$PRIV privacy

Latest papers

1. Tulva: Practical Asynchronous Threshold FHE cs.CR · 14 Oct · 1 hit

   …implementation, benchmark its threshold decryption performance and evaluate the end-to-end costs for typical privacy-preserving Ethereum Virtual Machine (EVM) use cases. For 16-out-of-512 threshold and a publicly…

2. Quantifying privacy risks in foundation model representations of brain MRI cs.CV · 14 Oct · 1 hit

   Pretrained representations are increasingly used to share and reuse information from medical images without…

3. GeoCloak: An Agentic Framework for Semantics-Preserving Geolocation Privacy via Peripheral Clue Manipulation cs.CV · 14 Oct · 4 hits

   …models (LVLMs) has made geolocation inference from images highly accurate and accessible. This poses serious privacy risks: a passive adversary with black-box LVLM access can infer a user's location from a single photo…

4. SPARS: A Stability-Plasticity-Aware Region Selection Framework for Continual Learning cs.LG · 14 Oct · 1 hit

   …forgetting. Memory replay methods mitigate catastrophic forgetting but rely on previous samples, raising privacy, memory, and scalability concerns. On the other hand, parameter isolation-based methods preserve…

5. Simultaneous Secure Communications and Sensing Privacy with Full Duplex MIMO Radios eess.SP · 14 Oct · 4 hits

   …minimum secrecy rate for data confidentiality and a minimum eavesdropping Cramer-Rao Bound (CRB) for sensing privacy. We derive the eavesdropping information measures governing both data interception and scene…

6. No Way To Steal My Face: Proactive Defense Against Identity-Preserving Personalized Generation cs.CV · 14 Oct · 1 hit

   …and virtual try-on systems. However, their reliance on sensitive facial reference images raises growing privacy concerns. Existing defense mechanisms are primarily designed for training-based personalization and…

7. A Graph-Based Analysis of Comparability, Scale, and Attribution in Private Transformer Inference cs.CR · 14 Oct · 1 hit

   Rising privacy concerns around large language models have accelerated research in private Transformer inference…

8. On Inherent Privacy of Posterior Sampling: A Unified R\'enyi-Divergence Framework stat.ML · 14 Oct · 5 hits

   Differential Privacy (DP) provides a rigorous framework for quantifying privacy guarantees. While most methods achieve DP…