URKI EPSRC Open Plus Fellowship on Securing the Next Billion Consumer Devices on the Edge
I am really excited to announce that I have been selected for an EPSRC Open Fellowship (Plus) 2022-2027 with a funding of around £2m from the UKRI, the industry, and Imperial College London. Throughout the next 5-years, I’ll be working on providing better security and privacy for edge devices (IoT & Browser), all the way from the on-device TEE to analytics done at the ISP end. The industrial supporters of the fellowship are : Arm Research, Telefonica I+D, Samsung AI, and CISCO.
As part of the Plus component of the fellowship, I will be closely working with The Information Commissioner’s Office (ICO) addressing the privacy recommendations and regulatory challenges raised by the consumer IoT sector and its data collection practices.
In this fellowship, I aim to address major challenge in the adoption of user-centred privacy-enhancing technologies by designing and evaluating an ecosystem where analytics from, and interaction with, consumer devices can happen with trust in the model and authenticity, while enabling auditing and personalisation, hence pushing today’s boundaries on all-or-nothing privacy and enabling new economic models. This approach requires designing for capabilities beyond the current trusted memory and processing limitations of the devices, and a cooperative dialogue and ecosystem involving service providers, ISPs, regulators, device manufacturers, and the end users. By designing our framework around the latest architectural and security features in edge devices, before they become commercially available, we provision for Model Privacy and a User-Centred ecosystem, where service providers can have trust in the authenticity, attestability, and trustworthiness of the valuable models running on user devices, without the users having to reveal sensitive personal information to these cloud-based centralised systems. This approach will enable advanced and sensitive edge-based analytics to be performed, without jeopardising the individuals’ privacy. Importantly, we aim to integrate mechanisms for data authenticity and attestation into our proposed framework, to enable trust in models and the data used by them. Such privacy-preserving technologies have the capacity to enable new forms of sensitive analytics, without sharing raw data and thereby providing legal balancing capabilities that might enable certain sensitive (or currently unlawful) data analysis.
I am really excited about the next 5 years! As part of the fellowship team, I will be recruiting a postdoctoral researcher, an engineer, and 2 PhD students. Watch out for adverts coming out soon! If you are thinking of applying for PhD with us, please get in touch and apply before February 2022.