Mohanad Sarhan

Orcid: 0000-0001-8597-6042

According to our database1, Mohanad Sarhan authored at least 19 papers between 2020 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

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Bibliography

2024
FlowTransformer: A transformer framework for flow-based network intrusion detection systems.
Expert Syst. Appl., 2024

Feature extraction for machine learning-based intrusion detection in IoT networks.
Digit. Commun. Networks, 2024

2023
Exploring edge TPU for network intrusion detection in IoT.
J. Parallel Distributed Comput., September, 2023

Inspection-L: self-supervised GNN node embeddings for money laundering detection in bitcoin.
Appl. Intell., August, 2023

XG-BoT: An explainable deep graph neural network for botnet detection and forensics.
Internet Things, July, 2023

Cyber Threat Intelligence Sharing Scheme Based on Federated Learning for Network Intrusion Detection.
J. Netw. Syst. Manag., 2023

From zero-shot machine learning to zero-day attack detection.
Int. J. Inf. Sec., 2023

DOC-NAD: A Hybrid Deep One-class Classifier for Network Anomaly Detection.
Proceedings of the 23rd IEEE/ACM International Symposium on Cluster, 2023

2022
Towards a Standard Feature Set for Network Intrusion Detection System Datasets.
Mob. Networks Appl., 2022

XG-BoT: An Explainable Deep Graph Neural Network for Botnet Detection and Forensics.
CoRR, 2022

HBFL: A hierarchical blockchain-based federated learning framework for collaborative IoT intrusion detection.
Comput. Electr. Eng., 2022

Evaluating Standard Feature Sets Towards Increased Generalisability and Explainability of ML-Based Network Intrusion Detection.
Big Data Res., 2022

E-GraphSAGE: A Graph Neural Network based Intrusion Detection System for IoT.
Proceedings of the 2022 IEEE/IFIP Network Operations and Management Symposium, 2022

Graph Neural Network-based Android Malware Classification with Jumping Knowledge.
Proceedings of the IEEE Conference on Dependable and Secure Computing, 2022

2021
Feature Analysis for ML-based IIoT Intrusion Detection.
CoRR, 2021

An Explainable Machine Learning-based Network Intrusion Detection System for Enabling Generalisability in Securing IoT Networks.
CoRR, 2021

E-GraphSAGE: A Graph Neural Network based Intrusion Detection System.
CoRR, 2021

Towards a Standard Feature Set of NIDS Datasets.
CoRR, 2021

2020
NetFlow Datasets for Machine Learning-Based Network Intrusion Detection Systems.
Proceedings of the Big Data Technologies and Applications, 2020


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