Netflow datasets for machine learning-based network intrusion detection systems M Sarhan, S Layeghy, N Moustafa, M Portmann Big Data Technologies and Applications: 10th EAI International Conference …, 2021 | 342 | 2021 |
Towards a standard feature set for network intrusion detection system datasets M Sarhan, S Layeghy, M Portmann Mobile networks and applications, 1-14, 2022 | 253 | 2022 |
E-graphsage: A graph neural network based intrusion detection system for iot WW Lo, S Layeghy, M Sarhan, M Gallagher, M Portmann NOMS 2022-2022 IEEE/IFIP Network Operations and Management Symposium, 1-9, 2022 | 250 | 2022 |
Wireless mesh networks for public safety and crisis management applications M Portmann, AA Pirzada Internet Computing, IEEE 12 (1), 18-25, 2008 | 223 | 2008 |
Efficient topology discovery in software defined networks F Pakzad, M Portmann, WL Tan, J Indulska 2014 8th international conference on signal processing and communication …, 2014 | 154 | 2014 |
Efficient topology discovery in OpenFlow-based software defined networks F Pakzad, M Portmann, WL Tan, J Indulska Computer Communications 77, 52-61, 2016 | 117 | 2016 |
Evaluation of multi-radio extensions to AODV for wireless mesh networks AA Pirzada, M Portmann, J Indulska Proceedings of the 4th ACM international workshop on Mobility management and …, 2006 | 113 | 2006 |
Feature extraction for machine learning-based intrusion detection in IoT networks M Sarhan, S Layeghy, N Moustafa, M Gallagher, M Portmann Digital Communications and Networks, 2022 | 106 | 2022 |
Anomal-E: A self-supervised network intrusion detection system based on graph neural networks E Caville, WW Lo, S Layeghy, M Portmann Knowledge-Based Systems 258, 110030, 2022 | 102 | 2022 |
The (in) security of topology discovery in software defined networks T Alharbi, M Portmann, F Pakzad 2015 IEEE 40th Conference on Local Computer Networks (LCN), 502-505, 2015 | 99 | 2015 |
A process algebra for wireless mesh networks A Fehnker, R Van Glabbeek, P Höfner, A McIver, M Portmann, WL Tan Programming Languages and Systems: 21st European Symposium on Programming …, 2012 | 96 | 2012 |
Task scheduling for energy-harvesting-based IoT: A survey and critical analysis MM Sandhu, S Khalifa, R Jurdak, M Portmann IEEE Internet of Things Journal 8 (18), 13825-13848, 2021 | 94 | 2021 |
Automated analysis of AODV using UPPAAL A Fehnker, R Van Glabbeek, P Höfner, A McIver, M Portmann, WL Tan Tools and Algorithms for the Construction and Analysis of Systems: 18th …, 2012 | 84 | 2012 |
Cost-effective broadcast for fully decentralized peer-to-peer networks M Portmann, A Seneviratne Computer Communications 26 (11), 1159-1167, 2003 | 79 | 2003 |
Cyber threat intelligence sharing scheme based on federated learning for network intrusion detection M Sarhan, S Layeghy, N Moustafa, M Portmann Journal of Network and Systems Management 31 (1), 3, 2023 | 78 | 2023 |
The cost of peer discovery and searching in the gnutella peer-to-peer file sharing protocol M Portmann, P Sookavatana, S Ardon, A Seneviratne Networks, 2001. Proceedings. Ninth IEEE International Conference on, 263-268, 2001 | 77 | 2001 |
MARCH: A distributed content adaptation architecture S Ardon, P Gunningberg, B Landfeldt, Y Ismailov, M Portmann, ... International Journal of Communication Systems 16 (1), 97-115, 2003 | 76 | 2003 |
Feature analysis for machine learning-based IoT intrusion detection M Sarhan, S Layeghy, M Portmann arXiv preprint arXiv:2108.12732, 2021 | 72 | 2021 |
Evaluating standard feature sets towards increased generalisability and explainability of ML-based network intrusion detection M Sarhan, S Layeghy, M Portmann Big Data Research 30, 100359, 2022 | 71 | 2022 |
Securing wireless mesh networks S Glass, M Portmann, V Muthukkumarasamy IEEE Internet Computing 12 (4), 30-36, 2008 | 71 | 2008 |