An integrated Intrusion Detection System for Aircrafts/Ships using Reinforcement learning and dynamical systems theory

Applications are invited for a three-year MPhil/PhD studentship. The studentship will start on 1st October 2021.

To apply please use the online application form. Simply search for PhD Computing, then clearly state that you are applying for a PhD studentship within the School of Engineering Computing and Mathematics and name the project at the top of your personal statement.

Online application

Take a look at the Doctoral College's general information on applying for a research degree.

Project description

With the advent of first generation of e-enabled aircrafts/ships, these cyber-physical systems have more sub-systems that are interlinked through various cyber protocols. While this has enhanced their capabilities and have made these systems more in-synch with the technological evolution in various fields, it, however, has increased the potential threats to these systems from malicious actors. Using cheap commercial-of-the-shelf equipment/software, attacks, such as GPS spoofing/jamming, can be initiated to divert aircrafts/ships and cause catastrophes. 

Intrusion detection/prevention has been a popular counter-measure to thwart various attacks on internet-connected systems. However, it’s use in the cyber-physical systems is challenging due to the complex interaction of the cyber and physical domains. In this project, we aim to enhance this research area of intrusion detection/prevention integrating techniques from cyber and physical systems in to one integrated intrusion detection system. To this end, we will develop algorithms in-line with the idea of defense-in-depth strategy, used in the conventional internet-connected systems, and design multiple intrusion detection systems that are connected in series/parallel topologies, and are based on data from cyber-domain and the actual dynamics of the aircraft/ship; the later being called ‘physics’ based intrusion detection. The intrusion information from various sources will be fed in to a reinforcement learning algorithm that will determine the likelihood of an intrusion. The efficacy of our idea will be tested using flight/ship simulators in a lab environment and with the help of test pilots.

Eligibility 

Applicants should have (at least) a first or upper second class honours degree in an appropriate subject and preferably a relevant MSc or MRes qualification. 

The studentship is supported for three years and includes full home tuition fees plus a stipend of £15,609 per annum (2021/22 rate). The studentship will only fully fund those applicants who are eligible for home fees with relevant qualifications. Applicants normally required to cover international fees will have to cover the difference between the home and the international tuition fee rates (approximately £12,697 per annum).

If you wish to discuss this project further informally, please contact hafizul.asad@plymouth.ac.uk. However, applications must be made in accordance with the details shown below.

General information about applying for a research degree at the University of Plymouth and to apply for this position please visit: https://www.plymouth.ac.uk/student-life/your-studies/research-degrees

Please mark it FAO Doctoral College and clearly state that you are applying for a PhD studentship within the School of Engineering, Computing and Mathematics.

For more information on the admissions process email the Doctoral College, doctoralcollege@plymouth.ac.uk.

The closing date for applications is 19 April 2021. Shortlisted candidates will be invited for interview the week beginning 3 May 2021. We regret that we may not be able to respond to all applications. Applicants who have not received an offer of a place by 31 May should consider their application has been unsuccessful on this occasion.