405 citations · 2.1k across the 16 of their papers we have counts for
4 papers · 2 filters
Feature Extraction for Machine Learning-based Intrusion Detection in IoT Networks
Mohanad Sarhan, Siamak Layeghy, Nour Moustafa +2
A large number of network security breaches in IoT networks have demonstrated the unreliability of current Network Intrusion Detection Systems (NIDSs). Consequently, network interr…
Exploring Edge TPU for Network Intrusion Detection in IoT
Seyedehfaezeh Hosseininoorbin, Siamak Layeghy, Mohanad Sarhan +2
This paper explores Google's Edge TPU for implementing a practical network intrusion detection system (NIDS) at the edge of IoT, based on a deep learning approach. While there are…
E-GraphSAGE: A Graph Neural Network based Intrusion Detection System for IoT
Wai Weng Lo, Siamak Layeghy, Mohanad Sarhan +2
This paper presents a new Network Intrusion Detection System (NIDS) based on Graph Neural Networks (GNNs). GNNs are a relatively new sub-field of deep neural networks, which can le…
Towards a Standard Feature Set for Network Intrusion Detection System Datasets
Mohanad Sarhan, Siamak Layeghy, Marius Portmann
Network Intrusion Detection Systems (NIDSs) are important tools for the protection of computer networks against increasingly frequent and sophisticated cyber attacks. Recently, a l…