.vehcom.2017.02.005openalex-snapshot
Field classification, modeling and anomaly detection in unknown CAN bus networks
inferredcites →https://doi.org/10.1016/j.vehcom.2019.100214openalex-snapshot
Cybersecurity challenges in vehicular communications
inferredcites →https://doi.org/10.1016/j.vehcom.2021.100338openalex-snapshot
Convolutional neural network-based intrusion detection system for AVTP streams in automotive Ethernet-based networks
inferredcites →https://doi.org/10.1088/1749-4699/8/1/014008openalex-snapshot
Hyperopt: a Python library for model selection and hyperparameter optimization
inferredcites →https://doi.org/10.1109/access.2021.3136147openalex-snapshot
An Efficient Intrusion Prevention System for CAN: Hindering Cyber-Attacks With a Low-Cost Platform
inferredcites →https://doi.org/10.1109/ieeestd.2016.7782716openalex-snapshot
IEEE Standard for a Transport Protocol for Time-Sensitive Applications in Bridged Local Area Networks
inferredcites →https://doi.org/10.1109/iemcon53756.2021.9623129openalex-snapshot
SOME/IP Intrusion Detection using Deep Learning-based Sequential Models in Automotive Ethernet Networks
inferredcites →https://doi.org/10.1109/iv51971.2022.9827285openalex-snapshot
Unsupervised Network Intrusion Detection System for AVTP in Automotive Ethernet Networks
inferredcites →https://doi.org/10.1109/mnet.2017.1600257openalex-snapshot
In-Vehicle Network Attacks and Countermeasures: Challenges and Future Directions
inferredcites →https://doi.org/10.1109/sp.2010.34openalex-snapshot
Experimental Security Analysis of a Modern Automobile
inferredcites →https://doi.org/10.1109/tifs.2018.2812149openalex-snapshot
VoltageIDS: Low-Level Communication Characteristics for Automotive Intrusion Detection System
inferredcites →https://doi.org/10.1109/tits.2019.2908074openalex-snapshot
A Survey of Intrusion Detection for In-Vehicle Networks
inferredcites →https://doi.org/10.1109/tvt.2021.3054934openalex-snapshot
Making the Case for Centralized Automotive E/E Architectures
inferredcites →https://doi.org/10.1109/vtcspring.2016.7504089openalex-snapshot
A Novel Intrusion Detection Method Using Deep Neural Network for In-Vehicle Network Security
inferredcites →https://doi.org/10.1145/2095256.2095257openalex-snapshot
The case for ethernet in automotive communications
inferredcites →https://doi.org/10.21227/1yr3-q009openalex-snapshot
Automotive Ethernet Intrusion Dataset
inferredcites →https://doi.org/10.4324/9781003075011-10openalex-snapshot
Experimental Security Analysis of a Modern Automobile
inferredcites →https://doi.org/10.48550/arxiv.1603.02754openalex-snapshot
XGBoost: A Scalable Tree Boosting System
What points at this work
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inferred← citeshttps://doi.org/10.1007/978-3-032-15993-9_16openalex-snapshot
Deep Learning-Based Intrusion Detection for Automotive Ethernet: Evaluating and Optimizing Fast Inference Techniques for Deployment on Low-Cost Platform
inferred← citeshttps://doi.org/10.1016/j.adhoc.2024.103548openalex-snapshot
Multi-stage deep learning-based intrusion detection system for automotive Ethernet networks
inferred← citeshttps://doi.org/10.1063/5.0312142openalex-snapshot
A comprehensive hybrid deep learning approach for effective intrusion detection in automotive ethernet systems
inferred← citeshttps://doi.org/10.1109/jiot.2025.3620567openalex-snapshot
Defense Against Adversarial Samples for Replay Attacks in Automotive AVTP Streams via a Novel Bidirectional Mamba-Based Intrusion Detection System
inferred← citeshttps://doi.org/10.5753/ctd.2025.7585openalex-snapshot
Enhancing Cybersecurity of Automotive Ethernet Networks with Deep Learning-based Intrusion Detection Systems
inferred← citeshttps://doi.org/10.5753/sbrc.2023.527openalex-snapshot
Multi-Criteria Optimized Deep Learning-based Intrusion Detection System for Detecting Cyberattacks in Automotive Ethernet Networks
inferred← citeshttps://doi.org/10.5753/sbrc_estendido.2025.6908openalex-snapshot
Enhancing Cybersecurity of Automotive Ethernet Networks with Deep Learning-based Intrusion Detection Systems
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