Machine Learning

A Methodological Framework for Optimizing the Energy Consumption of Deep Neural Networks: A Case Study of a Cyber Threat Detector
The growing prevalence of deep neural networks (DNNs) across various fields raises concerns about their increasing energy consumption, …
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A Machine-Learning-Based Cyberattack Detector for a Cloud-Based SDN Controller
The rapid evolution of network infrastructure through the softwarization of network elements has led to an exponential increase in the …
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Integration of Machine Learning-Based Attack Detectors into Defensive Exercises of a 5G Cyber Range
Cybercrime has become more pervasive and sophisticated over the years. Cyber ranges have emerged as a solution to keep pace with the …
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B5GEMINI: AI-Driven Network Digital Twin
Network Digital Twin (NDT) is a new technology that builds on the concept of Digital Twins (DT) to create a virtual representation of …
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B5GEMINI: Digital Twin Network for 5G and Beyond
Digital Twin Network (DTN) is a new technology that builds on the concept of Digital Twins (DT) to create a virtual representation of …
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