Mouhammd Alkasassbeh

Orcid: 0000-0001-8396-7441

Affiliations:
  • Princess Sumaya University for Technology, Amman, Jordan
  • Mutah University, Department of Information Technology, Karak, Jordan (former)


According to our database1, Mouhammd Alkasassbeh authored at least 47 papers between 2008 and 2024.

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

Timeline

Legend:

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Article 
PhD thesis 
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Online presence:

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Bibliography

2024
DT-ARO: Decision Tree-Based Artificial Rabbits Optimization to Mitigate IoT Botnet Exploitation.
J. Netw. Syst. Manag., March, 2024

Comparative Analysis of Fuzzy Rule Interpolation Techniques Across Various Scenarios Using a Set of Benchmarks.
IEEE Access, 2024

2023
On detecting distributed denial of service attacks using fuzzy inference system.
Clust. Comput., April, 2023

Towards Generating a Practical SUNBURST Attack Dataset for Network Attack Detection.
Comput. Syst. Sci. Eng., 2023

2022
Multi-Step Cyber-Attack Dataset (MSCAD for Intrusion Detection).
Dataset, June, 2022

Android Spyware Detection Using Machine Learning: A Novel Dataset.
Sensors, 2022

Generating a benchmark cyber multi-step attacks dataset for intrusion detection.
J. Intell. Fuzzy Syst., 2022

An Accurate Detection Approach for IoT Botnet Attacks Using Interpolation Reasoning Method.
Inf., 2022

Diabetic retinopathy detection method using artificial neural network.
Int. J. Bioinform. Res. Appl., 2022

Cyber-Phishing Website Detection Using Fuzzy Rule Interpolation.
Cryptogr., 2022

An accurate IoT Intrusion Detection Framework using Apache Spark.
CoRR, 2022

2021
Accurate detection of network anomalies within SNMP-MIB data set using deep learning.
Int. J. Comput. Appl. Technol., 2021

Diabetic Retinopathy Detection using Ensemble Machine Learning.
Proceedings of the International Conference on Information Technology, 2021

Anomaly-based Intrusion Detection System Using Fuzzy Logic.
Proceedings of the International Conference on Information Technology, 2021

2020
An efficient reinforcement learning-based Botnet detection approach.
J. Netw. Comput. Appl., 2020

Detection of IoT-botnet attacks using fuzzy rule interpolation.
J. Intell. Fuzzy Syst., 2020

An efficient approach to detect IoT botnet attacks using machine learning.
J. High Speed Networks, 2020

A State-of-the-Art Review on IoT botnet Attack Detection.
CoRR, 2020

Intelligent Methods for Accurately Detecting Phishing Websites.
CoRR, 2020

Detecting Network Anomalies using Rule-based machine learning within SNMP-MIB dataset.
CoRR, 2020

Attack based DoS attack detection using multiple classifier.
CoRR, 2020

LightGBM Algorithm for Malware Detection.
Proceedings of the Intelligent Computing, 2020

Feature Selection Using a Machine Learning to Classify a Malware.
Proceedings of the Handbook of Computer Networks and Cyber Security, 2020

2019
Winning tactics with DNS tunnelling.
Netw. Secur., 2019

Revisiting the Gentle Parameter of the Random Early Detection (RED) for TCP Congestion Control.
J. Commun., 2019

Intensive Pre-Processing of KDD Cup 99 for Network Intrusion Classification Using Machine Learning Techniques.
Int. J. Interact. Mob. Technol., 2019

Phishing Detection Based on Machine Learning and Feature Selection Methods.
Int. J. Interact. Mob. Technol., 2019

Collecting MIB Data from Network Managed by SNMP using Multi Mobile Agents.
CoRR, 2019

Network Attacks Anomaly Detection Using SNMP MIB Interface Parameters.
CoRR, 2019

Detecting network anomalies using machine learning and SNMP-MIB dataset with IP group.
CoRR, 2019

Evaluating the Impact of Feature Selection Methods on SNMP-MIB Interface Parameters to Accurately Detect Network Anomalies.
Proceedings of the IEEE International Symposium on Signal Processing and Information Technology, 2019

2018
Magnetic energy-based feature extraction for low-quality fingerprint images.
Signal Image Video Process., 2018

A Novel Hybrid Method for Network Anomaly Detection Based on Traffic Prediction and Change Point Detection.
J. Comput. Sci., 2018

Using machine learning methods for detecting network anomalies within SNMP-MIB dataset.
Int. J. Wirel. Mob. Comput., 2018

An anomaly-based approach for DDoS attack detection in cloud environment.
Int. J. Comput. Appl. Technol., 2018

Fuzzy Rule Interpolation and SNMP-MIB for Emerging Network Abnormality.
CoRR, 2018

Classification of malware based on file content and characteristics.
CoRR, 2018

Machine Learning Methods for Network Intrusion Detection.
CoRR, 2018

Intensive Preprocessing of KDD Cup 99 for Network Intrusion Classification Using Machine Learning Techniques.
CoRR, 2018

Exploiting SNMP-MIB Data to Detect Network Anomalies Using Machine Learning Techniques.
Proceedings of the Intelligent Systems and Applications, 2018

2017
An empirical evaluation for the intrusion detection features based on machine learning and feature selection methods.
CoRR, 2017

Evaluation of machine learning algorithms for intrusion detection system.
Proceedings of the 15th IEEE International Symposium on Intelligent Systems and Informatics, 2017

2016
Color-based object segmentation method using artificial neural network.
Simul. Model. Pract. Theory, 2016

Enhancing genetic algorithms using multi mutations.
PeerJ Prepr., 2016

2015
On Enhancing The Performance Of Nearest Neighbour Classifiers Using Hassanat Distance Metric.
CoRR, 2015

2009
Network fault detection with Wiener filter-based agent.
J. Netw. Comput. Appl., 2009

2008
Analysis of mobile agents in network fault management.
J. Netw. Comput. Appl., 2008


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