Study level

  • PhD
  • Honours

Faculty/School

Faculty of Science

School of Computer Science

Topic status

We're looking for students to study this topic.

Research centre

Centre for Data Science

Supervisors

Professor Yuefeng Li
Position
Professor
Division / Faculty
Faculty of Science

Overview

This project aims to investigate privacy preservation protocols in a 5G integrated IoT environment through an analysis of the depth of smart-device use in common smart domains. 5G’s addition to IoT-based smart devices will be effectively deployed and utilised by a large majority of individual and organisation-based users. The knowledge-based ontology and tools developed in the project will help form the new privacy preservation mechanisms that are required for the 5G enabled environment.

The development of an ontology for 5G enabled smart-devices is an important task for this project. Specifically, the task consists of three-steps: A) ontology construction; B) ontology refinement; D) ontology application. The first step, ontology construction uses data mining techniques to analyse the data collected and to discover underlying patterns as 5G and IoT domain knowledge. Reflecting the types of smart devices and subjects of information/communication needs, the discovered knowledge will be categorised to construct the ontology using categorisation techniques. Ontology refinement will be conducted semi-automatically, with outlier detection techniques to be used to find abnormalities in the ontology and domain experts to prune the ontology for refinement. Finally, axioms and inference rules will be developed for the knowledge in the ontology to be used to assist in designing privacy preservation protocols for smart devices under 5G enabled IoT systems in a specific given domain.

Research activities

The project will discuss or contribute leading techniques for building knowledge-based systems to help form the new privacy preservation mechanisms that are required for the 5G enabled environment.

The research group, AI-based Data Analysis will foster the development of students through the transition of knowledge from supervisors with the world-class level.

For VRES or honours students, you will obtain research experience in the ares of:

  • data mining
  • AI-based data analysis.

For HDR students, you will learn how to develop world-leading research capabilities or skills for your career.

Outcomes

For VRES or honours students: the aim of the project is to develop survey reports or a conceptual model to understand the current research trends or issues of AI-based algorithms for privacy preservation protocols in 5G and/or IoT environments.

For HDR students: the aim of the project is to develop new ontology construction models and/or application packages to solve the research gaps in the related fields.

Skills and experience

You must have:

  • a solid background in computer science
  • the python or java experience
  • GPA > = 5.5.

Scholarships

You may be eligible to apply for a research scholarship.

Explore our research scholarships

Keywords

Contact

Contact the supervisor for more information.