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  • Google Scholar profile
    https://scholar.google.co.th/citations?user=VoJGSlYAAAAJ&hl=en
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    https://www.linkedin.com/in/matthew-gaber-2683a99a/
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Matthew George Gaber

Overview of thesis

Cyber-attacks are constantly evolving and becoming more frequent, where a combination of technological advancements, financial motivation, advanced evasion techniques and targeted attacks contribute to increasingly sophisticated malware. Consequently, the field of Artificial Intelligence (AI) for malware detection is a highly active area of research, but the practical implementation of AI models in production environments is advancing at a slower pace. The accuracy and effectiveness of AI for malware detection is dependent on the quality and quantity of the features it is trained with. That is, an analysis tool that forces malware to expose it malicious intent and then extracts genuine features is necessary to train accurate AI models. My research investigates a malware detection system that focuses on five critical aspects: malware and software repositories; malware sophistication; analysis tools and techniques; feature engineering; and the deep learning model. Through investigation of the individual components and how they function as a system, this research aims to make a significant impact on the field of cybersecurity, by adding new knowledge and insights, through the development of more efficient tools and techniques for countering malware threats.

Qualifications

  • Master Cyber Security in Advanced Tradecraft 2021

Research

  • Peekaboo Dataset: https://ro.ecu.edu.au/datasets/138/
  • Matthew Gaber, Mohiuddin Ahmed, Helge Janicke. Defeating Evasive Malware with Peekaboo: Extracting Authentic Malware Behavior with Dynamic Binary Instrumentation, 21 April 2024, PREPRINT (Version 1) available at Research Square https://doi.org/10.21203/rs.3.rs-4279929/v1
  • Matthew Gaber, Mohiuddin Ahmed, Helge Janicke. Malware Detection with Artificial Intelligence: A Systematic Literature Review. ACM Comput. Surv. 56, 6, Article 148 (June 2024), 33 pages. https://doi.org/10.1145/3638552

Scholarships and Awards

  • The Australian Government Research Training Program (RTP) Scholarship 2024

Supervisors

Contact

Matthew George Gaber
PhD Student
School of Science
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