Speaker: Hamed Haddadi - Associate Professor, Imperial College London

Abstract: Consumer Internet of Things devices often come with a range of sensors and actuators, require access to a variety of personal data sources and continuous internet connectivity, and are equipped with a variety of embedded pre-trained Machine Learning (ML) models. In this talk, I will present our recent findings on privacy threats from these devices and potential mitigation strategies using selective blocking of device activities and destinations. I will then discuss the ways in which we can leverage novel architectures to provide private, trusted, personalised, and dynamically-configurable models on consumer devices to cater for heterogeneous environments and user requirements.

Bio: Hamed is a Reader in Human-Centred Systems and the Director of Postgraduate Studies at the Dyson School of Design Engineering at The Faculty of Engineering, Imperial College London. He leads the Systems and Algorithms Laboratory and is an Academic Fellow of the Data Science Institute. He is also a Visiting Professor at Brave Software where he works on developing privacy-preserving analytics protocols.

Zoom Link: https://mit.zoom.us/j/98781075598