MAISP 2021

Defence Against Dark Artefacts

Speaker: Hamed Haddadi
Imperial College London | Brave Software

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.


The ML data center is dead: What comes next?

Speaker: Nicholas Lane
University of Cambridge | Samsung AI Center


TBD