M
Mouhammd Alkasassbeh
Researcher at Princess Sumaya University for Technology
Publications - 62
Citations - 1196
Mouhammd Alkasassbeh is an academic researcher from Princess Sumaya University for Technology. The author has contributed to research in topics: Intrusion detection system & Denial-of-service attack. The author has an hindex of 14, co-authored 62 publications receiving 752 citations. Previous affiliations of Mouhammd Alkasassbeh include University of Portsmouth & Mutah University.
Papers
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Journal ArticleDOI
Detecting Distributed Denial of Service Attacks Using Data Mining Techniques
TL;DR: A new dataset is collected because there were no common data sets that contain modern DDoS attacks in different network layers, such as (SIDDoS, HTTP Flood), and this work incorporates three well-known classification techniques: Multilayer Perceptron (MLP), Naive Bayes and Random Forest.
Posted Content
Evaluation of Machine Learning Algorithms for Intrusion Detection System
TL;DR: In this article, several experiments have been performed and evaluated to assess various machine learning classifiers based on KDD intrusion dataset, which succeeded to compute several performance metrics in order to evaluate the selected classifiers.
Proceedings ArticleDOI
Evaluation of machine learning algorithms for intrusion detection system
TL;DR: Several experiments have been performed and evaluated to assess various machine learning classifiers based on KDD intrusion dataset and it succeeded to compute several performance metrics in order to evaluate the selected classifiers.
Journal ArticleDOI
An efficient reinforcement learning-based Botnet detection approach
Mohammad Alauthman,Nauman Aslam,Mouhammd Alkasassbeh,Suleman Khan,Ahmad Al-Qerem,Kim-Kwang Raymond Choo +5 more
TL;DR: A sophisticated traffic reduction mechanism, integrated with a reinforcement learning technique is proposed, which achieves a relatively low false positive rate and achieves a detection rate of 98.3%.
Journal ArticleDOI
Network fault detection with Wiener filter-based agent
Mouhammd Alkasassbeh,Mo Adda +1 more
TL;DR: A statistical method based on Wiener filter is carried out to capture the abnormal changes in the behaviour of the MIB variables to provide the manager node with a high level of information, rather than large volumes of data relating to each management task.