Machine Learning for Networking [[electronic resource] ] : 5th International Conference, MLN 2022, Paris, France, November 28–30, 2022, Revised Selected Papers / / edited by Éric Renault, Paul Mühlethaler

• Autore: Renault Éric
• Pubblicazione: Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023
• Edizione: 1st ed. 2023.
• Descrizione fisica: 1 online resource (190 pages)
• Disciplina: 006.312
• Soggetto topico: Data mining; Computer networks; Application software; Data Mining and Knowledge Discovery; Computer Communication Networks; Computer and Information Systems Applications
• Altri autori: MühlethalerPaul
• Nota di contenuto: Comparison of AI-based algorithms for low energy communication -- Development of an Intent-Based Network incorporating Machine Learning for service Assurance of E-commerce Online Stores -- Cyber-attack proactive defense using multivariate time series and machine learning with Fuzzy Inference-based Decision System -- iPerfOPS: a Tool for Machine Learning-Based Optimization through Protocol Selection -- GRAPHSEC -- Advancing the Application of AI/ML to Network Security through Graph Neural Networks -- Low Complexity Adaptive ML Approaches for End-to-End Latency Prediction -- TDMA-based MAC protocols designed or optimized using Artificial Intelligence for safety data dissemination in Vehicular ad-hoc network: A Survey -- A Machine Learning Based Approach to Detect Stealthy Cobalt Strike C\&C Activities from Encrypted Network Traffic -- Unified Emulation-Simulation Training Environment for Autonomous Cyber Agents -- Deep Learning Based Camera Switching for Sports Broadcasting -- Phisherman: Phishing Link Scanner -- Leader-Assisted Client Selection for Federated Learning in Iot via the Cooperation of Nearby Devices. .
• Sommario/riassunto: This book constitutes the post-conference proceedings of the 5th International Conference on Machine Learning for Networking, MLN 2022, held in Paris, France, November 28–30, 2022. The 12 full papers presented in this book were carefully reviewed and selected from 27 submissions. The papers present novel ideas, results, experiences and work-in-process on all aspects of Machine Learning and Networking.
• Titolo autorizzato: Machine Learning for Networking
• ISBN: 3-031-36183-0
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 996542671403316
• Lo trovi qui: Univ. di Salerno
• Serie: Lecture Notes in Computer Science, . 1611-3349 ; ; 13767