Adversarial Machine Learning-Based Anticipation of Threats Against Vehicle-to-Microgrid Services
Author:
Affiliation:
1. School of Electrical Engineering and Computer Science, University of Ottawa,Ottawa,Canada
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10000063/10000593/10000757.pdf?arnumber=10000757
Reference18 articles.
1. Cost-aware Data Aggregation and Energy Decentralization with Electrical Vehicles in Microgrids through LTE Links
2. Machine Learning in NextG Networks via Generative Adversarial Networks
3. Cyber-Attack Detection and Cyber-Security Enhancement in Smart DC-Microgrid Based on Blockchain Technology and Hilbert Huang Transform
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1. An AI-driven solution to prevent adversarial attacks on mobile Vehicle-to-Microgrid services;Simulation Modelling Practice and Theory;2024-12
2. Misconfiguration in O-RAN: Analysis of the impact of AI/ML;Computer Networks;2024-06
3. Generative Adversarial Networks to Secure Vehicle-to-Microgrid Services;2023 IEEE Virtual Conference on Communications (VCC);2023-11-28
4. Towards an Adversarial Machine Learning Framework in Cyber-Physical Systems;2023 IEEE/ACIS 21st International Conference on Software Engineering Research, Management and Applications (SERA);2023-05-23
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