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Ammar Almomani
Researcher at Al-Balqa` Applied University
Publications - 70
Citations - 1665
Ammar Almomani is an academic researcher from Al-Balqa` Applied University. The author has contributed to research in topics: Computer science & Botnet. The author has an hindex of 16, co-authored 52 publications receiving 1060 citations. Previous affiliations of Ammar Almomani include Universiti Sains Malaysia.
Papers
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A Survey of Phishing Email Filtering Techniques
TL;DR: This is the first comprehensive survey to discuss methods of protection against phishing email attacks in detail, and presents an overview of the various techniques presently used to detect phishing emails, at the different stages of attack, mostly focusing on machine-learning techniques.
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IoT transaction processing through cooperative concurrency control on fog–cloud computing environment
TL;DR: The researcher found that the proposed mechanism shall enable low-latency fog computing services of the IoT applications that are a delay sensitive and reduces the communication delay significantly.
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Secure and imperceptible digital image steganographic algorithm based on diamond encoding in DWT domain
TL;DR: Results are showing that the proposed algorithm is secure against the powerful universal steganalyzer “ensemble classifier” and the histogram attack, and robust against different image processing attacks such as compression, added noise, and cropping attacks.
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A survey of botnet detection based on DNS
TL;DR: This paper is the first survey to discuss DNS-based botnet detection techniques in which the problems, existing solutions and the future research direction in the field ofBotnet detection based on DNS traffic analysis for effective botnets detection mechanisms in the future are explored and clarified.
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The monarch butterfly optimization algorithm for solving feature selection problems
Mohammed Alweshah,Saleh Al khalaileh,Brij B. Gupta,Brij B. Gupta,Ammar Almomani,Abdelaziz I. Hammouri,Mohammed Azmi Al-Betar +6 more
TL;DR: The use of the MBO to solve the FS problems has been proven through the results obtained to be effective and highly efficient in this field, and the results have also proven the strength of the balance between global and local search of MBO.