Home \ Faculty Details \ Dr Rami Mustafa A Mohammad
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  • Phone:

  • Email:

    rmohammad@pmu.edu.sa

  • Office No:

    F024

  • Dr Rami Mustafa A Mohammad

  • Job Title :

    Associate Professor

  • College :

    College of Computer Engineering and Science


  • Department :

    Computer Engineering


Dr. Rami Mustafa is an Associate Professor of Information Security. He earned his Ph.D. in Computer Science with a specialization in Information Security from the University of Huddersfield, United Kingdom.

With over 20 years of teaching experience across Saudi Arabia, the United Kingdom, and Jordan, Dr. Rami has delivered a wide range of undergraduate and postgraduate courses, including Ethical Hacking, Digital Forensics, Network Forensics, Data Mining, Cloud Computing, and Operating Systems, among many others. His teaching philosophy is grounded in empowering students through engaging, application-driven instruction, continuous skill development, and a steadfast commitment to lifelong learning.

Dr. Rami has published over 50 articles in prestigious international journals and conferences, accumulating more than 3,700 citations and an h-index of 28. He has been ranked among the World's Top 2% Scientists by Stanford University for four consecutive years (2022–2025). His research interests encompass Information Security, Digital Forensics, Intrusion Detection, OT Security, Data Mining, and Phishing Detection.

Dr. Rami is committed to advancing cybersecurity research and education at PMU in alignment with Saudi Arabia’s Vision 2030, contributing to the Kingdom's digital resilience through impactful research, innovative curricula, and the mentorship of next-generation professionals.

 

I earned my Doctor of Philosophy (Ph.D.) in Computer Science with a specialization in Information Security from the University of Huddersfield, United Kingdom, in 2016.

My doctoral research focused on developing advanced computational solutions for complex cybersecurity challenges. Specifically, my thesis, titled "An Ensemble Self-Structuring Neural Network Approach to Solving Classification Problems with Concept Drift and its Application to Phishing Websites," pioneered novel machine learning techniques. I designed and implemented an ensemble-based, self-structuring neural network architecture specifically engineered to handle the critical problem of concept drift – where the statistical properties of target data change over time – within classification tasks.

This foundational research was directly applied to the pressing issue of phishing website detection, demonstrating the practical efficacy of the proposed model in combating evolving online threats. My Ph.D. work established the core expertise in machine learning, neural networks, and information security that continues to underpin my research program.

 

  • Mohammad, R. M. (2026). Android malware detection using a novel binary Firefly Bat feature selection algorithm. Information Security Journal: A Global Perspective, 1–27. https://doi.org/10.1080/19393555.2026.2615244
  • Norah Ahmed Almubairik, Fakhri Alam Khan, Rami Mustafa Mohammad, Mubarak Alshahrani, WristSense framework: Exploring the forensic potential of wrist-wear devices through case studies, Forensic Science International: Digital Investigation, Volume 52, 2025, 301862, ISSN 2666-2817, https://doi.org/10.1016/j.fsidi.2025.301862.
  • R. A. Alzahrani, M. Aljabri and R. A. Mustafa Mohammad, "Ad Click Fraud Detection Using Machine Learning and Deep Learning Algorithms," in IEEE Access, vol. 13, pp. 12746-12763, 2025, doi: 10.1109/ACCESS.2025.3532200.
  • Aljabri, Malak, Hanan S. Altamimi, Shahd A. Albelali, Maimunah Al-Harbi, Haya T. Alhuraib, Najd K. Alotaibi, Amal A. Alahmadi, Fahd Alhaidari, and Rami Mustafa A. Mohammad. "Kashif: A Chrome Extension for Classifying Arabic Content on Web Pages Using Machine Learning." Applied Sciences 14, no. 20 (2024): 9222.
  • Alsmadi, M. K., Mohammad, R. M. A., Alzaqebah, M., Jawarneh, S., AlShaikh, M., Al Smadi, A., Alghamdi, F. A., Alqurni, J. S., & Alfagham, H. (2024). Intrusion detection using an improved cuckoo search optimization algorithm. Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications, 15(2), 73–93. https://doi.org/10.58346/JOWUA.2024.I2.006
  • Rahman, A., Almomen, M., Albahrani, A., Alhamoud, A., Al Jafar, A., Alyaseen, H., Bakri, A., Ibrahim, N., Aloup, K., Iqbal, T., Mohammad, R.M., Alkhulaifi, D. (2024). Blockchain empowered interoperable framework for smart healthcare. Mathematical Modelling of Engineering Problems, Vol. 11, No. 5, pp. 1330-1340. https://doi.org/10.18280/mmep.110524
  • Almubairik, N.A., Khan, F.A., Mohammad, R.M. (2024). WristSense: A Wrist-Wear Dataset for Identifying Aggressive Tendencies. In:Artificial Intelligence Applications and Innovations. AIAI 2024. IFIP Advances in Information and Communication Technology, vol 711. Springer, Cham. https://doi.org/10.1007/978-3-031-63211-2_21
  • Alshaikh, M., Alzaqebah, M., Gmati, N., Alrefai, N., Alsmadi, M. K., Almarashdeh, I., Mohammad, R. M., Alamri, S., & Kara, M. (2024). Image encryption algorithm based on factorial decomposition. Multimedia Tools and Applications. https://doi.org/10.1007/s11042-023-17663-1
  • Aljabri, M., & Mohammad, R. M. A. (2023). Click fraud detection for online advertising using machine learning. Egyptian Informatics Journal, 24(2), 341-350.
  • Talha, M.; Sarfraz, M.; Rahman, A.; Ghauri, S.A.; Mohammad, R.M.; Krishnasamy, G.; Alkharraa, M. Voting-Based Deep Convolutional Neural Networks (VB-DCNNs) for M-QAM and M-PSK Signals Classification. Electronics 2023, 12, 1913.
  • Musleh, Dhiaa, Meera Alotaibi, Fahd Alhaidari, Atta Rahman, and Rami M. Mohammad. "Intrusion Detection System Using Feature Extraction with Machine Learning Algorithms in IoT." Journal of Sensor and Actuator Networks 12, no. 2 (2023): 29.
  • Aljabri, Malak, Amal Alahmadi, Rami M A. Mohammad, Fahd Alhaidari, Menna Aboulnour, Dorieh Alomari, and Samiha Mirza. "Machine Learning-Based Detection for Unauthorized Access to IoT Devices." Journal of Sensor and Actuator Networks 12, no. 2 (2023): 27.
  • Alzaqebah, Malek, Mutasem K. Alsmadi, Sana Jawarneh, Jehad Saad Alqurni, Mohammed Tayfour, Ibrahim Almarashdeh, Rami Mustafa A. Mohammad et al. "Improved Whale Optimization with Local-Search Method for Feature Selection."
  • Alshabeeb, Esra’A., Malak Aljabri, Rami Mustafa A. Mohammad, Fatemah S. Alqarqoosh, Aseel A. Alqahtani, Zainab T. Alibrahim, Najd Y. Alawad, and Mashael A. Alzeer. "Intelligent Techniques for Predicting Stock Market Prices: A Critical Survey." Journal of Information & Knowledge Management (2023): 2250099.
  • Gollapalli, M., Alamoudi, A., Aldossary, A., Alqarni, A., Alwarthan, S., AlMunsour, Y.Z., Abdulqader, M.M., Mohammad, R.M., Chabani, S. (2022).  Modeling algorithms for task scheduling in cloud computing using CloudSim. Mathematical Modelling of Engineering Problems, Vol. 9, No. 5, pp. 1201-1209. https://doi.org/10.18280/mmep.090506
  • Aljabri, Malak, Hanan S. Altamimi, Shahd A. Albelali, AL-Harbi Maimunah, Haya T. Alhuraib, Najd K. Alotaibi, Amal A. Alahmadi, Fahd Alhaidari, Rami Mustafa A. Mohammad, and Khaled Salah. "Detecting Malicious URLs Using Machine Learning Techniques: Review and Research Directions." IEEE Access (2022).
  • Aljabri, Malak, Fahd Alhaidari, Rami Mustafa A. Mohammad, Samiha Mirza, Dina H. Alhamed, Hanan S. Altamimi, and Sara Mhd Chrouf. "An Assessment of Lexical, Network, and Content-Based Features for Detecting Malicious URLs Using Machine Learning and Deep Learning Models." Computational Intelligence and Neuroscience 2022 (2022).
  • Alzaqebah, Malek, Sana Jawarneh, Maram Alwohaibi, Mutasem K. Alsmadi, Ibrahim Almarashdeh, and Rami Mustafa A. Mohammad. "Hybrid brain storm optimization algorithm and late acceptance hill climbing to solve the flexible job-shop scheduling problem." Journal of King Saud University-Computer and Information Sciences (2020).
  • Aljabri, Malak, Amal A. Alahmadi, Rami Mustafa A. Mohammad, Menna Aboulnour, Dorieh M. Alomari, and Sultan H. Almotiri. "Classification of Firewall Log Data Using Multiclass Machine Learning Models." Electronics 11, no. 12 (2022): 1851.
  • Mohammad, Mustafa A., Malak Aljabri, Menna Aboulnour, Samiha Mirza, and Ahmad Alshobaiki. "Classifying the Mortality of People with Underlying Health Conditions Affected by COVID-19 Using Machine Learning Techniques." Applied Computational Intelligence and Soft Computing 2022 (2022).
  • Alhejazi, Manal Mohamed, and Rami Mustafa A. Mohammad. "Enhancing the blockchain voting process in IoT using a novel blockchain Weighted Majority Consensus Algorithm (WMCA)." Information Security Journal: A Global Perspective 31, no. 2 (2022): 125-143.
  • Alsmadi, Mutasem K., Ghaith M. Jaradat, Malek Alzaqebah, Ibrahim ALmarashdeh, Fahad A. Alghamdi, Rami Mustafa A. Mohammad, Nahier Aldhafferi, and Abdullah Alqahtani. "An Enhanced Particle Swarm Optimization for ITC2021 Sports Timetabling." CMC-Computers Materials & Continua 72, no. 1 (2022): 1995-2014.
  • Almarashdeh, Ibrahim, Kamal Eldin Eldaw, Mutasem Alsmadi, Fahad Alghamdi, Ghaith Jaradat, Ahmad Althunibat, Malek Alzaqebah, and Rami Mustafa A. Mohammad. "The adoption of bitcoins technology: The difference between perceived future expectation and intention to use bitcoins: Does social influence matter?." International Journal of Electrical and Computer Engineering 11, no. 6 (2021): 5351.
  • Aljabri, Malak, Sumayh S. Aljameel, Rami Mustafa A. Mohammad, Sultan H. Almotiri, Samiha Mirza, Fatima M. Anis, Menna Aboulnour, Dorieh M. Alomari, Dina H. Alhamed, and Hanan S. Altamimi. "Intelligent techniques for detecting network attacks: review and research directions." Sensors 21, no. 21 (2021): 7070.
  • Mohammad, Rami Mustafa A., and Mutasem K. Alsmadi. "Intrusion detection using Highest Wins feature selection algorithm." Neural Computing and Applications 33, no. 16 (2021): 9805-9816.
  • Alzaqebah, Malek, Sana Jawarneh, Rami Mustafa A. Mohammad, Mutasem K. Alsmadi, Ibrahim Al-Marashdeh, Eman AE Ahmed, Nashat Alrefai, and Fahad A. Alghamdi. "Hybrid feature selection method based on particle swarm optimization and adaptive local search method." International Journal of Electrical and Computer Engineering 11, no. 3 (2021): 2414.
  • Alzaqebah, Malek, Sana Jawarneh, Rami Mustafa A. Mohammad, Mutasem K. Alsmadi, and Ibrahim Almarashdeh. "Improved multi-verse optimizer feature selection technique with application to phishing, spam, and denial of service attacks." International Journal of Communication Networks and Information Security 13, no. 1 (2021): 76-81.
  • Mohammad, Rami Mustafa A., and Mamoun Masoud Abdulqader. "Exploring Cyber Security Measures in Smart Cities." In 2020 21st International Arab Conference on Information Technology (ACIT), pp. 1-7. IEEE, 2020.
  • Alsmadi, Mutasem K., Ibrahim Al-Marashdeh, Malek Alzaqebah, Ghaith Jaradat, Fahad A. Alghamdi, Rami Mustafa A. Mohammad, Muneerah Alshabanah et al. "Digitalization of learning in Saudi Arabia during the COVID-19 outbreak: A survey." Informatics in Medicine Unlocked 25 (2021).
  • Alzaqebah, Malek, Khaoula Briki, Nashat Alrefai, Sami Brini, Sana Jawarneh, Mutasem K. Alsmadi, Rami Mustafa A. Mohammad et al. "Memory based cuckoo search algorithm for feature selection of gene expression dataset." Informatics in Medicine Unlocked 24 (2021): 100572.
  • Mohammad, Rami Mustafa A., Mutasem K. Alsmadi, Ibrahim Almarashdeh, and Malek Alzaqebah. "An improved rule induction based denial of service attacks classification model." Computers & Security 99 (2020).
  • Mohammad, Rami Mustafa A. "A lifelong spam emails classification model." Applied Computing and Informatics (2020).
  • Mohammad, Rami Mustafa A. "An Improved Multi-Class Classification Algorithm based on Association Classification Approach and its Application to Spam Emails." IAENG International Journal of Computer Science 47, no. 2 (2020).
  • Mohammad, Rami Mustafa A. "An enhanced multiclass support vector machine model and its application to classifying file systems affected by a digital crime." Journal of King Saud University-Computer and Information Sciences (2019).
  • Gonsalves, Amanda H., Fadi Thabtah, Rami Mustafa A. Mohammad, and Gurpreet Singh. "Prediction of coronary heart disease using machine learning: an experimental analysis." In Proceedings of the 2019 3rd International Conference on Deep Learning Technologies, pp. 51-56. 2019.
  • Mohammad, Rami Mustafa A., and Mohammed Alqahtani. "A comparison of machine learning techniques for file system forensics analysis." Journal of Information Security and Applications 46 (2019): 53-61.
  • Mohammad, Rami M. "A neural network based digital forensics classification." In 2018 IEEE/ACS 15th International Conference on Computer Systems and Applications (AICCSA), pp. 1-7. IEEE, 2018.
  • Mohammad, Rami M., and Hussein Y. AbuMansour. "An intelligent model for trustworthiness evaluation in semantic web applications." In 2017 8th International Conference on Information and Communication Systems (ICICS), pp. 362-367. IEEE, 2017.
  • Thabtah, Fadi, Rami M. Mohammad, and Lee McCluskey. "A dynamic self-structuring neural network model to combat phishing." In 2016 international joint conference on Neural networks (ijcnn), pp. 4221-4226. IEEE, 2016.
  • Mohammad, Rami M., Fadi Thabtah, and Lee McCluskey. "An improved self-structuring neural network." In Pacific-Asia conference on knowledge discovery and data mining, pp. 35-47. Springer, Cham, 2016.
  • Mohammad, Rami. "Investigating Trust Issue in Semantic Web Applications." In The Second Forum in Information Security-Naif Arab University for Security Sciences, Riyadh-Saudi Arabia, pp. 1-6. 2016.
  • Mohammad, Rami Mustafa A. "An ensemble self-structuring neural network approach to solving classification problems with virtual concept drift and its application to phishing websites." Ph.D. diss., University of Huddersfield, 2016.
  • Mohammad, Rami M., Fadi Thabtah, and Lee McCluskey. "Tutorial and critical analysis of phishing websites methods." Computer Science Review 17 (2015): 1-24.
  • Mohammad, Rami, Fadi Thabtah, and T. L. McCluskey. "Phishing websites dataset." (2015).
  • Mohammad, Rami M., Fadi Thabtah, and Lee McCluskey. "Phishing websites features." School of Computing and Engineering, University of Huddersfield (2015).
  • Mohammad, Rami M., Fadi Thabtah, and Lee McCluskey. "Predicting phishing websites based on self-structuring neural network." Neural Computing and Applications 25, no. 2 (2014): 443-458.
  • Mohammad, Rami M., Fadi Thabtah, and Lee McCluskey. "Intelligent rule‐based phishing websites classification." IET Information Security 8, no. 3 (2014): 153-160.
  • Mohammad, Rami, T. L. McCluskey, and Fadi Thabtah. "Predicting phishing websites using neural network trained with back-propagation." World Congress in Computer Science, Computer Engineering, and Applied Computing, 2013.
  • Mohammad, Rami M., Fadi Thabtah, and Lee McCluskey. "An assessment of features related to phishing websites using an automated technique." In 2012 International conference for Internet technology and secured transactions, pp. 492-497. IEEE, 2012.

 

Dr. Rami Mustafa Abdelrahman Mohammad
Associate Professor
Department of Cybersecurity
College of Computer Engineering and Science
Prince Mohammad Bin Fahd University

 

Currently I am working as an Associate Professor in the Department of Cybersecurity within the College of Computer Engineering and Science at Prince Mohammad Bin Fahd University. Previously, I held the position of Associate Professor (and prior to that, Assistant Professor) in the Department of Networks and Communications, College of Computer Science and Information Technology at Imam Abdulrahman Bin Faisal University (IAU) from 2018 until 2026.

 

Ethical Hacking – EC-Council-V12  and V13

Digital Forensics Techniques and Tools.

Advanced Computer Forensics.

Information Security Management.

Research Methods for Computer Science 

Data Mining and Warehousing

Object Oriented Analysis and Design.

System Analysis and Design.

Webpage Design (HTML, CSS, FrontPage).

Data Structure with C++.

Network Forensics, Intrusion Detection, and Response.

Digital Evidence Analysis.

Fundamentals of Cybersecurity

Introduction to Operating Systems.

Cloud Computing

Network Protocols & E-Commerce.

Selected Topics in Information Systems.

Decision Support Systems.

Advanced Internet Programming (PHP, ASP)

Object Oriented Programming with Java.

 

 

 

My research focuses on advancing cybersecurity and intelligent systems through applied computational techniques. My core interests include:

  1. Information Security & Digital Forensics: Developing novel methods for intrusion detection, malware analysis (including Android and IoT environments), digital evidence extraction (especially from emerging platforms like wearable devices), and forensic tool evaluation.
  2. Machine Learning & Data Mining for Cybersecurity: Designing and optimizing feature selection algorithms and ensemble learning models to combat evolving threats like phishing, click fraud, botnet activity, and concept drift in malicious datasets. Applying these techniques to real-world security challenges such as network attack detection and malicious URL classification.
  3. Secure & Intelligent Systems: Exploring the integration of blockchain technology for enhancing security and trust in critical infrastructures like IoT, smart healthcare, and smart cities. Investigating machine learning applications for anomaly detection in network traffic, user behavior, and system logs.
  4. Optimization Algorithms: Utilizing and enhancing nature-inspired optimization algorithms (e.g., Cuckoo Search, Whale Optimization, Firefly Bat Algorithm) for critical tasks like feature selection, intrusion detection system improvement, and scheduling problems.