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Mr Ashley Woodiss-Field

Overview of thesis

Developing Resilient Approaches for Detection of compromised IoT Devices through Machine Learning

Qualifications

  • Bachelor of Computer Science (2015)
  • Bachelor of Computer Science with First Class Honours (2016)

Research

Research Interests

  • Machine Learning Techniques for Intrusion Detection

Past Teaching

  • Introduction to Mobile Applications Development

Recent Publications (within the last five years)

Conference Publications/ Presentations

  • Woodiss-Field, A. (2016). A hybrid behaviour recognition and intrusion detection method for mobile devices. In Johnstone, M. (Ed.). (2016). The Proceedings of 14th Australian Information Security Management Conference, 5-6 December, 2016, Edith Cowan University, Perth, Western Australia. (pp.37-47).

Contact

Mr Ashley Woodiss-Field
PhD student
ECU Security Research Institute
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