Defending Machine Learning Operations (MLOps) across the Human-Machine Interface

点击翻译按钮获取中文摘要

This project aims to address the socio-technical cybersecurity risks of operationalising machine learning models. It will generate new knowledge in the areas of computer security and human-computer interaction by using a transdisicplinary research approach that brings together social and behavioural science, computer science, and data science. The outputs from the research will be models of the behavioural risks to machine learning operations; a tool for facilitating experiments to manage the risks of human-machine teaming and novel algorithms that can be used to both defend and attack machine learning operations. The benefits arising from the research with be increased trust in the operationalisation of machine learning models.