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  • ORCiD profile
    https://orcid.org/0000-0002-5621-4126
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    https://scholar.google.com/citations?user=MtzEaT8AAAAJ&hl=en
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    https://www.linkedin.com/in/mohammad-alfawareh/
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    https://www.researchgate.net/profile/Mohammad-Al-Fawareh
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Mohammad Al-Fawa’reh

Overview of thesis

My PhD research project aims to enhance machine learning generalizability and robustness against adversarial attacks in Computer Networks and XIoT (e.g., medical, industrial) environments. This involves developing advanced Network Intrusion Detection Systems (NIDS) and exploring offensive strategies to understand how attackers bypass AI systems, ultimately aiming to develop robust countermeasures for resilience against sophisticated adversarial threats.

The methods employed include integrating state-of-the-art machine learning techniques such as Variational Autoencoders (VAE), Normalizing Flow (NF) models, Reinforcement Learning, Stochastic Shattering Gradient Descent, and Large Language Models (LLMs) in novel ways to improve NIDS robustness and generalizability.

Expected outcomes of my research include the creation of more resilient NIDS capable of maintaining high detection rates and low false positives, even in the presence of sophisticated adversarial threats.

Qualifications

  • M.Sc., Information System Security and Digital Crimes, Princess Sumaya University for Technology, Jordan (2017 - 2020)
  • B.Sc., Computer Engineering, Al-Hussein Bin Talal University, Jordan (2010 - 2014)

Research

Research Interests

  • AI robustness, AI generalizability, LLM (Large Language Models), and Malware detection.

Other work

  • 2016 - 2021: Network Engineer, AABU (Jordan)
  • 2015 - 2016: Network Engineer (Unified Communications Specialist), ARTELCO (Jordan)

Past Teaching

  • 2021 - 2022, Cybersecurity Lecturer,  Information Technology Department, Yarmouk University, Jordan.

Scholarships and Awards

  • 2010 - 2014, Ministry of Education Scholarship, Jordan.
  • 2017 – 2020, Orange Scholarship, Jordan.
  • 2022 – 2025, HDR Scholarship from Edith Cowan University, Australia.
  • Highest GPA in Master of Information System Security and Digital Crimes.
  • Highest GPA in B.Sc., Computer Engineering.

Supervisors

  • Principal Supervisor: Dr. Jumana ABU-KHALAF (School of Science, Centre for Artificial Intelligence and Machine Learning)
  • Associate Supervisor: Dr. Patryk Szewczyk (School of Science, Security Research Institute)
  • Associate Supervisor: Dr. Naeem Janjua (School of Science, Centre for Artificial Intelligence and Machine Learning)
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