Machine/Deep Learning based Analysis of Security/Privacy mechanism of IoT Networks

Australia’s cybersecurity infrastructure, particularly in IoT networks, must be strengthened to meet evolving standards set by international bodies like NIST and the NSA. This project will support Australian organizations in adapting to quantum-safe standards, ensuring the protection of sensitive data and critical system

With the rise of quantum computing, traditional cybersecurity mechanisms like RSA and ECC, commonly used to protect data, may soon become vulnerable. This project focuses on preparing IoT networks (such as critical infrastructure monitoring, fleet management, healthcare, and EV charging) for this shift by transitioning to post-quantum cryptographic (PQC) methods, which are resistant to quantum attacks. Key goals include developing IoT Networks in the above mentioned contexts, find out about all quantum-vulnerable security/mechanisms that might have been used in such networks, and perform a risk assessment for each application.

What will students learn in this project

Students are expected to learn about:

• How to setup/configure a working IoT network (both software and hardware) in different contexts and applications
• How to find/retrieve different security/privacy mechanisms/protocols used in a given IoT network.
• Perform risk assessment on all security/privacy mechanisms on different layers of IoT Networks, including hardware, software, and network traffics.

Skills Required

• Basic understanding of network protocols.
• Ability to work with constraint devices, routers, switches, and setup an IoT network.

Application Instructions

Please attach a copy of your CV and current transcripts.