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.
.- 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).
