Tampering Detection for Automotive Exhaust Aftertreatment Systems using Long Short-Term Memory Predictive Networks-Reference-Cited by-同舟云学术

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Tampering Detection for Automotive Exhaust Aftertreatment Systems using Long Short-Term Memory Predictive Networks

Published:2022-06 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW)
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Author:

Bolboaca Roland¹,Haller Piroska¹,Kontses Dimitris²,Papageorgiou-Koutoulas Alexandros²,Doulgeris Stylianos²,Zingopis Nikolaos³,Samaras Zissis²

Affiliation:

1. ‘G. E. Palade’ University of Medicine, Pharmacy, Science and Technology,Târgu Mureş,Romania

2. Aristotle University of Thessaloniki,Thessaloniki,Greece

3. Exothermia SA,Thessaloniki,Greece

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9799286/9799291/09799428.pdf?arnumber=9799428

Reference35 articles.

1. Exploring Inherent Sensor Redundancy for Automotive Anomaly Detection

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Recent Advances in SCR Systems of Heavy-Duty Diesel Vehicles—Low-Temperature NOx Reduction Technology and Combination of SCR with Remote OBD;Atmosphere;2024-08-20

2. An Estimate of the NOX Emissions of Euro 6 Diesel Passenger Cars with Manipulated Emission Control Systems;Sustainability;2024-02-25

3. Dynamic Utility-Improving Time Series Data Perturbation Framework;The 16th International Conference Interdisciplinarity in Engineering;2022-12-16

4. Adaptive Ensemble Methods for Tampering Detection in Automotive Aftertreatment Systems;IEEE Access;2022

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