I-GWAS: Privacy-Preserving Interdependent Genome-Wide Association Studies

in Proceedings on Privacy Enhancing Technologies (2023)

Genome-wide Association Studies (GWASes) identify genomic variations that are statistically associated with a trait, such as a disease, in a group of individuals. Unfortunately, careless sharing of GWAS ... [more ▼]

Genome-wide Association Studies (GWASes) identify genomic variations that are statistically associated with a trait, such as a disease, in a group of individuals. Unfortunately, careless sharing of GWAS statistics might give rise to privacy attacks. Several works attempted to reconcile secure processing with privacy-preserving releases of GWASes. However, we highlight that these approaches remain vulnerable if GWASes utilize overlapping sets of individuals and genomic variations. In such conditions, we show that even when relying on state-of-the-art techniques for protecting releases, an adversary could reconstruct the genomic variations of up to 28.6% of participants, and that the released statistics of up to 92.3% of the genomic variations would enable membership inference attacks. We introduce I-GWAS, a novel framework that securely computes and releases the results of multiple possibly interdependent GWASes. I-GWAS continuously releases privacy-preserving and noise-free GWAS results as new genomes become available. [less ▲]

Unlinkable Updatable Hiding Databases and Privacy-Preserving Loyalty Programs

in Proceedings on Privacy Enhancing Technologies (2021, July), 2021(3), 95-121

Loyalty programs allow vendors to profile buyers based on their purchase histories, which can reveal privacy sensitive information. Existing privacy friendly loyalty programs force buyers to choose ... [more ▼]

Loyalty programs allow vendors to profile buyers based on their purchase histories, which can reveal privacy sensitive information. Existing privacy friendly loyalty programs force buyers to choose whether their purchases are linkable. Moreover, vendors receive more purchase data than required for the sake of profiling. We propose a privacy-preserving loyalty program where purchases are always unlinkable, yet a vendor can profile a buyer based on her purchase history, which remains hidden from the vendor. Our protocol is based on a new building block, an unlinkable updatable hiding database (HD), which we define and construct. HD allows the vendor to initialize and update databases stored by buyers that contain their purchase histories and their accumulated loyalty points. Updates are unlinkable and, at each update, the database is hidden from the vendor. Buyers can neither modify the database nor use old versions of it. Our construction for HD is practical for large databases. [less ▲]

Publishing Community-Preserving Attributed Social Graphs with a Differential Privacy Guarantee

in Proceedings on Privacy Enhancing Technologies (2020), 2020(4), 131-152

We present a novel method for publishing differentially private synthetic attributed graphs. Our method allows, for the first time, to publish synthetic graphs simultaneously preserving structural ... [more ▼]

We present a novel method for publishing differentially private synthetic attributed graphs. Our method allows, for the first time, to publish synthetic graphs simultaneously preserving structural properties, user attributes and the community structure of the original graph. Our proposal relies on CAGM, a new community-preserving generative model for attributed graphs. We equip CAGM with efficient methods for attributed graph sampling and parameter estimation. For the latter, we introduce differentially private computation methods, which allow us to release communitypreserving synthetic attributed social graphs with a strong formal privacy guarantee. Through comprehensive experiments, we show that our new model outperforms its most relevant counterparts in synthesising differentially private attributed social graphs that preserve the community structure of the original graph, as well as degree sequences and clustering coefficients. [less ▲]

Black-Box Wallets: Fast Anonymous Two-Way Payments for Constrained Devices

in Proceedings on Privacy Enhancing Technologies (2020), 2020(1), 165--194

On privacy notions in anonymous communication

in Proceedings on Privacy Enhancing Technologies (2019), 2019(2), 105--125

Many anonymous communication networks (ACNs) with different privacy goals have been devel- oped. Still, there are no accepted formal definitions of privacy goals, and ACNs often define their goals ad hoc ... [more ▼]

Many anonymous communication networks (ACNs) with different privacy goals have been devel- oped. Still, there are no accepted formal definitions of privacy goals, and ACNs often define their goals ad hoc. However, the formal definition of privacy goals benefits the understanding and comparison of different flavors of privacy and, as a result, the improvement of ACNs. In this paper, we work towards defining and comparing pri- vacy goals by formalizing them as privacy notions and identifying their building blocks. For any pair of no- tions we prove whether one is strictly stronger, and, if so, which. Hence, we are able to present a complete hier- archy. Using this rigorous comparison between notions, we revise inconsistencies between the existing works and improve the understanding of privacy goals. [less ▲]