Category: Confidential computing

A Tutorial Introduction to Lattice-based Cryptography and Homomorphic Encryption

September 3, 2022

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

July 13, 2021

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

Towards Fair and Privacy-Preserving Federated Deep Learning Models

May 24, 2020

My former postdoc Lingjuan Lyu has been working with a few research collaborators on a fair and privacy-preserving federated deep-learning framework and a paper describing the framework has just been published at the IEEE Transactions on Parallel and Distributed Systems. Here’s the paper details: Title: Towards Fair and Privacy-Preserving Federated Deep Models Abstract: The current … More Towards Fair and Privacy-Preserving Federated Deep Learning Models

Distributed Privacy-Preserving Prediction

November 3, 2019

Another day, another paper, this time by my postdoc Lingjuan Lyu and a few collaborators. Here’s the abstract: In privacy-preserving machine learning, individual parties are reluctant to share their sensitive training data due to privacy concerns. Even the trained model parameters or prediction can pose serious privacy leakage. To address these problems, we demonstrate a … More Distributed Privacy-Preserving Prediction

Accurate and Efficient Privacy-Preserving String Matching

October 20, 2019

A few ANU colleagues and I have just completed a paper on a suffix-tree-based algorithm for computing the longest common substring of two strings in a privacy-preserving manner. Here’s the abstract: The task of calculating similarities between strings held by different organizations without revealing these strings is an increasingly important problem in areas such as … More Accurate and Efficient Privacy-Preserving String Matching

Linking Integer Records: The Simplest Case of PPRL

May 26, 2019

Privacy-Preserving Record Linkage (PPRL) is one of those problems that still doesn’t have a solid and widely accepted mathematical definition, perhaps because the problem of Record Linkage itself, especially the kind that doesn’t reduce to supervised learning through an abundance of labelled matches, still doesn’t have a solid mathematical definition despite thousands of papers published … More Linking Integer Records: The Simplest Case of PPRL

Useful Technical Tutorials on Fully Homomorphic Encryption

January 18, 2019

I have gone through quite a few articles over the last 12 months in my attempt to get a proper understanding of fully homomorphic encryption (FHE) schemes. The process was somewhat frustrating because most of the articles are either too basic, giving just very high-level intuitions, or too deep, assuming too much background on the … More Useful Technical Tutorials on Fully Homomorphic Encryption