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On TinyML and Cybersecurity: Electric Vehicle Charging Infrastructure Use Case
April 29, 2024, 4:11 a.m. | Fatemeh Dehrouyeh, Li Yang, Firouz Badrkhani Ajaei, Abdallah Shami
cs.CR updates on arXiv.org arxiv.org
Abstract: As technology advances, the use of Machine Learning (ML) in cybersecurity is becoming increasingly crucial to tackle the growing complexity of cyber threats. While traditional ML models can enhance cybersecurity, their high energy and resource demands limit their applications, leading to the emergence of Tiny Machine Learning (TinyML) as a more suitable solution for resource-constrained environments. TinyML is widely applied in areas such as smart homes, healthcare, and industrial automation. TinyML focuses on optimizing ML …
applications arxiv can case charging complexity cs.ai cs.cr cs.lg cyber cybersecurity cyber threats demands electric electric vehicle energy high infrastructure limit machine machine learning ml models resource technology threats tiny use case vehicle
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A Privacy Preserving System for Movie Recommendations Using Federated Learning
2 days, 21 hours ago |
arxiv.org
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