Secure and Distributed Assessment of Privacy-Preserving Releases of GWAS

in ACM/IFIP International Middleware Conference (2022, November)

Genome-wide association studies (GWAS) identify correlations between the genetic variants and an observable characteristic such as a disease. Previous works presented privacy-preserving distributed ... [more ▼]

Genome-wide association studies (GWAS) identify correlations between the genetic variants and an observable characteristic such as a disease. Previous works presented privacy-preserving distributed algorithms for a federation of genome data holders that spans multiple institutional and legislative domains to securely compute GWAS results. However, these algorithms have limited applicability, since they still require a centralized instance to decide whether GWAS results can be safely disclosed, which is in violation to privacy regulations, such as GDPR. In this work, we introduce GenDPR, a distributed middleware that leverages Trusted Execution Environments (TEEs) to securely determine a subset of the potential GWAS statistics that can be safely released. GenDPR achieves the same accuracy as centralized solutions, but requires transferring significantly less data because TEEs only exchange intermediary results but no genomes. Additionally, GenDPR can be configured to tolerate all-but-one honest-but-curious federation members colluding with the aim to expose genomes of correct members. [less ▲]

Threat Adaptive Byzantine Fault Tolerant State-Machine Replication

Scientific Conference (2021, September)

Critical infrastructures have to withstand advanced and persistent threats, which can be addressed using Byzantine fault tolerant state-machine replication (BFT-SMR). In practice, unattended cyberdefense ... [more ▼]

Critical infrastructures have to withstand advanced and persistent threats, which can be addressed using Byzantine fault tolerant state-machine replication (BFT-SMR). In practice, unattended cyberdefense systems rely on threat level detectors that synchronously inform them of changing threat levels. How- ever, to have a BFT-SMR protocol operate unattended, the state- of-the-art is still to configure them to withstand the highest possible number of faulty replicas f they might encounter, which limits their performance, or to make the strong assumption that a trusted external reconfiguration service is available, which introduces a single point of failure. In this work, we present ThreatAdaptive the first BFT-SMR protocol that is automatically strengthened or optimized by its replicas in reaction to threat level changes. We first determine under which conditions replicas can safely reconfigure a BFT-SMR system, i.e., adapt the number of replicas n and the fault threshold f, so as to outpace an adversary. Since replicas typically communicate with each other using an asynchronous network they cannot rely on consensus to decide how the system should be reconfigured. ThreatAdaptive avoids this pitfall by proactively preparing the reconfiguration that may be triggered by an increasing threat when it optimizes its performance. Our evaluation shows that ThreatAdaptive can meet the latency and throughput of BFT baselines configured statically for a particular level of threat, and adapt 30% faster than previous methods, which make stronger assumptions to provide safety. [less ▲]