Riyad Alshammari
Riyad Alshammari
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Machine learning based encrypted traffic classification: Identifying ssh and skype
R Alshammari, AN Zincir-Heywood
2009 IEEE symposium on computational intelligence for security and defense …, 2009
Can encrypted traffic be identified without port numbers, IP addresses and payload inspection?
R Alshammari, AN Zincir-Heywood
Computer networks 55 (6), 1326-1350, 2011
A flow based approach for SSH traffic detection
R Alshammari, AN Zincir-Heywood
2007 IEEE international conference on systems, man and cybernetics, 296-301, 2007
Investigating two different approaches for encrypted traffic classification
R Alshammari, AN Zincir-Heywood
2008 Sixth Annual Conference on Privacy, Security and Trust, 156-166, 2008
Identification of VoIP encrypted traffic using a machine learning approach
R Alshammari, AN Zincir-Heywood
Journal of King Saud University-Computer and Information Sciences 27 (1), 77-92, 2015
Comparison of statistical logistic regression and random forest machine learning techniques in predicting diabetes
T Daghistani, R Alshammari
Journal of Advances in Information Technology Vol 11 (2), 78-83, 2020
An investigation on the identification of VoIP traffic: Case study on Gtalk and Skype
R Alshammari, AN Zincir-Heywood
2010 International Conference on Network and Service Management, 310-313, 2010
Using neuro-fuzzy approach to reduce false positive alerts
R Alshammari, S Sonamthiang, M Teimouri, D Riordan
Fifth Annual Conference on Communication Networks and Services Research …, 2007
Diagnosis of diabetes by applying data mining classification techniques
T Daghistani, R Alshammari
International Journal of Advanced Computer Science and Applications 7 (7), 2016
Unveiling Skype encrypted tunnels using GP
R Alshammari, AN Zincir-Heywood
IEEE Congress on Evolutionary Computation, 1-8, 2010
Type-2 diabetes mellitus diagnosis from time series clinical data using deep learning models
Z Alhassan, AS McGough, R Alshammari, T Daghstani, D Budgen, ...
Artificial Neural Networks and Machine Learning–ICANN 2018: 27th …, 2018
Generalization of signatures for ssh encrypted traffic identification
R Alshammari, N Zincir-Heywood
2009 IEEE Symposium on Computational Intelligence in Cyber Security, 167-174, 2009
Prediction of Stroke using Data Mining Classification Techniques
OAR Alshammar
International Journal of Advanced Computer Science and Applications(IJACSA …, 2018
Middle east and North African health informatics association (MENAHIA): building sustainable collaboration
N Al-Shorbaji, M Househ, A Taweel, A Alanizi, BO Mohammed, H Abaza, ...
Yearbook of medical informatics 27 (01), 286-291, 2018
Predictors of outpatients’ no-show: big data analytics using apache spark
T Daghistani, H AlGhamdi, R Alshammari, RH AlHazme
Journal of Big Data 7, 1-15, 2020
Improving accelerometer-based activity recognition by using ensemble of classifiers
T Daghistani, R Alshammari
International journal of advanced computer science and applications 7 (5), 2016
Classifying ssh encrypted traffic with minimum packet header features using genetic programming
R Alshammari, PI Lichodzijewski, M Heywood, AN Zincir-Heywood
Proceedings of the 11th annual conference companion on genetic and …, 2009
Stacked denoising autoencoders for mortality risk prediction using imbalanced clinical data
Z Alhassan, D Budgen, R Alshammari, T Daghstani, AS McGough, ...
2018 17th IEEE International Conference on Machine Learning and Applications …, 2018
Arabic text categorization using machine learning approaches
R Alshammari
International Journal of Advanced Computer Science and Applications 9 (3), 2018
How robust can a machine learning approach be for classifying encrypted VoIP?
R Alshammari, AN Zincir-Heywood
Journal of Network and Systems Management 23, 830-869, 2015
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