4 papers
FedTransKD-IDS: Robust Federated Transfer Learning with Knowledge Distillation for Intrusion Detection in IoT
Mohammad Hosssein Gholamrezazadeh, Ahmadreza MontazerolghaemAhmadreza Montazerolghaem
In modern distributed network environments, particularly in Internet of Things infrastructures and 5G networks, stringent privacy preservation and scalability requirements have cre…
Machine Learning-Driven Content Popularity Prediction and Cache Optimization in D2D Clustered Networks
Maede Rezaei, Ahmadreza Montazerolghaem
Advancements in wireless communication technology have led to the widespread use of smart devices including computers, mobile phones, tablets, wearable devices, and vehicles which…
A Hybrid Cluster-Based Classification Model for Anomaly Detection in Unbalanced IoT Networks
Hossein Shaemi Barzoki, Amir Hossein Fathi Hafshejani, Ahmadreza Montazerolghaem
Detecting anomalies in Internet of Things (IoT) networks is a critical security challenge, often hampered by highly imbalanced and diverse network traffic datasets. Standard classi…
XAI FL-IDS: A Federated Learning and SHAP-Based Explainable Framework for Distributed Intrusion Detection Systems
Mohammad Hossein Gholamrezazadeh, AhmadReza Montazerolghaem
An Intrusion Detection System (IDS) is vital in cybersecurity, detecting unauthorized activity across networks. With attacks on network layers increasing, stronger IDSs are needed.…