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Automatic Privacy Management Based on Dynamic Consent

Within EU GDPR (General Data Protection Regulation), consent constitutes one of the six possible legal grounds for lawfully processing personal data, and it is also the one found most confusing. To comply with GDPR, consent must be freely given, specific, informed and unambiguous. However, it is questionable that the current schemes ensure a real privacy choice to the data subject. Also, while GDPR empowers individuals to have more control over their personal data, it seems to also rely on robust decision-making when individuals may not have the knowledge or experience in data privacy or security.

This project will explore how automation may improve user experience in consent in smart home environments with a multiplicity of Internet of Things devices. The research will explore temporal knowledge representation and reasoning to identify attributes and rules for consent in particular contexts and how they change with time. Extracted knowledge will be used to create a user-friendly representation of consent behaviour, and automatically generate recommendations for user privacy policies.

Applicants will be required to demonstrate their ability to think analytically and innovatively; develop software with a working knowledge of data analysis techniques; research, analyse and critically evaluate information; communicate results and findings in research reports.

Applicants will have or be expected to receive a first or upper-second class honours degree in Engineering, Computer Science, Design, Mathematics, Physics or a similar discipline. A Postgraduate Masters degree may be an advantage.

Experience in privacy and data protection principles; privacy-enhancing technologies; Internet of Things, user-experience design; recommendation systems is an advantage. In addition, the applicant should be highly motivated, able to work in a team, collaborate with others and have good communication skills.



M. Massey, “Widespread confusion over GDPR rules that protect your privacy,” 25 May 2019.

A. Smith, “'I Agree to the Terms and Conditions:' One of the Largest Lies in Tech,” 21 August 2019. [Online].

I. v. Oojen and H. U. Vrabec, “Does the GDPR Enhance Consumer's Control over Personal Data? An Analysis from a Behavioural Perspective,” Journal of Consumer Policy, vol. 42, pp. 91-107, 2019.

How to apply

If you are interested in applying for the above PhD topic please follow the steps below:

  1. Contact the supervisor by email or phone to discuss your interest and find out if you woold be suitable. Supervisor details can be found on this topic page. The supervisor will guide you in developing the topic-specific research proposal, which will form part of your application.
  2. Click on the 'Apply here' button on this page and you will be taken to the relevant PhD course page, where you can apply using an online application.
  3. Complete the online application indicating your selected supervisor and include the research proposal for the topic you have selected.

Good luck!

This is a self funded topic

Brunel offers a number of funding options to research students that help cover the cost of their tuition fees, contribute to living expenses or both. See more information here: https://www.brunel.ac.uk/research/Research-degrees/Research-degree-funding. The UK Government is also offering Doctoral Student Loans for eligible students, and there is some funding available through the Research Councils. Many of our international students benefit from funding provided by their governments or employers. Brunel alumni enjoy tuition fee discounts of 15%.

Meet the Supervisor(s)

Cigdem Sengul - Cigdem has more than ten years of experience in research and development in mobile and wireless networks in both academia and industry. She has been working on standards for building privacy and trust in the Internet of Things during her time at Nominet as a Senior Researcher (2015-2019).  Between 2012-2015, she worked as a Senior Lecturer at Oxford Brookes University, where she lectured and conducted research on wireless and mobile networks, with a particular focus on energy and interference efficiency, and Internet of Robotic Things. From 2008-2012, she was with Telekom Innovation Labs (the main research unit of Deutsche Telekom) as a Senior Research Scientist leading projects on Wireless Mesh Networks. Her work has been published in more than 50 journal and conference publications.  She is a Fulbright, Department of Computer Science, UIUC and Vodafone fellow. Cigdem is a passionate advocate of increasing diversity awareness in computing. She is the Communication and Outreach Chair of ACM Women-Europe. She collaborates with the Micro:bit Educational Foundation to support their mission of teaching coding to school children. She is the co-author of the Networking with the Micro:bit book.