Supervisor

Gihan Gunasekara
Gunasekara, Gihan (Dr)
gihan.gunasekara@flinders.edu.au
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Project description

IoT networks for health and well-being are becoming increasingly popular. However, typical IoT devices are not secure because of their limited memory and computing power. In the context of digital health systems, this lack of security can be catastrophic. To overcome this problem, Intrusion Detection Systems (IDS) can be used to detect anomalies, malicious intrusions, or new attacks in an IoT network and make alerts. This project examines the application of AI-driven open-source software-based intrusion detection systems for healthcare IoT networks. The aim of this project is to design, develop, and implement an AI-driven open-source intrusion detection system to enhance the security and reliability of IoT networks in digital health.

Assumed knowledge

While this project does not require formal research skills, some research will be required.
  • Set up an IoT Network infrastructure in the Digital Health Design Laboratory (DHDL) to capture data from healthcare-related sensors.
  • Discover current AI/ IDS methods and techniques suitable for IoT networks.
  • Design and demonstrate an AI-driven IDS in the DHDL IoT Network.
  • Produce a technical report on findings and results.
It requires access to relevant resources available in the Digital Health Design Lab (Tonsley Campus, Room 5.40). The infrastructure will involve elements such as microcontrollers, IoT devices, database management systems, IoT platforms, IoT messaging, connecting a variety of sensors, and potentially some programming using languages.

Supervisors research focus

The project aims to improve the security of healthcare-related IoT networks. This project is part of the Digital Health Design Laboratory.

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