1 code implementation • 28 Apr 2023 • Liam Daly Manocchio, Siamak Layeghy, Wai Weng Lo, Gayan K. Kulatilleke, Mohanad Sarhan, Marius Portmann
This paper presents the FlowTransformer framework, a novel approach for implementing transformer-based Network Intrusion Detection Systems (NIDSs).
no code implementations • 15 Dec 2022 • Mohanad Sarhan, Gayan Kulatilleke, Wai Weng Lo, Siamak Layeghy, Marius Portmann
Therefore, this paper proposes a Deep One-Class (DOC) classifier for network intrusion detection by only training on benign network data samples.
no code implementations • 19 Jul 2022 • Wai Weng Lo, Gayan K. Kulatilleke, Mohanad Sarhan, Siamak Layeghy, Marius Portmann
The proposed model comprises a botnet detector and an explainer for automatic forensics.
1 code implementation • 14 Jul 2022 • Evan Caville, Wai Weng Lo, Siamak Layeghy, Marius Portmann
This paper investigates Graph Neural Networks (GNNs) application for self-supervised network intrusion and anomaly detection.
no code implementations • 8 Apr 2022 • Mohanad Sarhan, Wai Weng Lo, Siamak Layeghy, Marius Portmann
The continuous strengthening of the security posture of IoT ecosystems is vital due to the increasing number of interconnected devices and the volume of sensitive data shared.
no code implementations • 20 Mar 2022 • Wai Weng Lo, Gayan K. Kulatilleke, Mohanad Sarhan, Siamak Layeghy, Marius Portmann
The proposed method was evaluated on the Elliptic dataset and shows that our approach outperforms the state-of-the-art in terms of key classification metrics, which demonstrates the potential of self-supervised GNN in the detection of illicit cryptocurrency transactions.
no code implementations • 19 Jan 2022 • Wai Weng Lo, Siamak Layeghy, Mohanad Sarhan, Marcus Gallagher, Marius Portmann
This paper presents a new Android malware detection method based on Graph Neural Networks (GNNs) with Jumping-Knowledge (JK).
2 code implementations • 30 Mar 2021 • Wai Weng Lo, Siamak Layeghy, Mohanad Sarhan, Marcus Gallagher, Marius Portmann
This paper presents a new Network Intrusion Detection System (NIDS) based on Graph Neural Networks (GNNs).