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  • Alexander Grojek

    Alexander Grojek

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  • ORCiD profile
    https://orcid.org/0000-0003-2877-2785
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    https://www.linkedin.com/in/alexander-grojek/
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Alexander Grojek

Overview of thesis

The continued and rapid development of Internet of Things (IoT) devices in our modern world has brought significant changes to how society is being productive and connected. The widespread uptake and application of IoT devices in the past ten years alone has seen how technology has advanced to aid in our daily lives and is now considered an integral factor to living. However, this advancement has come with a cost, the art of performing digital forensic investigations, particularly with IoT devices, has stagnated. Traditional methods that have been developed and applied in computer forensics over the last twenty years cannot be directly applied to the new domain of IoT forensics, mainly due to its greater complexity and being crossover with network and cloud forensics. This is further complicated by the exponentially growing number of IoT networks and associated computing devices producing ever-growing volume, variety, heterogeneity, and velocity of data.

My research seeks to address some of these challenges by investigating how the implementation of artificial intelligence (AI) can reduce the required amount of human interaction, expertise, and aid in producing results that meet or exceed industry standard scientific techniques and methodologies to extract and analyse data. New forensic methods must be researched and established that can address these issues, while still maintaining the core principle of digital forensics, namely, to maintain the chain of custody throughout the investigative process. I am working on a novel approach to apply AI to the IoT forensics domain, in particular, a semantic-based ontology facilitating machine learning. To achieve this, an AI-powered mechanism will be developed that can infer explicit statements from implicit knowledge captured in digital forensic datasets as a result of forensically sound data acquisition and data aggregated from heterogeneous data sources.

Qualifications

  • Bachelor of Science (Security) Honours (Science), Edith Cowan University (2020–2021)
  • Bachelor of Computer Science (Science) Major in Cyber Security (2016–2019)

Research

  • 2024  Augmenting Cyber Defence Capability (ACDC) project, Honeypot Deception project.
  • 2023 The Value of Incident Response Drills on a Cyber Range in Cyber-Defence Education Semantics-Powered Formalisms for Digital Forensics.
  • 2022 Ontology-Driven Artificial Intelligence in IoT Forensics. CamDec: Advancing Axis P1435-LE Video Camera Security using Honeypot-based Deception.
  • 2020–2021 Honeypot Research Group project.
  • 2020 Point of Sale Terminals: Convenience or Compromise? (Honours thesis).
  • 2018 Broadband Router Threats Database project.

Research Interests

  • Cyber Security Vulnerabilities and Countermeasures
  • Honeypot-based Deception
  • Digital, Network, IoT, and Cloud Forensics
  • Artificial Intelligence Automation
  • IoT Device Exploitation
  • Hardware-Level Device Spoofing
  • Critical Infrastructure Security
  • Cyber-Range Simulations and Evaluations

Past Research employment history

  • 2023/24 Research Assistant, ECU Centre for Securing Digital Futures
  • 2020/21 Research Assistant, ECU Security Research Institute

Other work

  • 2021-2024 Tutor & Unit Coordinator, ECU School of Science - Computing and Security
  • 2021 Unit Content Developer, ECU School of Science - Computing and Security

Supervisors

Contact

Alexander Grojek
PhD students
Security Research Institute
School of Science
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