Deep machine learning for zero-day adversarial intrusion detection in Internet-of-Things and Cyber-Physical Systems

About the Project

The increasing demand of secure and reliable communication has never been higher due to elevated number of applications in the present-day world such as the Internet of Things (IoT). The integration of numerous IoT-based applications in various aspects of our lives, e.g., industrial automation, smart healthcare, smart cities, and intelligent transportation has resulted in a continuously growing amount of heterogenous data generated and shared among IoT devices.

This situation has constituted grounds for intruders to attack on the ubiquitous IoT devices and security against these attacks is considered one of the biggest barriers in adopting IoT. The aim of this project is to design machine learning-based intrusion detection system (IDS) that can discriminate between normal samples and the samples under zero-day adversarial network attacks.

Perspective applicants are encouraged to contact the Supervisor before submitting their applications. Applications should make it clear the project you are applying for and the name of the supervisors.

Academic qualifications

First degree (minimum 2:1 classification) in Computer Science, Engineering, Mathematics, Artificial Intelligence, Data Science

English language requirement

IELTS score must be at least 6.5 (with not less than 6.0 in each of the four components). Other, equivalent qualifications will be accepted. Full details of the University’s policy are available online.

Essential attributes:

• Fundamental knowledge in programming in C/C++/R/Java/Python/Matlab etc. Also Basic Computer Science, Networking and communication concepts
• Good Oral and Written communication skills
• Strong motivation, with evidence of independent research skills relevant to the project
• Good Time and Project Management Skills

Desirable attributes:

• Interest in cybersecurity and artificial intelligence or machine learning

APPLICATION CHECKLIST

• Completed application form
• CV
• 2 academic references, using the Postgraduate Educational Reference Form (download)
• Research project outline of 2 pages (list of references excluded). The outline may provide details about
  1. Background and motivation of the project. The motivation, explaining the importance of the project, should be supported also by relevant literature. You can also discuss the applications you expect for the project results.
  2. Research questions or objectives.
  3. Methodology: types of data to be used, approach to data collection, and data analysis methods.
  4. List of references.
• Statement no longer than 1 page describing your motivations and fit with the project.
• Evidence of proficiency in English (if appropriate)

The outline must be created solely by the applicant. Supervisors can only offer general discussions about the project idea without providing any additional support.

To be considered, the application must use the advertised title as project title

For informal enquiries about this PhD project, please contact S.Jan@napier.ac.uk

PhD Start Date: October 2026

Funding Notes

International applicants should note that visa application costs and the NHS health surcharge are additional costs to be taken into consideration, and successful applicants will need to cover these expenses themselves.