5 papers
Machine-learning-assisted phase-amplitude reduction for fast synchronization of airfoil wakes with constrained fluctuations
Daiki Beppu, Vedasri Godavarthi, Koichiro Yawata +2
This study considers rapidly modifying the wake shedding frequency of the flow around an airfoil using sparse sensor information, subject to constraints on the lift coefficient flu…
On the Evidentiary Limits of Membership Inference for Copyright Auditing
Murat Bilgehan Ertan, Emirhan Böge, Min Chen +2
As large language models (LLMs) are trained on increasingly opaque corpora, membership inference attacks (MIAs) have been proposed to audit whether copyrighted texts were used duri…
Function Recovery Attacks in Gate-Hiding Garbled Circuits using SAT Solving
Chao Yin, Zunchen Huang, Chenglu Jin +2
Semi-Private Function Evaluation (SPFE) enables joint computation while protecting both input data and the function itself. A practical instantiation is gate-hiding garbled circuit…
Fundamental Limitations of Favorable Privacy-Utility Guarantees for DP-SGD
Murat Bilgehan Ertan, Marten van Dijk
Differentially Private Stochastic Gradient Descent (DP-SGD) is the dominant paradigm for private training, but its fundamental limitations under worst-case adversarial privacy defi…
Beyond Anonymization: Object Scrubbing for Privacy-Preserving 2D and 3D Vision Tasks
Murat Bilgehan Ertan, Ronak Sahu, Phuong Ha Nguyen +2
We introduce ROAR (Robust Object Removal and Re-annotation), a scalable framework for privacy-preserving dataset obfuscation that eliminates sensitive objects instead of modifying…