We are Andrea Gadotti, Shubham Jain, and Luc Rocher, researchers in the Computational Privacy Group at Imperial College London. We spend our time finding vulnerabilities in privacy-preserving technologies by attacking them, and in recent months we have been looking at global efforts to develop contact tracing apps in the wake of the COVID-19 pandemic.

Ask us anything! We'll be answering live 4-6 PM UK time (11 AM - 1 PM Eastern US) today and sporadically over the next few days.

Mobile contact tracing apps and location tracking systems could help open up the world again in the wake of the coronavirus, and mitigate future pandemics. The data generated, shared, and collected by such technologies could revolutionise policy-making and aid research in the global fight against infectious diseases.

However, the omnipresent tracking of people's movements and interactions can reveal a lot about our lives. Using a contact tracing app means broadcasting unique identifiers, often several times a minute, wherever you go. Part of the data is sent to a central authority e.g. a Ministry of Health, who manages the notification of people exposed to the virus. This raises concerns of function creep, where a technology built for good intentions is later used for more questionable goals. At the same time, large-scale collection and sharing of location data could limit freedom of speech as whistleblowers, journalists, or activists are traced, whilst contributing to an “architecture of oppression” identified by Edward Snowden.

In the search for a solution governments, companies and researchers are investigating privacy-preserving technologies that would enable the use of data and contact tracing systems without invading users’ privacy. Some proposals emphasize technical concepts such as anonymisation, encryption, blockchain, differential privacy, etc. Whilst there are a lot of trendy tech-buzzwords in this list, some of these solutions have real potential, and prove that limiting the spread of this or any future virus can be achieved without resorting to mass surveillance.

So what are the promising technologies? How do contact tracing protocols work under the hood? Are centralized protocols really that privacy-invasive? Are there any risks for privacy in decentralized models, such as the one proposed by Apple and Google? Can data be meaningfully anonymised? Is it really possible to collect and share location data without getting into mass surveillance?

During this AMA we’re happy to answer all your questions on the technical aspects of contact tracing systems, anonymisation and privacy-preserving technologies for data sharing, the potential risks or vulnerabilities posed by them as well as the career of computational privacy researchers and how we got into our current role.

• Andrea works on attacks against systems that are supposed to be privacy-preserving, including inference attacks against commercial software. He co-authored a piece proposing 8 questions to help assess the guarantees of privacy in contact tracing apps.
• Shubham is one of the lead developers for OPAL – a large-scale platform for privacy-preserving location data analytics – and co-creator of Project UNVEIL, a platform for increasing public awareness around Wi-Fi vulnerabilities.
• Luc (/u/cynddl) studies the limits of our anonymity online. His latest work in Nature Communications shows that 99.98% of Americans would be correctly re-identified in any dataset using 15 demographic attributes in any anonymous dataset, a result you can reproduce by playing online with your data.