7 papers
ASA: Adaptive Smart Agent Federated Learning via Device-Aware Clustering for Heterogeneous IoT
Ali Salimi, Saadat Izadi, Mahmood Ahmadi +1
Federated learning (FL) has become a promising answer to facilitating privacy-preserving collaborative learning in distributed IoT devices. However, device heterogeneity is a key c…
A Q-Learning Approach for Dynamic Resource Management in Three-Tier Vehicular Fog Computing
Bahar Mojtabaei Ranani, Mahmood Ahmadi, Sajad Ahmadian
In this paper, a method for predicting the resources required for an intelligent vehicle client using a three-layer vehicular computing architecture is proposed. This method levera…
CF-HFC:Calibrated Federated based Hardware-aware Fuzzy Clustering for Intrusion Detection in Heterogeneous IoTs
Saadat Izadi, Mahmood Ahmadi
The rapid expansion of heterogeneous Internet of Things (IoT) environments has heightened security risks, as resource-constrained devices remain vulnerable to diverse cyberattacks.…
Lightweight Cluster-Based Federated Learning for Intrusion Detection in Heterogeneous IoT Networks
Saadat Izadi, Mahmood Ahmadi
The rise of heterogeneous Internet of Things (IoT) devices has raised security concerns due to their vulnerability to cyberattacks. Intrusion Detection Systems (IDS) are crucial in…
Adaptive Meta-Aggregation Federated Learning for Intrusion Detection in Heterogeneous Internet of Things
Saadat Izadi, Mahmood Ahmadi
The rapid proliferation of the Internet of Things (IoT) has brought remarkable advancements to industries by enabling interconnected systems and intelligent automation. However, th…
Mist-Assisted Federated Learning for Intrusion Detection in Heterogeneous IoT Networks
Saadat Izadi, Shakib Komasi, Ali Salimi +2
The rapid growth of the Internet of Things (IoT) offers new opportunities but also expands the attack surface of distributed, resource-limited devices. Intrusion detection in such…