Georgi Ganev

According to our database, Georgi Ganev authored at least 14 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Synthetic Data, Similarity-based Privacy Metrics, and Regulatory (Non-)Compliance.

Georgi Ganev

CoRR, 2024

The Elusive Pursuit of Replicating PATE-GAN: Benchmarking, Auditing, Debugging.

Georgi Ganev, Meenatchi Sundaram Muthu Selva Annamalai, Emiliano De Cristofaro

CoRR, 2024

"What do you want from theory alone?" Experimenting with Tight Auditing of Differentially Private Synthetic Data Generation.

Meenatchi Sundaram Muthu Selva Annamalai, Georgi Ganev, Emiliano De Cristofaro

Proceedings of the 33rd USENIX Security Symposium, 2024

Graphical vs. Deep Generative Models: Measuring the Impact of Differentially Private Mechanisms and Budgets on Utility.

Georgi Ganev, Kai Xu, Emiliano De Cristofaro

Proceedings of the 2024 on ACM SIGSAC Conference on Computer and Communications Security, 2024

2023

On the Inadequacy of Similarity-based Privacy Metrics: Reconstruction Attacks against "Truly Anonymous Synthetic Data".

Georgi Ganev, Emiliano De Cristofaro

CoRR, 2023

On the Challenges of Deploying Privacy-Preserving Synthetic Data in the Enterprise.

Lauren Arthur, Jason Costello, Jonathan Hardy, Will O'Brien, James Rea, Gareth Rees, Georgi Ganev

CoRR, 2023

When Synthetic Data Met Regulation.

Georgi Ganev

CoRR, 2023

Understanding how Differentially Private Generative Models Spend their Privacy Budget.

Georgi Ganev, Kai Xu, Emiliano De Cristofaro

CoRR, 2023

Synthetic Data Generation of Many-to-Many Datasets via Random Graph Generation.

Kai Xu, Georgi Ganev, Emile Joubert, Rees Davison, Olivier Van Acker, Luke Robinson

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

dpart: Differentially Private Autoregressive Tabular, a General Framework for Synthetic Data Generation.

Sofiane Mahiou, Kai Xu, Georgi Ganev

CoRR, 2022

On Utility and Privacy in Synthetic Genomic Data.

Bristena Oprisanu, Georgi Ganev, Emiliano De Cristofaro

Proceedings of the 29th Annual Network and Distributed System Security Symposium, 2022

Robin Hood and Matthew Effects: Differential Privacy Has Disparate Impact on Synthetic Data.

Georgi Ganev, Bristena Oprisanu, Emiliano De Cristofaro

Proceedings of the International Conference on Machine Learning, 2022

2021

DP-SGD vs PATE: Which Has Less Disparate Impact on GANs?

Georgi Ganev

CoRR, 2021

Measuring Utility and Privacy of Synthetic Genomic Data.

Bristena Oprisanu, Georgi Ganev, Emiliano De Cristofaro

CoRR, 2021