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Multi-Criteria Optimized Deep Learning-based Intrusion Detection System for Detecting Cyberattacks in Automotive Ethernet Networks
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1016/j.comnet.2019.107093openalex-snapshot
Security issues and challenges in V2X: A Survey
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/10.1109/access.2018.2877890openalex-snapshot
Benchmark Analysis of Representative Deep Neural Network Architectures
inferredcites →https://doi.org/10.1109/access.2021.3097247openalex-snapshot
Deep Learning-Based Intrusion Detection Systems: A Systematic Review
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/iv51971.2022.9827285openalex-snapshot
Unsupervised Network Intrusion Detection System for AVTP in Automotive Ethernet Networks
inferredcites →https://doi.org/10.1109/mce.2018.2828440openalex-snapshot
Advanced Driver-Assistance Systems: A Path Toward Autonomous Vehicles
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/pst.2018.8514157openalex-snapshot
GIDS: GAN based Intrusion Detection System for In-Vehicle Network
inferredcites →https://doi.org/10.1109/tits.2014.2320605openalex-snapshot
Intra-Vehicle Networks: A Review
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/tits.2021.3078740openalex-snapshot
A Survey of Attacks on Controller Area Networks and Corresponding Countermeasures
inferredcites →https://doi.org/10.1109/tits.2021.3085297openalex-snapshot
A Survey on Cyber-Security of Connected and Autonomous Vehicles (CAVs)
inferredcites →https://doi.org/10.1109/tvt.2021.3054934openalex-snapshot
Making the Case for Centralized Automotive E/E Architectures
inferredcites →https://doi.org/10.4324/9781003075011-10openalex-snapshot
Experimental Security Analysis of a Modern Automobile
inferredcites →https://doi.org/10.48550/arxiv.2204.02965openalex-snapshot
LilNetX: Lightweight Networks with EXtreme Model Compression and Structured Sparsification
inferredcites →https://doi.org/10.5753/sbrc.2022.222153openalex-snapshot
Machine Learning-Based Intrusion Detection System for Automotive Ethernet: Detecting Cyber-Attacks with a Low-Cost Platform
What points at this work
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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/10.23919/cje.2025.00.230openalex-snapshot
Towards Secure In-Vehicle Communication: Surveying CAN and Automotive Ethernet Threats, Standards, and Detection Techniques
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_estendido.2025.6908openalex-snapshot
Enhancing Cybersecurity of Automotive Ethernet Networks with Deep Learning-based Intrusion Detection Systems
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