PhD project in Anti-counterfeiting Techniques Design and Analysis for IoTs

According to Cisco, 500 billion devices are expected to be connected to the Internet by 2030. The Covid-19 pandemic, resulting in remote working and home-schooling, is leading to a multiplier effect on rising computing technologies. As devices are connected to the Internet, this opens up a range of new attack vectors for malicious adversaries and hackers. There has been a significant increase in attacks and threats directed at networks in 2020, including the infamous the internet of things (IoT) botnet attacks, which can harvest confidential data and execute cyber-attacks by taking control of the victim’s devices and systems remotely. Additionally, counterfeit devices are an increasing problem as more and more devices are connected online. To address this, this project explores the potential of emerging digital technologies, such as hardware security, machine learning and IoT, to transform the way we design, manufacture, and operate products and services. The project offers a bespoke research and training programme that aims to develop students into cross-disciplinary thinkers and leaders who will influence the roadmaps of future advanced technologies and their applications. They will have a balanced understanding of ICT (security and data analytics) in the context of their application to advanced technologies and high value designs.

The internet of things (IoT), enabling smart cities and machines widely and intelligently connected, has led to the development of smart factories. The move to IoT devices and machine-to-machine communication poses serious security and privacy issues as there is not direct control over the connected devices. Current cryptographic methods used to secure computers connected to the Internet won’t easily scale to the volume of the IoT, due to both key management issues, as well as the fact that low cost IoT devices often don’t have the computational power required for complex cryptographic computations.

Silicon physical unclonable functions (PUFs), which exploit manufacturing variations of silicon chips, offer a promising mechanism that can be used in many security, protection and digital rights management applications. Such a primitive has a number of desirable properties from a security perspective, such as the ability to provide a low-cost unique identifier for an integrated circuit (IC) or to provide a variability aware circuit that returns a device specific response to an input challenge. This gives it an advantage over current state-of-art alternatives such as secure non-volatile memory (NVM) or trusted platform modules (TPMs). No special manufacturing processes are required to integrate a PUF into a design. This lowers the overall cost of the security for the IC enabling the PUF to be utilised as a hardware root of trust for all security or identity related operations on the device.

However, PUF based authentication/identification schemes are vulnerable to a number of security attacks including machine learning based modelling attacks and physical cloning attacks. The aim of this project is to develop a secure PUF design, which can deliver a corner stone for building unforgeable devices. The explainable AI techniques will be also investigated to assist the development of PUF designs. A low-cost secure PUF-based authentication/identification scheme will lead to a step change in meeting the stringent security requirements of a number of key areas of the digital economy such as Industry 4.0, IoT, and the hardware supply chain.

Funding Information

To be eligible for consideration for a Home DfE or EPSRC Studentship (covering tuition fees and maintenance stipend of approx. £19,237 per annum), a candidate must satisfy all the eligibility criteria based on nationality, residency and academic qualifications.

To be classed as a Home student, candidates must meet the following criteria and the associated residency requirements:

• Be a UK National,
or • Have settled status,
or • Have pre-settled status,
or • Have indefinite leave to remain or enter the UK.

Candidates from ROI may also qualify for Home student funding.

Previous PhD study MAY make you ineligible to be considered for funding.

Please note that other terms and conditions also apply.

Please note that any available PhD studentships will be allocated on a competitive basis across a number of projects currently being advertised by the School.

A small number of international awards will be available for allocation across the School. An international award is not guaranteed to be available for this project, and competition across the School for these awards will be highly competitive.

Academic Requirements:

The minimum academic requirement for admission is normally an Upper Second Class Honours degree from a UK or ROI Higher Education provider in a relevant discipline, or an equivalent qualification acceptable to the University.

Entrance requirements

Graduate
The minimum academic requirement for admission to a research degree programme is normally an Upper Second Class Honours degree from a UK or ROI HE provider, or an equivalent qualification acceptable to the University. Further information can be obtained by contacting the School.

International Students

For information on international qualification equivalents, please check the specific information for your country.

English Language Requirements

Evidence of an IELTS* score of 6.0, with not less than 5.5 in any component, or equivalent qualification acceptable to the University is required (*taken within the last 2 years).

International students wishing to apply to Queen’s University Belfast (and for whom English is not their first language), must be able to demonstrate their proficiency in English in order to benefit fully from their course of study or research. Non-EEA nationals must also satisfy UK Visas and Immigration (UKVI) immigration requirements for English language for visa purposes.

For more information on English Language requirements for EEA and non-EEA nationals see: www.qub.ac.uk/EnglishLanguageReqs.