M
Monther Aldwairi
Researcher at Zayed University
Publications - 79
Citations - 1737
Monther Aldwairi is an academic researcher from Zayed University. The author has contributed to research in topics: Computer science & Intrusion detection system. The author has an hindex of 16, co-authored 68 publications receiving 1214 citations. Previous affiliations of Monther Aldwairi include North Carolina State University & Jordan University of Science and Technology.
Papers
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Journal ArticleDOI
Anomaly-based intrusion detection system through feature selection analysis and building hybrid efficient model
TL;DR: A new hybrid model can be used to estimate the intrusion scope threshold degree based on the network transaction data’s optimal features that were made available for training and revealed that the hybrid approach had a significant effect on the minimisation of the computational and time complexity involved when determining the feature association impact scale.
Journal ArticleDOI
Detecting Fake News in Social Media Networks
Monther Aldwairi,Ali Alwahedi +1 more
TL;DR: This work uses simple and carefully selected features of the title and post to accurately identify fake posts and comes up with a solution that can be utilized by users to detect and filter out sites containing false and misleading information.
Journal ArticleDOI
Configurable string matching hardware for speeding up intrusion detection
TL;DR: A configurable string matching accelerator is developed with the focus on increasing throughput while maintaining the configurability provided by the software IDSs.
Journal ArticleDOI
Fog Computing Enabling Industrial Internet of Things: State-of-the-Art and Research Challenges.
Rabeea Basir,Saad Qaisar,Mudassar Ali,Mudassar Ali,Monther Aldwairi,Muhammad Ikram Ashraf,Aamir Mahmood,Mikael Gidlund +7 more
TL;DR: A comprehensive review of methods and techniques in fog computing is provided, providing solutions to critical challenges and as an enabler for IIoT application domains and open research challenges are discussed to enlighten fog computing aspects in different fields and technologies.
Proceedings ArticleDOI
Automated malicious advertisement detection using VirusTotal, URLVoid, and TrendMicro
Rima Masri,Monther Aldwairi +1 more
TL;DR: This paper proposes and implements a system for automatically detecting malicious advertisements, which employs three different online malware domain detections systems (VirusTotal, URLVoid, and TrendMicro) for malicious advertisements detection purposes and reports the number of detected malicious advertisements using each system.