IoT Intrusion Detection Using Group Outlier Detection Methods and Advanced Artificial Intelligence Approaches

An exciting opportunity to apply for eight fully funded PhD positions in the College of Arts, Technology and Environment, UWE Bristol.

Ref: 2223-APR-CATE13

The expected start date of these studentships is 1 April 2023.

The closing date for applications is 8 January 2023.

Please note: out of the eight projects being advertised for the CATE Studentships 2022. The projects for funding will be selected based on the merit of applicants following the process outlined below.

The proposed project will investigate the use of advanced artificial intelligence (AI) and machine learning (ML) methods for retrieving group traffic outliers in internet of things (IoT).  This will be useful for detecting complex intrusions and DDoS attacks. The candidate will start this project by identifying the limitations of utilising traditional solutions as a mechanism to identify intrusion in IoT environments. They will investigate the advantages of combining data and deep learning in deriving data traffic group outliers then propose original models for IoT traffic by exploring advanced concepts such as graph-based network traffic correlation XAI solutions, e.g., Shapley value method. GPU implementation will also be considered for scalability.  

The project will be based in the Computer Science Research Centre Computer Science Research Centre (CSRC)

The supervisory team includes scholars with complementary expertise; the director of study, and main supervisor, Dr Djamel Djenouri from UWE, and two co-supervisors, Dr Youcef Djenour from Noce, NORCE, and Dr Zeineb Rezaeifar from UWE. The team will provide complementary expertise in IoT security, wireless networks and protocols, network traffic analysis, deep learning, parallel computing and GPU technology, outlier detection and explainable AI. 

The studentship is available from 01 April 2023 for a period of three and half years, subject to satisfactory progress and includes a tax exempt stipend, which is currently £17,668 per annum. 

In addition, full-time tuition fees will be covered for up to three years. 

Applicants must have at least a good honours degree, and preferably a Master’s degree, in Computer Science, Computer or Electrical Engineering, Applied Mathematics or a closely related discipline. Familiarity with security and/or IoT, Machine Learning (e.g. through a final year project) is highly desirable.  

Please submit your application online. When prompted use the reference number 2223-APR-CATE13

Supporting documentation: You will need to upload your research proposal, all your degree certificates and transcripts and your proof of English language proficiency as attachments to your application, so please have these available when you complete the application form.

References: You will need to provide details of two referees as part of your application. At least one referee must be an academic referee from the institution that conferred your highest degree. Your referee will be asked for a reference at the time you submit your application, so please ensure that your nominated referees are willing and able to provide references within 14 days of your application being submitted.

The closing date for applications is 08 January 2023.

It is expected that interviews will take place on weeks commencing 20 February 2023. If you have not heard from us by February, we thank you for your application but on this occasion you have not been successful.