On the Semantics of Differential Privacy and Its Responsible Use

Differential Privacy (DP) is one of the most widely adopted formal model of privacy protection but its semantics, especially in the presence of correlated data and in the adversarial interactive setting, is still not broadly understood among data science practitioners. In this paper, we first look at how DP originated from research on database-reconstruction attacks … More On the Semantics of Differential Privacy and Its Responsible Use

Data Security vs Cyber Security

Cyber security and data security are closely related concepts that operate at different levels and provide different safeguards. Cyber security is primarily about controlling access to systems and data through different security protection mechanisms, from the physical network layer all the way to the application layer. These security mechanisms come primarily in the form of … More Data Security vs Cyber Security

Dealing with Linkage Attacks using Differential Privacy

A key claim of differential privacy in [DR14] is that it provides “automatic neutralization of linkage attacks, including all those attempted with all past, present, and future datasets and other forms and sources of auxiliary information”. This is an important and often repeated claim — see e.g. [N17, Section E] and [PR23] — but the … More Dealing with Linkage Attacks using Differential Privacy

Privacy Technologies for Financial Intelligence

It took a little while to write, but hopefully the following survey paper by Yang Li, Thilina Ranbaduge and yours truly can help demystify financial intelligence and privacy technologies for practitioners and technologists alike. The focus is on anti-money laundering and counter-terrorism financing, but the opportunity set is much broader. https://arxiv.org/abs/2408.09935 Here’s the abstract of … More Privacy Technologies for Financial Intelligence

What Can Differential Privacy Actually Protect?

Differential Privacy (DP) is, by now, the most widely adopted formal model of privacy protection used in industry [L23] and government [ABS22] but my sense is that its “semantics”, especially in the presence of correlated data and in the adversarial interactive setting, is still not broadly understood in the community, especially among practitioners. In the … More What Can Differential Privacy Actually Protect?

How To Deal with Database Reconstruction Attacks

I have been thinking about data security issues, in particular database-reconstruction attacks. To quote Wikipedia, a reconstruction attack is any method for partially reconstructing a private database from public aggregate information. The question I am specifically interested in is this: Can an attacker with general interactive query access to a dataset recover a piece of … More How To Deal with Database Reconstruction Attacks

FinTracer and Friends

About 5 years ago, Tania Churchill and I assembled a team of researchers and engineers across AUSTRAC and ANU to work on privacy technologies for detecting criminal activities across the financial system, funded by the Fintel Alliance Expansion budget measure, the Investigative Analytics NPP (led by CSIRO’s Data61), and an ANU Translational Fellowship. The overall … More FinTracer and Friends

A Tutorial Introduction to Lattice-based Cryptography and Homomorphic Encryption

A few of us have been working with homomorphic encryption for a number of years now, but we never found a paper / book that covers all the foundational mathematical material in one place. So we decided to write one — well my postdoc Kelvin Yang Li decided to write one and Mike Purcell and I assisted … More A Tutorial Introduction to Lattice-based Cryptography and Homomorphic Encryption

Private Graph Data Release using Differential Privacy

A few colleagues and I have just put on arXiv a new survey paper on Private Graph Data Release, which took us nearly 9 months to write. Here’s the abstract: The application of graph analytics to various domains have yielded tremendous societal and economical benefits in recent years. However, the increasingly widespread adoption of graph … More Private Graph Data Release using Differential Privacy