Special lssues
Table of Content

Sensors for Malicious Traffic Identification Using Machine Learning in IoT

Submission Deadline: 10 April 2022 (closed)

Guest Editors

Dr. Muhammad Arif, The University of Lahore, Pakistan.
Prof. Dr. Oana Geman, Universitatea Stefan cel Mare din Suceava, Romania.
Prof. Dr. Aniello Castiglione, University of Naples Parthenope, Italy.
Dr. Khurram Ejaz, University of Lahore, Pakistan.


This Special Issue aims to provide state-of-the-art systems for malicious traffic identification in the Internet of things (IoT) network using machine learning (ML) techniques. We, therefore, wish to look complete systems for IoT malicious and management systems for the IoT network traffic classification, which contributes to truly innovative pervasive for the unwanted IoT traffic in IoT network environment. The goal of the present Special Issue is to collect contributions in the disciplines of IoT devices, computer science, engineering, machine learning, protocols, feature selection and traffic classification, identification in IoT that extend the current state of the art with innovative ideas and solutions. Experimental and theoretical studies for IoT networks are encouraged. 


Internet of Things Network Traffic Classification
Intelligent systems for security and privacy in IoT Network
IoT Network Traffic Management Using Machine Learning
Malicious IoT Traffic Identification Using Machine Learning
QoE/QoS for IoT Network Management
Machine Learning Algorithms for IoT Traffic Classification
Technique for IoT Devices management
Authentication Technique for IoT Based on Machine Learning
Real-time online IoT traffic classification system based on Machine Learning
IoT Network Security Bases on Machine Learning
Other Topics

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