Publications by Zhicong Huang | EPFL Graph Search

On Secure Cloud Computing for Genomic Data: From Storage to Analysis

Although privacy is generally considered to be the right of an individual or group to control information about themselves, such a right has become challenging to protect in the digital era, this is exemplified by the case of cloud-based genomic computing. ...

EPFL2018

Labeled PSI from Fully Homomorphic Encryption with Malicious Security

Zhicong Huang

Private Set Intersection (PSI) allows two parties, the sender and the receiver, to compute the intersection of their private sets without revealing extra information to each other. We are interested in the unbalanced PSI setting, where (1) the receiver's s ...

ASSOC COMPUTING MACHINERY2018

System and method for providing a collective decentralized authority for sharing sensitive data

Jean-Pierre Hubaux, Bryan Alexander Ford, Jean Louis Raisaro, Zhicong Huang, Patricia Egger

A method of sharing private and/or sensitive data from plurality of data providers to a data user, the data user having a private key and a public key, the method comprising the steps of providing a first data set and encrypting the first data set at a ter ...

2018

Logistic regression over encrypted data from fully homomorphic encryption

Zhicong Huang

Background: One of the tasks in the 2017 iDASH secure genome analysis competition was to enable training of logistic regression models over encrypted genomic data. More precisely, given a list of approximately 1500 patient records, each with 18 binary feat ...

2018

SQC: Secure Quality Control for Meta-Analysis of Genome-Wide Association Studies

Jean-Pierre Hubaux, Jacques Fellay, Zhicong Huang, Huang Lin

Motivation: Due to the limited power of small-scale genome-wide association studies (GWAS), researchers tend to collaborate and establish a larger consortium in order to perform large-scale GWAS. Genome-wide association meta-analysis (GWAMA) is a statistic ...

Oxford University Press2017

UnLynx: A Decentralized System for Privacy-Conscious Data Sharing

Jean-Pierre Hubaux, Bryan Alexander Ford, David Jules Froelicher, Jean Louis Raisaro, Zhicong Huang, Christian Vincent Mouchet, Joao André Gomes de Sá e Sousa, Patricia Egger

Current solutions for privacy-preserving data sharing among multiple parties either depend on a centralized authority that must be trusted and provides only weakest-link security (e.g., the entity that manages private/secret cryptographic keys), or leverag ...

De Gruyter2017

A privacy-preserving solution for compressed storage and selective retrieval of genomic data

Jean-Pierre Hubaux, Jacques Fellay, Erman Ayday, Adam Molyneaux, Zhicong Huang, Huang Lin, Zhi Ming Xu

In clinical genomics, the continuous evolution of bioinformatic algorithms and sequencing platforms makes it beneficial to store patients' complete aligned genomic data in addition to variant calls relative to a reference sequence. Due to the large size of ...

Cold Spring Harbor Laboratory2016

GenoGuard: Protecting Genomic Data against Brute-Force Attacks

Jean-Pierre Hubaux, Jacques Fellay, Erman Ayday, Zhicong Huang, Ari Juels

Secure storage of genomic data is of great and increasing importance. The scientific community's improving ability to interpret individuals' genetic materials and the growing size of genetic database populations have been aggravating the potential conseque ...

2015

Quantifying Genomic Privacy via Inference Attack with High-Order SNV Correlations

Jean-Pierre Hubaux, Jacques Fellay, Erman Ayday, Zhicong Huang, Sahel Shariati Samani

As genomic data becomes widely used, the problem of genomic data privacy becomes a hot interdisciplinary research topic among geneticists, bioinformaticians and security and privacy experts. Practical attacks have been identified on genomic data, and thus ...

2015

Differential Privacy with Bounded Priors: Reconciling Utility and Privacy in Genome-Wide Association Studies

Jean-Pierre Hubaux, Erman Ayday, Zhicong Huang, Florian Tramèr

Differential privacy (DP) has become widely accepted as a rigorous definition of data privacy, with stronger privacy guarantees than traditional statistical methods. However, recent studies have shown that for reasonable privacy budgets, differential priva ...

2015