News - Computational Privacy Group, Imperial College London

News from the Computational Privacy Group at Imperial College London

Evaluating COVID-19 contact tracing apps? Here are 8 privacy questions we think you should ask.

Apr 2, 2020

While governments are ramping up their efforts to slow down the spread of COVID-19, contact tracing apps are being developed to record interactions and warn users if one of their contacts is later diagnosed positive. These apps could help avoid long-term confinement, but also record fine-grained location or close-proximity data. In this blog post, we propose 8 questions one should ask to understand how protective of privacy an app is.











When the signal is in the noise: Exploiting Aircloak's Diffix anonymization mechanism

Apr 24, 2018

We studied Diffix, a system developed and commercialized by Aircloak to anonymise data by adding noise to SQL queries sent by analysts. In a manuscript we just published on arXiv, we show that Diffix is vulnerable to a noise-exploitation attack. In short, our attack uses the noise added by Diffix to infer people’s private information with high accuracy. We share Diffix’s creators opinion that it is time to take a fresh look at building practical anonymization systems.



Solving AI's Privacy Problem

Feb 16, 2018

Artificial Intelligence (AI) has potential to fundamentally change the way we work, live, and interact. There is however, no general AI out there and the accuracy of current machine learning models largely depend on the data on which they have been trained. For the coming decades, the development of AI will depend on access to ever larger and richer medical and behavioral datasets. We now have strong evidence that the tool we have used historically to find a balance between using the data in aggregate and protecting people’s privacy, de-identification, does not scale to big data datasets. The development and deployment of modern privacy-enhancing technologies (PET), allowing data controllers to make data available in a safe and transparent way, will be key to unlocking the great potential of AI.