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Name : Mohammad Alauthman

Academic Rank: Assistant Professor

Administrative Position : Head of Department

Office       Ext No

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Specialization: Network Security

Graduate Of: Northumbria University






    Hashemite University
    Amman Arab University
    Northumbria University
    United Kingdom

  • Journal Paper

      Mohammad Alauthman, Nauman Aslam, Mouhammd Al-Kasassbeh, Suleman Khan, Ahmad Al-Qerem, Kim-Kwang Raymond Choo, " An efficient reinforcement learning-based Botnet detection approach " , "Journal of Network and Computer Applications",Vol.150,No., Elsevier, USA, 01/15/2020 Abstract:
      The use of bot malware and botnets as a tool to facilitate other malicious cyber activities (e.g. distributed denial of service attacks, dissemination of malware and spam, and click fraud). However, detection of botnets, particularly peer-to-peer (P2P) botnets, is challenging. Hence, in this paper we propose a sophisticated traffic reduction mechanism, integrated with a reinforcement learning technique. We then evaluate the proposed approach using real-world network traffic, and achieve a detection rate of 98.3%. The approach also achieves a relatively low false positive rate (i.e. 0.012%).

      Ayoub Alsarhan, Abdel-Rahman Al-Ghuwairi, Islam T Almalkawi, Mohammad Alauthman, Ahmed Al-Duba, " Machine Learning-Driven Optimization for Intrusion Detection in Smart Vehicular Networks " , "Wireless Personal Communications",Vol.Online first,No., Springer, Netherlands, 09/08/2020 Abstract:
      An essential element in the smart city vision is providing safe and secure journeys via intelligent vehicles and smart roads. Vehicular ad hoc networks (VANETs) have played a significant role in enhancing road safety where vehicles can share road information conditions. However, VANETs share the sam

      Ahmad Al-Nawasrah, Ammar Ali Almomani, Samer Atawneh, Mohammad Alauthman, " A Survey of Fast Flux Botnet Detection With Fast Flux Cloud Computing " , "International Journal of Cloud Applications and Computing ",Vol.10,No., IGI Global, USA, 07/01/2020 Abstract:
      A botnet refers to a set of compromised machines controlled distantly by an attacker. Botnets are considered the basis of numerous security threats around the world. Command and control (C&C) servers are the backbone of botnet communications, in which bots send a report to the botmaster, and the lat

      Kamal Alieyan, Ammar Almomani, Mohammed Anbar, Mohammad Alauthman, Rosni Abdullah, BB Gupta, " DNS rule-based schema to botnet detection " , "Enterprise Information Systems ",Vol.14,No., Taylor & Francis, United Kingdom , 07/25/2019 Abstract:
      Botnets are considered a serious issue today. They have several negative economic impacts as well. Such impacts are affecting organizations and individuals. Recent botnets–such as Zeus and Citadel’s Conficker–use the Domain Name System (DNS) to avoid detection. These botnets use the DNS server to pr

      Ahmad Al-Qerem, Mohammad Alauthman, Ammar Almomani, BB Gupta, " IoT transaction processing through cooperative concurrency control on fog–cloud computing environment " , "Soft Computing",Vol.24,No., Springer, Berlin Heidelberg, 04/01/2020 Abstract:
      In cloud–fog environments, the opportunity to avoid using the upstream communication channel from the clients to the cloud server all the time is possible by fluctuating the conventional concurrency control protocols. Through the present paper, the researcher aimed to introduce a new variant of the

      Ammar Almomani, Mohammad Alauthman, Mohammed Alweshah, O Dorgham, Firas Albalas, " A comparative study on spiking neural network encoding schema: implemented with cloud computing " , "Cluster Computing",Vol.22,No., springer, Netherlands , 06/15/2019 Abstract:
      Spiking neural networks (SNN) represents the third generation of neural network models, it differs significantly from the early neural network generation. The time is becoming the most important input. The presence and precise timing of spikes encapsulate have a meaning such as human brain behavior.

      Mohammad Alauthman, Nauman Aslam, Li Zhang, Rafe Alasem, M Alamgir Hossain, " A P2P Botnet detection scheme based on decision tree and adaptive multilayer neural networks " , "Neural Computing and Applications",Vol.29,No., Springer , London, 06/04/2018 Abstract:
      In recent years, Botnets have been adopted as a popular method to carry and spread many malicious codes on the Internet. These malicious codes pave the way to execute many fraudulent activities including spam mail, distributed denial-of-service attacks and click fraud. While many Botnets are set up

      Ammar Almomani, Mohammad Alauthman, Firas Albalas, O Dorgham, Atef Obeidat, " An online intrusion detection system to cloud computing based on NeuCube algorithms " , "International Journal of Cloud Applications and Computing ",Vol.8,No., IGI-Global, USA, 04/02/2018 Abstract:
      This article describes how as network traffic grows, attacks on traffic become more complicated and harder to detect. Recently, researchers have begun to explore machine learning techniques with cloud computing technologies to classify network threats. So, new and creative ways are needed to enhance

      Smadi, S. , Alauthman, M. , Almomani, O. , Saaidah, A. , Alzobi, F., " Application layer denial of services attack detection based on stacknet " , "International Journal of Advanced Trends in Computer Science and Engineering,",Vol.9,No., Warse, india, 06/30/2020 Abstract:
      Denial of Services (DoS) Attack is one of the most advanced attacks targeting cybercriminals. The DoS attack is designed to reduce the performance of network devices by performing their intended functions. In addition, the confidentiality, reliability and quality of data can be compromised by DoS at

      Ammar Almomani, Ahmad Al-Nawasrah, Mohammad Alauthman, Mohammed Azmi Al-Betar, Farid Meziane , " Botnet detection used fast-flux technique, based on adaptive dynamic evolving spiking neural network algorithm " , "International Journal of Ad Hoc and Ubiquitous Computing",Vol.36,No., inderscience, United Kingdom , 01/28/2021 Abstract:
      A botnet refers to a group of machines. These machines are controlled distantly by a specific attacker. It represents a threat facing the web and data security. Fast-flux service network (FFSN) has been engaged by bot herders for cover malicious botnet activities. It has been engaged by bot herders

      Ayoub Alsarhan, Mohammad Alauthman, Esra’a Alshdaifat, Abdel-Rahman Al-Ghuwairi and Ahmed Al-Dubai , " Machine Learning-driven optimization for SVM-based intrusion detection system in vehicular ad hoc networks " , "Journal of Ambient Intelligence and Humanized Computing",Vol.12,No., springer, Germany, 02/24/2021 Abstract:
      Machine learning (ML) driven solutions have been widely used to secure wireless communications Vehicular ad hoc networks (VANETs) in recent studies. Unlike existing works, this paper applies support vector machine (SVM) for intrusion detection in VANET. The structure of SVM has many computation adva

      Rizwan Hamid Randhawa; Nauman Aslam; Mohammad Alauthman; Husnain Rafiq; Frank Comeau, " Security Hardening of Botnet Detectors using Generative Adversarial Networks " , "IEEE Access",Vol.Early Access,No., IEEE Access, United States, 05/25/2021 Abstract:
      Machine learning (ML) based botnet detectors are no exception to traditional ML models when it comes to adversarial evasion attacks. The datasets used to train these models have also scarcity and imbalance issues. We propose a new technique named Botshot, based on generative adversarial networks (GA

      Ammar Almomani, Mohammad Alauthman, Mohd Taib Shatnawi, Mohammed Alweshah, Ayat Alrosan, Waleed Alomoush, Brij B. Gupta, " Phishing Website Detection With Semantic Features Based on Machine Learning Classifiers: A Comparative Study " , "International Journal on Semantic Web and Information Systems (IJSWIS)",Vol.18,No., IGI, USA, 03/22/2022

  • Chapter in a Book

      Mohammad Alauthman, Ammar Almomani, Mohammed Alweshah, Waleed Omoush, Kamal Alieyan, " Machine Learning for Phishing Detection and Mitigation " , "Machine Learning for Computer and Cyber Security",Vol.1,No., CRC Press, USA, 02/03/2019 Abstract:
      Phishing e-mails refer to fraudulent e-mails sent with the aim of deceiving people and tricking them into revealing confidential information, such as passwords, usernames and credit card information. Such information may be related to the bank account. This is done to make an illegal financial gain.

      Mouhammd Al-Kasassbeh, Safaa Mohammed, Mohammad Alauthman and Ammar Almomani, " Feature Selection Using a Machine Learning to Classify a Malware " , "Handbook of Computer Networks and Cyber Security",Vol.1,No., Springer, Cham, Switzerland , 01/01/2020 Abstract:
      Generally, malware has come to be known as one of the biggest threats, so malware is a program which operates malicious actions and steals information, to specifically identify it as software which is designed specifically to through breaking the system of a computer without consent from the owner.

      Ahmad al-Qerem, Bushra Abutahoun, Shadi Nashwan, Shatha Shakhatreh, Mohammad Alauthman, Almmar Almomani, " Network-Based Detection of Mirai Botnet Using Machine Learning and Feature Selection Methods " , "Handbook of Research on Multimedia Cyber Security",Vol.1,No., IGI global, USA, 04/20/2020 Abstract:
      The spread of IoT devices is significantly increasing worldwide with a low design security that makes it more easily compromised than desktop computers. This gives rise to the phenomenon of IoT-based botnet attacks such as Mirai botnet, which have recently emerged as a high-profile threat that conti

      ALMOMANI, M ALAUTHMAN, N ASLAM, O DORGHAM, M AL-REFAI, " Botnet Behavior and Detection Techniques: A Review " , "Computer and Cyber Security: Principles, Algorithm, Applications, and Perspectives",Vol.1,No., CRC Press, USA, 10/19/2018 Abstract:
      n recent years, there has been increasing interest in Botnet problems compared to others threats to computing. Malware has infected every area of the Internet, and this shows no signs of stopping. Despite the relative novelty of Botnets, a significant number of studies have attempted

      Kamal Alieyan, Ammar Almomani, Rosni Abdullah, Badr Almutairi, Mohammad Alauthman, " Botnet and Internet of Things (IoTs): A Definition, Taxonomy, Challenges, and Future Directions " , "Security, Privacy, and Forensics Issues in Big Data",Vol.1,No., IGI, USA, 02/10/2020 Abstract:
      In today's internet world the internet of things (IoT) is becoming the most significant and developing technology. The primary goal behind the IoT is enabling more secure existence along with the improvement of risks at various life levels. With the arrival of IoT botnets, the perspective towards Io

  • Conference paper

      M. Alauthman, G. Albesani, " Application-Layer Dos Attack Detection Using Machine Learning " , "International Conference on Data Science, Machine Learning and Statistics - 2019 (DMS-2019)",Vol.1,No., International Conference on Data Science, Machine Learning and Statistics - 2019 (DMS-2019), Van, Turkey, 07/25/2019 Abstract:
      The greatest risk to internet networks is denial of service (DoS) attacks. Where availability for network security is the primary goal, DoS attacks aim at breaking down servers to stop or diminish the availability of services by preventing or limiting the use of these services by legitimate users. D

      Kamal Alieyan ; Mohammed Anbar ; Ammar Almomani ; Rosni Abdullah ; Mohammad Alauthman, " Botnets Detecting Attack Based on DNS Features " , "Security, Privacy, and Forensics Issues in Big Data",Vol.1,No., 2018 International Arab Conference on Information Technology (ACIT), Werdanye, Lebanon, 10/30/2018 Abstract:
      A botnet is considered a serious issue that threatens cyber security. It is a mean used by cybercriminals for carrying out their illegal activities. Such activities may include click fraud and DDoS attacks. The present paper aims to propose a new filtering approach called “The Gunner System”. The me

      Ahmad Al-Nawasrah ; Ammar Al-Momani ; Farid Meziane ; Mohammad Alauthman, " Fast flux botnet detection framework using adaptive dynamic evolving spiking neural network algorithm " , "2018 9th International Conference on Information and Communication Systems (ICICS)",Vol.1,No., IEEE, Irbid, Jordan, 04/02/2018 Abstract:
      A botnet, a set of compromised machines controlled distantly by an attacker, is the basis of numerous security threats around the world. Command and Control servers are the backbones of botnet communications, where the bots and botmasters send report and attack orders to each other. Botnets are also

      Almomani Ammar, Alauthman Mohammad, Almomani Omar, Albalas Firas, " A Proposed Framework for Botnet Spam-email Filtering Using Neucube " , "The International Arab Conference on Information Technology, ACIT’2017",Vol.17,No., The International Arab Conference on Information Technology, Yassmine Hammamet, Tunisia, 11/26/2017 Abstract:
      The voluminous amount of SPAM emails that originated from different botnets worldwide has a direct effect on the limited capacity of mailboxes, security of personal mail, space-loss from the communication as well as the time that is required to identify and address the spam emails. These issues are

      Mohammad Aluthman, Nauman Aslam, M.A. Hossain, Rafe Alasem, " Investigation of peer-to-peer botnet using TCP control packets and data mining techniques " , "Software, Knowledge, Information Management and Applications (SKIMA 2013)",Vol.7,No., inderscience, Chiang Mai, Thailand, 11/14/2013 Abstract:
      Nowadays botnets are commonly used in cyber-attacks and malicious activities. A botnet is the main way to carry and spread many malicious codes in internet that are responsible for many malicious activities including spam mail, distributed denial of service attack and click fraud. In this paper, we

      Bilal Sowan, Nasim Matar, Firas Omar, Mohammad Alauthman, Mohammed Eshtay, " Evaluation of Class Decomposition based on Clustering Validity and K-means Algorithm " , "2020 21st International Arab Conference on Information Technology (ACIT)",Vol.21,No., IEEE, 6 of October, Giza, Egypt, 11/28/2020 Abstract:
      A class decomposition is one of the possible solutions and the most important factors of success for the improvement of classification performance. The idea is to transform a dataset by categorizing each class label into groups or clusters. Thus, the transformation is done concerning data characteri

      Israa Odeh; Mouhammd Alkasassbeh; Mohammad Alauthman, " Diabetic Retinopathy Detection using Ensemble Machine Learning " , "2021 International Conference on Information Technology (ICIT)",Vol.2021,No., IEEE, Amman, Jordan, 07/26/2021
  • Event Calendar
    <July 2022>