This book constitutes the refereed proceedings of the 6th International Conference on Machine Learning for Networking, MLN 2023, held in Paris, France, during November 28-30, 2023.
The 18 full papers included in this book were carefully reviewed and selected from 34 submissions. The conference aims at providing a top forum for researchers and practitioners to present and discuss new trends in machine learning, deep learning, pattern recognition and optimization for network architectures and services.
Inhaltsverzeichnis
. - Machine Learning for IoT Devices Security Reinforcement.
. - All Attentive Deep Conditional Graph Generation for Wireless Network Topology Optimization.
. - Enhancing Social Media Profile Authenticity Detection A Bio Inspired Algorithm Approach.
. - Deep Learning Based Detection of Suspicious Activity in Outdoor Home Surveillance.
. - Detecting Abnormal Authentication Delays in Identity and Access Management using Machine Learning.
. - SIP DDoS SIP Framework for DDoS Intrusion Detection based on Recurrent Neural Networks.
. - Deep Reinforcement Learning for multiobjective Scheduling in Industry 5. 0 Reconfigurable Manufacturing Systems.
. - Toward a digital twin IoT for the validation of AI algorithms in smart-city applications.
. - Data Summarization for Federated Learning.
. - ML Comparison Countermeasure prediction using radio internal metrics for BLE radio.
. - Towards to Road Profiling with Cooperative Intelligent TransportSystems.
. - Study of Masquerade Attack in VANETs with machine learning.
. - Detecting Virtual Harassment in Social Media Using Machine Learning.
. - Leverage data security policies complexity for users an end to end storage service management in the Cloud based on ABAC attributes.
. - Machine Learning to Model the Risk of Alteration of historical buildings.
. - A novel Image Encryption Technique using Modified Grain.
. - Transformation Network Model for Ear Recognition.
. - Cybersecurity analytics: Toward an efficient ML-based Network Intrusion Detection System (NIDS).
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