PhD Scholarship in Data-Driven IoT Security

PhD Scholarship in Data-Driven IoT Security

PhD Scholarship funded by 2022 ARC Discovery Project “Adaptive and Ubiquitous Trust Framework for Internet of Things interactions”.

The successful applicant will conduct research to design and develop novel machine/deep learning based trust technologies for securing IoT services/devices.

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  • $31,106 per annum for three years.
  • Successful international applicants will be provided with tuition fee waiver.

Application is now open

Application will be closed when the right PhD candidates are selected

One (1)

To be eligible for this scholarship you must: Have a Master by Research degree; or a Master by Coursework degree with a significant research component graded as high distinction or equivalent; or an Honours degree achieving first class honours in Computer Science. Applicants with research experience in IoT, security, and/or machine learning are preferred.

To apply, please submit the following documents to Dr Hai Dong (hai.dong@rmit.edu.au).

Expressions of interest should contain the following information:

  • A one-page cover letter briefly outlining your interest in the project
  • Evidence of research ability: A digital copy of a Master’s or Honours’ thesis; and a digital copy of academic transcripts
  • A detailed CV clearly outlining your experience in developing distributed systems/applications; also important to list any publications, awards, and relevant professional experience
  • English language proficiency test result (for international applicants)

The aim of the project is to address the Trust challenges in Internet of Things (IoT) environments, thus enabling the wide deployment of potentially billions of IoT devices. This project will generate new knowledge in the area of IoT Trust by developing novel techniques to establish trust in highly dynamic crowdsourcing IoT environments. The project's main outcomes include the development of a ubiquitous and adaptive multi-component trust framework reflecting trust perspectives. The developed solutions will allow the establishment of trusted interactions among crowdsourced IoT devices and wider deployment of convenient and just-in-time services, thus enabling the development of novel applications, such as the crowdsourcing of green energy.

For further inquiries please contact Dr Hai Dong (hai.dong@rmit.edu.au)

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Acknowledgement of Country

RMIT University acknowledges the people of the Woi wurrung and Boon wurrung language groups of the eastern Kulin Nation on whose unceded lands we conduct the business of the University. RMIT University respectfully acknowledges their Ancestors and Elders, past and present. RMIT also acknowledges the Traditional Custodians and their Ancestors of the lands and waters across Australia where we conduct our business - Artwork 'Sentient' by Hollie Johnson, Gunaikurnai and Monero Ngarigo.

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