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ORCIDRiyad Alshammari
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2020 – today
- 2023
[j5]Abdulwahhab Alshammari
, Noorah Atiyah, Hanoof Alaboodi, Riyad Alshammari:
Identification of stroke using deepnet machine learning algorithm. Int. J. Medical Eng. Informatics 15(5): 416-429 (2023)- [c21]Zolboo Erdenebaatar, Riyad Alshammari, Biswajit Nandy, Nabil Seddigh, Marwa Elsayed, Nur Zincir-Heywood:
Depicting Instant Messaging Encrypted Traffic Characteristics through an Empirical Study. ICCCN 2023: 1-10 - [c20]Zolboo Erdenebaatar, Riyad Alshammari, Nur Zincir-Heywood, Marwa Elsayed, Biswajit Nandy, Nabil Seddigh:
Analyzing Traffic Characteristics of Instant Messaging Applications on Android Smartphones. NOMS 2023: 1-5 - [c19]Zolboo Erdenebaatar, Biswajit Nandy, Nabil Seddigh, Riyad Alshammari, Marwa Elsayed, Nur Zincir-Heywood:
Instant Messaging Application Encrypted Traffic Generation System. NOMS 2023: 1-3 - [d1]Zolboo Erdenebaatar, Riyad Alshammari, Nur Zincir-Heywood, Marwa Elsayed, Biswajit Nandy, Nabil Seddigh:
Encrypted Mobile Instant Messaging Traffic Dataset. IEEE DataPort, 2023
- 2021
- [c18]Asma Kausar, Imran Razzak, Mohd Ibrahim Shapiai, Riyad Alshammari:
An Improved Dense V-Network for Fast and Precise Segmentation of Left Atrium. IJCNN 2021: 1-8 - 2020
- [j4]Tahani Daghistani, Huda Alghamdi, Riyad Alshammari, Raed H. AlHazme:
Predictors of outpatients' no-show: big data analytics using apache spark. J. Big Data 7(1): 108 (2020)
2010 – 2019
- 2019
- [c17]Moath Bagarish, Riyad Alshammari, Nur Zincir-Heywood:
Are There Bots even in FIFA World Cup 2018 Tweets? CNSM 2019: 1-5 - [c16]Zakhriya Alhassan, David Budgen, Ali Alessa, Riyad Alshammari, Tahani Daghstani, Noura Al Moubayed:
Collaborative Denoising Autoencoder for High Glycated Haemoglobin Prediction. ICANN (Workshop) 2019: 338-350 - 2018
- [c15]Zakhriya Alhassan, A. Stephen McGough, Riyad Alshammari, Tahani Daghstani, David Budgen, Noura Al Moubayed:
Type-2 Diabetes Mellitus Diagnosis from Time Series Clinical Data Using Deep Learning Models. ICANN (3) 2018: 468-478 - [c14]Zakhriya Alhassan, David Budgen, Riyad Alshammari, Tahani Daghstani, A. Stephen McGough, Noura Al Moubayed:
Stacked Denoising Autoencoders for Mortality Risk Prediction Using Imbalanced Clinical Data. ICMLA 2018: 541-546 - 2017
- [e1]Abdelkader Hameurlain, Josef Küng, Roland R. Wagner, Sherif Sakr, Imran Razzak, Riyad Alshammari:
Transactions on Large-Scale Data- and Knowledge-Centered Systems XXXV. Lecture Notes in Computer Science 10680, Springer 2017, ISBN 978-3-662-56120-1 [contents] - 2015
- [j3]Riyad Alshammari, Nur Zincir-Heywood:
Identification of VoIP encrypted traffic using a machine learning approach. J. King Saud Univ. Comput. Inf. Sci. 27(1): 77-92 (2015) - [j2]Riyad Alshammari, Nur Zincir-Heywood:
How Robust Can a Machine Learning Approach Be for Classifying Encrypted VoIP? J. Netw. Syst. Manag. 23(4): 830-869 (2015) - [c13]Mowafa S. Househ, Riyad Alshammari, Mariam Almutairi, Amr Jamal, Saleh Alshoaib:
Building a Culture of Health Informatics Innovation and Entrepreneurship: A New Frontier. ICIMTH 2015: 237-240 - 2014
- [c12]Mowafa S. Househ, Riyad Alshammari, Huda Jradi, Omar B. Da'ar, Basema Saddik, Ahmed Alamry:
Aligning Public Health and Health Informatics Research Strengths with National Level Research Priorities in Saudi Arabia. ICIMTH 2014: 249-252 - 2012
- [c11]Riyad Alshammari, Nur Zincir-Heywood:
The Impact of Evasion on the Generalization of Machine Learning Algorithms to Classify VoIP Traffic. ICCCN 2012: 1-8 - 2011
- [j1]Riyad Alshammari, Nur Zincir-Heywood:
Can encrypted traffic be identified without port numbers, IP addresses and payload inspection? Comput. Networks 55(6): 1326-1350 (2011) - [c10]Riyad Alshammari, Nur Zincir-Heywood:
Is machine learning losing the battle to produce transportable signatures against VoIP traffic? IEEE Congress on Evolutionary Computation 2011: 1543-1550 - 2010
- [c9]Riyad Alshammari, Nur Zincir-Heywood:
Unveiling Skype encrypted tunnels using GP. IEEE Congress on Evolutionary Computation 2010: 1-8 - [c8]Riyad Alshammari, Nur Zincir-Heywood:
An investigation on the identification of VoIP traffic: Case study on Gtalk and Skype. CNSM 2010: 310-313
2000 – 2009
- 2009
- [c7]Riyad Alshammari, Nur Zincir-Heywood:
Generalization of signatures for SSH encrypted traffic identification. CICS 2009: 167-174 - [c6]Riyad Alshammari, Nur Zincir-Heywood:
Machine learning based encrypted traffic classification: Identifying SSH and Skype. CISDA 2009: 1-8 - [c5]Riyad Alshammari, Peter Lichodzijewski, Malcolm I. Heywood, Nur Zincir-Heywood:
Classifying SSH encrypted traffic with minimum packet header features using genetic programming. GECCO (Companion) 2009: 2539-2546 - 2008
- [c4]Riyad Alshammari, Nur Zincir-Heywood:
A Preliminary Performance Comparison of Two Feature Sets for Encrypted Traffic Classification. CISIS 2008: 203-210 - [c3]Riyad Alshammari, Nur Zincir-Heywood:
Investigating Two Different Approaches for Encrypted Traffic Classification. PST 2008: 156-166 - 2007
- [c2]Riyad Alshammari, Sumalee Sonamthiang, Mohsen Teimouri, Denis Riordan:
Using Neuro-Fuzzy Approach to Reduce False Positive Alerts. CNSR 2007: 345-349 - [c1]Riyad Alshammari, Nur Zincir-Heywood:
A flow based approach for SSH traffic detection. SMC 2007: 296-301
Coauthor Index
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