Please note that advertised projects are sample projects and prospective applicants are not required to apply to one of the advertised projects, but are welcome to discuss broader research interests with the academic named in the advert - and/or to apply with their own research proposal.
This project will examine cybersecurity, privacy, bias and trust in female-oriented technologies (FemTech). FemTech is a term applied to a category of digital technologies (apps, IoT devices, etc.) focusing on women's health e.g. in menstruation, nursing, sexual and reproductive health. FemTech apps have millions of users and the FemTech market has a significant market (estimated to be an over $75-billion industry by 2025). By processing user data e.g. via AI and ML, FemTech assists in managing women’s health, and gives scientists more insight about people’s bodies. However, there is a lack of clarity in the law (e.g. GDPR) and the industry practice in relation to this extremely sensitive data on different levels i.e. user consent, third-party sharing, and algorithmic bias which may lead to malicious purposes.
Previous work demonstrates the poor security and privacy practices of the industry e.g., how the majority of fertility apps start tracking the user right after the app is open and before any user consent, and how new IoT sensors can put users at serious risk by collecting a wide range of intimate and sensitive data about the users and when we look at the risks from the differential vulnerabilities lens. Yet the user perception and protection behaviour are far less than the actual risks. The project’s aim is to evaluate the security and privacy of such systems and co-design (with users and other stakeholders) the new generation of FemTech solutions allowing the users to improve the quality of their lives without fear and risk.
This project takes its novelty by bringing a critical approach into the engineering processes of developing FemTech solutions via studying systems and engaging with the end-users (and other stakeholders) as co-designers. This project will achieve its aims by:
· Evaluating the security and privacy of FemTech by carrying out research on several aspects of the ecosystem e.g., web apps and APIs, mobile apps, sensors, networks, cloud architecture and configuration, source code analysis, hardware and firmware, as well as analysing the tracking practices and privacy notices according to the law e.g. GDPR for special category data and other related regulations.
· Investigating user perception and practice via conducting large-scale user studies (e.g. Prolific) and focused group workshops and interviews for co-designing future solutions, as well as studying socio-technical bias and trust in data, algorithms and AI systems via studying datasets and algorithms using and improving ‘fairness metrics’.
· Informing the design and implementation of the next generation of the FemTech solutions in a privacy-preserving, secure, safe, and fair way.
We welcome applications from students with an interest in usable security and privacy projects with a background in computing science, engineering or a very closely related discipline. The student will receive training in security and privacy analysis as well as user studies and co-design activities. We have been working with the FemTech industry for years and will provide the student with networking opportunities to deliver an impactful project.
Please contact Dr Maryam Mehrnezhad [Email Address Removed] to discuss further.
Continue with Facebook
