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Mouhammd Alkasassbeh 0001
Person information
- affiliation: Princess Sumaya University for Technology, Amman, Jordan
- affiliation (former): Mutah University, Department of Information Technology, Karak, Jordan
Other persons with the same name
- Mouhammd Alkasassbeh 0002
— Universiti Utara Malaysia, Sintok, Malaysia
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2020 – today
- 2024
- [j25]Maen Alzubi
Comparative Analysis of Fuzzy Rule Interpolation Techniques Across Various Scenarios Using a Set of Benchmarks. IEEE Access 12: 33140-33153 (2024) - [j24]Jamil Al-Sawwa, Mohammad Almseidin, Mouhammd Alkasassbeh, Khalid Alemerien, Remah Younisse:
Spark-based multi-verse optimizer as wrapper features selection algorithm for phishing attack challenge. Clust. Comput. 27(5): 5799-5814 (2024) - [j23]Mohammad Almseidin, Jamil Al-Sawwa, Mouhammd Alkasassbeh, Maen Alzubi
DT-ARO: Decision Tree-Based Artificial Rabbits Optimization to Mitigate IoT Botnet Exploitation. J. Netw. Syst. Manag. 32(1): 14 (2024) - [c8]Mouhammd Alkasassbeh, Ammar Almomani, Amjad Aldweesh, Ahmad Al-Qerem, Mohammad Alauthman, Khalid M. O. Nahar, Beenu Mago:
Cyberbullying Detection Using Deep Learning: A Comparative Study. ICCR 2024: 1-6 - [c7]Mohammad Alauthman, Ahmad Al-Qerem, Mouhammd Alkasassbeh, Nauman Aslam, Amjad Aldweesh:
Malware Threats Targeting Cryptocurrency: A Comparative Study. ICCR 2024: 1-8 - 2023
- [j22]Mohammad Almseidin
On detecting distributed denial of service attacks using fuzzy inference system. Clust. Comput. 26(2): 1337-1351 (2023) - [j21]Ehab Almasri, Mouhammd Alkasassbeh, Amjad Aldweesh:
Towards Generating a Practical SUNBURST Attack Dataset for Network Attack Detection. Comput. Syst. Sci. Eng. 47(2): 2643-2669 (2023) - 2022
- [j20]Mohammad Almseidin
Cyber-Phishing Website Detection Using Fuzzy Rule Interpolation. Cryptogr. 6(2): 24 (2022) - [j19]Israa Odeh, Mouhammd Alkasassbeh, Mohammad Almseidin:
Diabetic retinopathy detection method using artificial neural network. Int. J. Bioinform. Res. Appl. 18(4): 300-317 (2022) - [j18]Mohammad Almseidin
An Accurate Detection Approach for IoT Botnet Attacks Using Interpolation Reasoning Method. Inf. 13(6): 300 (2022) - [j17]Mohammad Almseidin, Jamil Al-Sawwa, Mouhammd Alkasassbeh:
Generating a benchmark cyber multi-step attacks dataset for intrusion detection. J. Intell. Fuzzy Syst. 43(3): 3679-3694 (2022) - [j16]Majdi K. Qabalin
Android Spyware Detection Using Machine Learning: A Novel Dataset. Sensors 22(15): 5765 (2022) - [d1]Mohammad Almseidin, Jamil Al-Sawwa, Mouhammd Alkasassbeh:
Multi-Step Cyber-Attack Dataset (MSCAD for Intrusion Detection). IEEE DataPort, 2022 - [i21]Mohamed Abushwereb, Mouhammd Alkasassbeh, Mohammad Almseidin, Muhannad Mustafa:
An accurate IoT Intrusion Detection Framework using Apache Spark. CoRR abs/2203.04347 (2022) - 2021
- [j15]Ghazi Al-Naymat, Hanan Hussain
Accurate detection of network anomalies within SNMP-MIB data set using deep learning. Int. J. Comput. Appl. Technol. 66(1): 74-85 (2021) - [c6]Israa Odeh, Mouhammd Alkasassbeh, Mohammad Alauthman
Diabetic Retinopathy Detection using Ensemble Machine Learning. ICIT 2021: 173-178 - [c5]Mohammad Almseidin, Jamil Al-Sawwa, Mouhammd Alkasassbeh:
Anomaly-based Intrusion Detection System Using Fuzzy Logic. ICIT 2021: 290-295 - [i20]Israa Odeh, Mouhammd Alkasassbeh, Mohammad Alauthman:
Diabetic Retinopathy Detection using Ensemble Machine Learning. CoRR abs/2106.12545 (2021) - [i19]Mohammad Almseidin, Jamil Al-Sawwa, Mouhammd Alkasassbeh:
Anomaly-based Intrusion Detection System Using Fuzzy Logic. CoRR abs/2107.12299 (2021) - 2020
- [j14]Zainab Al-Othman, Mouhammd Alkasassbeh, Sherenaz W. Al-Haj Baddar:
An efficient approach to detect IoT botnet attacks using machine learning. J. High Speed Networks 26(3): 241-254 (2020) - [j13]Mouhammd Al-Kasassbeh, Mohammad Almseidin, Khaled Alrfou
Detection of IoT-botnet attacks using fuzzy rule interpolation. J. Intell. Fuzzy Syst. 39(1): 421-431 (2020) - [j12]Mohammad Alauthman
An efficient reinforcement learning-based Botnet detection approach. J. Netw. Comput. Appl. 150 (2020) - [c4]Mouhammd Al-Kasassbeh, Mohammad Ali Abbadi, Ahmed M. Al-Bustanji:
LightGBM Algorithm for Malware Detection. SAI (3) 2020: 391-403 - [p1]Mouhammd Al-Kasassbeh, Safaa Mohammed, Mohammad Alauthman
Feature Selection Using a Machine Learning to Classify a Malware. Handbook of Computer Networks and Cyber Security 2020: 889-904 - [i18]Mohamed Abushwereb, Muhannad Mustafa, Mouhammd Al-Kasassbeh, Malik Qasaimeh:
Attack based DoS attack detection using multiple classifier. CoRR abs/2001.05707 (2020) - [i17]Abdalrahman Hwoij, Mouhammd Al-Kasassbeh, Mustafa Al-Fayoumi:
Detecting Network Anomalies using Rule-based machine learning within SNMP-MIB dataset. CoRR abs/2002.02368 (2020) - [i16]Almaha Abuzuraiq, Mouhammd Alkasassbeh, Mohammad Almseidin:
Intelligent Methods for Accurately Detecting Phishing Websites. CoRR abs/2002.07223 (2020) - [i15]Zainab Al-Othman, Mouhammd Alkasassbeh, Sherenaz W. Al-Haj Baddar:
A State-of-the-Art Review on IoT botnet Attack Detection. CoRR abs/2010.13852 (2020)
2010 – 2019
- 2019
- [j11]Ibrahim Obeidat, Nabhan Hamadneh, Mouhammd Alkasassbeh
Intensive Pre-Processing of KDD Cup 99 for Network Intrusion Classification Using Machine Learning Techniques. Int. J. Interact. Mob. Technol. 13(1): 70-84 (2019) - [j10]Mohammad Almseidin, Almaha Abuzuraiq, Mouhammd Al-Kasassbeh, Nidal Alnidami:
Phishing Detection Based on Machine Learning and Feature Selection Methods. Int. J. Interact. Mob. Technol. 13(12): 171-183 (2019) - [j9]Nabhan Hamadneh, Mouhammd Al-Kasassbeh
Revisiting the Gentle Parameter of the Random Early Detection (RED) for TCP Congestion Control. J. Commun. 14(3): 229-235 (2019) - [j8]Mouhammd Alkasassbeh
Winning tactics with DNS tunnelling. Netw. Secur. 2019(12): 12-19 (2019) - [c3]Ghazi Al-Naymat, Ahmed Hambouz
Evaluating the Impact of Feature Selection Methods on SNMP-MIB Interface Parameters to Accurately Detect Network Anomalies. ISSPIT 2019: 1-6 - [i14]Abdelrahman Manna, Mouhammd Alkasassbeh:
Detecting network anomalies using machine learning and SNMP-MIB dataset with IP group. CoRR abs/1906.00863 (2019) - [i13]Ahmed Hambouz, Mouhammd Alkasassbeh:
Network Attacks Anomaly Detection Using SNMP MIB Interface Parameters. CoRR abs/1906.00865 (2019) - [i12]Nisreen Madi, Mouhammd Alkasassbeh:
Collecting MIB Data from Network Managed by SNMP using Multi Mobile Agents. CoRR abs/1909.02547 (2019) - 2018
- [j7]Adnan Rawashdeh, Mouhammd Alkasassbeh, Muna Al-Hawawreh
An anomaly-based approach for DDoS attack detection in cloud environment. Int. J. Comput. Appl. Technol. 57(4): 312-324 (2018) - [j6]Ghazi Al-Naymat, Mouhammd Al-Kasassbeh, Eshraq Al-Hawari:
Using machine learning methods for detecting network anomalies within SNMP-MIB dataset. Int. J. Wirel. Mob. Comput. 15(1): 67-76 (2018) - [j5]Mouhammd Alkasassbeh
A Novel Hybrid Method for Network Anomaly Detection Based on Traffic Prediction and Change Point Detection. J. Comput. Sci. 14(2): 153-162 (2018) - [j4]Ahmad B. A. Hassanat, V. B. Surya Prasath
Magnetic energy-based feature extraction for low-quality fingerprint images. Signal Image Video Process. 12(8): 1471-1478 (2018) - [c2]Ghazi Al-Naymat, Mouhammd Al-Kasassbeh
Exploiting SNMP-MIB Data to Detect Network Anomalies Using Machine Learning Techniques. IntelliSys (2) 2018: 991-1004 - [i11]Mohammad Almseidin, Maen Alzubi, Szilveszter Kovács, Mouhammd Alkasassbeh:
Evaluation of Machine Learning Algorithms for Intrusion Detection System. CoRR abs/1801.02330 (2018) - [i10]Mouhammd Alkasassbeh:
A Novel Hybrid Method for Network Anomaly Detection Based on Traffic Prediction and Change Point Detection. CoRR abs/1801.05309 (2018) - [i9]Ibrahim Obeidat, Nabhan Hamadneh, Mouhammd Alkasassbeh, Mohammad Almseidin:
Intensive Preprocessing of KDD Cup 99 for Network Intrusion Classification Using Machine Learning Techniques. CoRR abs/1805.10458 (2018) - [i8]Mouhammd Alkasassbeh, Mohammad Almseidin:
Machine Learning Methods for Network Intrusion Detection. CoRR abs/1809.02610 (2018) - [i7]Ghazi Al-Naymat, Mouhammd Al-Kasassbeh, Eshraq Al-Hawari:
Exploiting SNMP-MIB Data to Detect Network Anomalies using Machine Learning Techniques. CoRR abs/1809.02611 (2018) - [i6]Mouhammd Alkasassbeh, Samail Al-Daleen:
Classification of malware based on file content and characteristics. CoRR abs/1810.07252 (2018) - [i5]Mohammad Almseidin, Mouhammd Alkasassbeh, Szilveszter Kovács:
Fuzzy Rule Interpolation and SNMP-MIB for Emerging Network Abnormality. CoRR abs/1811.08954 (2018) - 2017
- [c1]Mohammad Almseidin
Evaluation of machine learning algorithms for intrusion detection system. SISY 2017: 277-282 - [i4]Mouhammd Alkasassbeh:
An empirical evaluation for the intrusion detection features based on machine learning and feature selection methods. CoRR abs/1712.09623 (2017) - 2016
- [j3]Ahmad B. A. Hassanat
Color-based object segmentation method using artificial neural network. Simul. Model. Pract. Theory 64: 3-17 (2016) - [i3]Ahmad B. A. Hassanat, Esra'a Alkafaween, Nedal A. Al-Nawaiseh, Mohammad Ali Abbadi, Mouhammd Alkasassbeh, Mahmoud Bashir Alhasanat:
Enhancing Genetic Algorithms using Multi Mutations. CoRR abs/1602.08313 (2016) - [i2]Ahmad B. A. Hassanat, Esra'a Alkafaween, Nedal A. Al-Nawaiseh, Mohammad Ali Abbadi, Mouhammd Alkasassbeh, Mahmoud Bashir Alhasanat:
Enhancing genetic algorithms using multi mutations. PeerJ Prepr. 4: e2187 (2016) - 2015
- [i1]Mouhammd Alkasassbeh, Ghada Awad Altarawneh, Ahmad B. A. Hassanat:
On Enhancing The Performance Of Nearest Neighbour Classifiers Using Hassanat Distance Metric. CoRR abs/1501.00687 (2015)
2000 – 2009
- 2009
- [j2]Mouhammd Al-Kasassbeh
Network fault detection with Wiener filter-based agent. J. Netw. Comput. Appl. 32(4): 824-833 (2009) - 2008
- [j1]Mouhammd Al-Kasassbeh
Analysis of mobile agents in network fault management. J. Netw. Comput. Appl. 31(4): 699-711 (2008)
Coauthor Index
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last updated on 2024-08-27 22:57 CEST by the dblp team
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