26 citations · 42 across the 5 of their papers we have counts for
5 papers
DP-SNP-TIHMM: Differentially Private, Time-Inhomogeneous Hidden Markov Models for Synthesizing Genome-Wide Association Datasets
Shadi Rahimian, Mario Fritz
Single nucleotide polymorphism (SNP) datasets are fundamental to genetic studies but pose significant privacy risks when shared. The correlation of SNPs with each other makes stron…
Private and Collaborative Kaplan-Meier Estimators
Shadi Rahimian, Raouf Kerkouche, Ina Kurth +1
Kaplan-Meier estimators are essential tools in survival analysis, capturing the survival behavior of a cohort. Their accuracy improves with large, diverse datasets, encouraging dat…
Practical Challenges in Differentially-Private Federated Survival Analysis of Medical Data
Shadi Rahimian, Raouf Kerkouche, Ina Kurth +1
Survival analysis or time-to-event analysis aims to model and predict the time it takes for an event of interest to happen in a population or an individual. In the medical context…
Sampling Attacks: Amplification of Membership Inference Attacks by Repeated Queries
Shadi Rahimian, Tribhuvanesh Orekondy, Mario Fritz
Machine learning models have been shown to leak information violating the privacy of their training set. We focus on membership inference attacks on machine learning models which a…
Segmentations-Leak: Membership Inference Attacks and Defenses in Semantic Image Segmentation
Yang He, Shadi Rahimian, Bernt Schiele +1
Today's success of state of the art methods for semantic segmentation is driven by large datasets. Data is considered an important asset that needs to be protected, as the collecti…