Search: “privacy”

Privacy-Preserving Data Drift Detection and Recovery for Large-Scale LLM Applications via Proxy Representations

arXiv:2608.08245v1 Announce Type: cross Abstract: LLM applications deployed at scale face a fundamental challenge: privacy constraints prevent direct inspection of user interactions, making it difficu

11 Aug 2026

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Protecting patient privacy in clinical foundation models: Technical and legal perspectives

DGX agent

arXiv:2608.07705v1 Announce Type: new Abstract: Clinical foundation models trained on large-scale patient data are increasingly used for decision support, screening, and public health. As deployment e

applicationsarxiv-cs-ai

11 Aug 2026

Evaluating OpenAI's Privacy Filter: Cross-Lingual, Cross-Domain PII Detection Across 42 Benchmarks

arXiv:2608.02616v1 Announce Type: cross Abstract: We present the first independent, systematic evaluation of OpenAI's Privacy Filter (OPF), a 1.5B-parameter bidirectional PII detector, across 42 synth

5 Aug 2026

FedChronos: Federated Fine-Tuning of Time-Series Foundation Models for Privacy-Preserving Commodity Price Forecasting

arXiv:2608.01290v1 Announce Type: new Abstract: Time-series foundation models (TSFMs) such as Chronos have demonstrated strong forecasting capabilities across domains, yet adapting them to institution

4 Aug 2026

Robust Estimation of Sparse Numerical Vectors under Local Differential Privacy

arXiv:2607.27815v1 Announce Type: cross Abstract: Local differential privacy (LDP) protocols are vulnerable to poisoning attacks. Existing research have proposed efficient defense strategies for singl

31 Jul 2026

MOSAIC-FL, a micro-service based privacy-preserving framework with application to genomics

arXiv:2607.25107v1 Announce Type: cross Abstract: Security and privacy are primordial requirements for Federated Learning (FL), especially in fields such as healthcare and genomics where sensitive inf

29 Jul 2026

NWaaS: A Non-Intrusive and Privacy-Preserving Watermarking-as-a-Service System with Adaptive Resource Scheduling

model-releasesarxiv-cs-cv

arXiv:2507.18036v2 Announce Type: replace-cross Abstract: Securing intellectual property (IP) in Machine Learning as a Service is critical yet challenging. While deep neural network watermarking serve

27 Jul 2026

Sarus: Privacy-Preserving Multi-Vendor Perception Fusion via Homomorphic Encryption

arXiv:2607.19146v1 Announce Type: cross Abstract: Cooperative perception enables autonomous vehicles (AVs) to improve situational awareness by aggregating detection outputs from multiple agents and se

agentsarxiv-cs-cv

23 Jul 2026

Federated Deep Learning for Privacy-Preserving Cardiovascular Disease Risk Prediction

arXiv:2607.08595v1 Announce Type: new Abstract: Cardiovascular disease risk prediction models often rely on data from a single institution or centrally pooled datasets. Extending these models across i

10 Jul 2026

Idiobionics: The Unification of Privacy and Intelligent Robotic Prostheses

arXiv:2607.07775v1 Announce Type: new Abstract: The human body is at the center of a growing family of technologies designed to tightly and persistently couple biological and digital systems. Robotic

10 Jul 2026

Security and Privacy in Agentic AI: Grand Challenges and Future Directions

arXiv:2607.06608v1 Announce Type: cross Abstract: We present key challenges and future research directions in the security and privacy of agentic AI, based on a horizon-scanning exercise that brought

9 Jul 2026

Tutorials

Hierarchical Anti-Aesthetics: Protecting Facial Privacy against Customized Diffusion Models

arXiv:2607.02038v2 Announce Type: replace Abstract: The rise of customized diffusion models has fueled a boom in personalized visual content creation, but it also introduces serious risks of malicious

tutorialsarxiv-cs-cv

7 Jul 2026

Privacy-Aware Agent Collaboration for Dynamic VR Slice Management in 6G SD-RAN

arXiv:2606.26123v1 Announce Type: cross Abstract: Ultra-low latency and high throughput are required for Virtual Reality (VR) services in 6G networks, which presents critical challenges for Software-D

26 Jun 2026

Local Ai

Security and Privacy in Retrieval-Augmented Generation: Architectures, Threats, Defenses, and Future Directions for Building Trustworthy Systems

arXiv:2606.25533v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) has emerged as a dominant paradigm for enhancing large language models with external knowledge. By coupling retri

local-aiarxiv-cs-cl

25 Jun 2026

Privacy-Preserving RAG via Multi-Agent Semantic Rewriting: Achieving Confidentiality Without Compromising Contextual Fidelity

arXiv:2606.24623v1 Announce Type: cross Abstract: Retrieval-Augmented Generation enhances large language models by incorporating external knowledge, but deploying it in sensitive scenarios risks priva

24 Jun 2026

Integrated Marketing Attribution: A Bayesian Framework for Privacy-Safe Granular Measurement Anchored in MMM

arXiv:2606.16878v3 Announce Type: replace Abstract: Retail marketing measurement increasingly requires granular campaign-level insights without relying on user-level tracking. However, the two dominan

23 Jun 2026

Privacy-Preserving Person Re-Identification from Temporal Sequences with Transformer and Hungarian Optimization

arXiv:2606.23230v1 Announce Type: new Abstract: Person re-identification (Re-ID) is a crucial task in surveillance and human behavior analysis, often used in public spaces such as transport hubs. Trad

researcharxiv-cs-cv

23 Jun 2026

From Privacy to Workflow Integrity: Communication-Graph Metadata in Autonomous Agent Interoperability

arXiv:2606.07150v1 Announce Type: cross Abstract: Agent-interoperability protocols such as A2A and MCP standardize what agents say to one another, but assume address-based transport over HTTP(S). Such

8 Jun 2026

What Your Posts Reveal: A Benchmark and Agentic Framework for User-Level Privacy Leakage on Social Media

arXiv:2606.06784v1 Announce Type: cross Abstract: Public social media posts can reveal private information through weak cues scattered across text, images, or metadata. Such leakage is often cumulativ

8 Jun 2026

RAG Security and Privacy: Formalizing the Threat Model and Attack Surface

arXiv:2509.20324v2 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) is an emerging approach in natural language processing that combines large language models (LLMs) with ex

applicationsarxiv-cs-ai

6 Jun 2026

Need to Know: Contextual-Integrity-Grounded Query Rewriting for Privacy-Conscious LLM Delegation

arXiv:2606.04067v1 Announce Type: cross Abstract: As LLMs become increasingly woven into everyday workflows, user queries sent to cloud hosted LLMs routinely mix task-essential content with task non-e

4 Jun 2026

GuidaPA: Privacy-Preserving Chatbot for Public Administration via Federated Learning

arXiv:2606.01386v1 Announce Type: new Abstract: We present GuidaPA, a privacy-preserving chatbot for the Italian Public Administration (PA) trained via Federated Learning (FL) on documentation from tw

2 Jun 2026

The Fast Mixing Mechanism for Differential Privacy

arXiv:2605.30600v1 Announce Type: new Abstract: Randomized sketching is a central tool for compressing large-scale optimization problems while preserving accuracy. In particular, sketches that are bas

1 Jun 2026

Privacy-Enhanced Zero-Order Federated Learning via xMK-CKKS over Wireless Channels

arXiv:2605.30123v1 Announce Type: cross Abstract: Homomorphic encryption (HE) enables privacy-preserving aggregation in federated learning (FL) by allowing the server to operate on encrypted data with

29 May 2026

Bandwidth-Efficient and Privacy-Preserving Edge-Cloud Many-to-Many Speech Translation

arXiv:2605.28642v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have demonstrated significant potential for speech-to-text translation (S2TT). However, existing deployment par

BuddyBench: A Privacy-Constrained Multi-Task Benchmark for Pediatric Social-Communication Personalization

arXiv:2605.28089v1 Announce Type: new Abstract: BuddyBench introduces a privacy-constrained multi-task benchmark for pediatric social-communication personalization. Unlike existing neurodevelopmental

Got a Secret? LLM Agents Can't Keep It: Evaluating Privacy in Multi-Agent Systems

arXiv:2605.27766v1 Announce Type: new Abstract: LLM safety evaluations predominantly test models in isolation, yet deployed AI agents increasingly operate within persistent social environments alongsi

MaskClaw: Edge-Side Personalized Privacy Arbitration for GUI Agents with Behavior-Driven Skill Evolution

model-releasesarxiv-cs-cl

arXiv:2605.28646v1 Announce Type: cross Abstract: GUI agents rely on screenshots to infer intent and operate across applications, but these screenshots often contain private messages, medical records,

Privacy Protection Against Personalized Text-to-Image Synthesis via Cross-image Consistency Constraints

arXiv:2504.12747v2 Announce Type: replace Abstract: The rapid advancement of diffusion models and personalization techniques has made it possible to recreate individual portraits from just a few publi

researcharxiv-cs-cv

From Privacy to Generalization: Linear Max-Information Bounds for DP-SGD

arXiv:2605.26222v1 Announce Type: new Abstract: Understanding the relationship between generalization and privacy remains a central challenge in modern machine learning theory, particularly for deep n

27 May 2026

Secure, Verifiable, and Scalable Multi-Client Data Sharing via Consensus-Based Privacy-Preserving Data Distribution

arXiv:2601.00418v2 Announce Type: replace-cross Abstract: We propose the Consensus-Based Privacy-Preserving Data Distribution (CPPDD) framework, a lightweight and post-setup autonomous protocol for se

21 May 2026

Local Ai

Sustainability Is Not Linear: Quantifying Performance, Energy, and Privacy Trade-offs in On-Device Intelligence

arXiv:2603.26603v2 Announce Type: replace-cross Abstract: The migration of Large Language Models (LLMs) from cloud clusters to edge devices promises enhanced privacy and offline accessibility, but thi

local-aiarxiv-cs-lg

21 May 2026

MetaMoE: Diversity-Aware Proxy Selection for Privacy-Preserving Mixture-of-Experts Unification

arXiv:2605.14289v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) models scale capacity by combining specialized experts, but most existing approaches assume centralized access to training da

researcharxiv-cs-ai

15 May 2026

Tutorials

Optimization, Generalization and Differential Privacy Bounds for Gradient Descent on Kolmogorov-Arnold Networks

arXiv:2601.22409v3 Announce Type: replace-cross Abstract: Kolmogorov--Arnold Networks (KANs) have recently emerged as a structured alternative to standard MLPs, yet a principled theory for their train

tutorialsarxiv-cs-ai

14 May 2026

ERIS: Enhancing Privacy and Scalability in Federated Learning via Federated Shard Aggregation

arXiv:2602.08617v2 Announce Type: replace Abstract: Scaling Federated Learning (FL) to billion-parameter models forces a challenging trade-off between privacy, scalability, and model utility. Existing

12 May 2026

ICPR 2026 Competition on Privacy-Preserving Person Re-Identification from Top-View RGB-Depth Camera (TVRID)

model-releasesarxiv-cs-cv

arXiv:2605.04977v1 Announce Type: new Abstract: This companion paper reports the ICPR 2026 TVRID competition on privacy-aware top-view person re-identification. We present the competition setting, the

7 May 2026

Federated Semi-Supervised Graph Neural Networks with Prototype-Guided Pseudo-Labeling for Privacy-Preserving Gestational Diabetes Mellitus Prediction

arXiv:2605.01810v1 Announce Type: new Abstract: Gestational Diabetes Mellitus (GDM) is a high-prevalence pregnancy complication that requires accurate early risk stratification to reduce maternal and

5 May 2026

When RAG Chatbots Expose Their Backend: An Anonymized Case Study of Privacy and Security Risks in Patient-Facing Medical AI

model-releasesarxiv-cs-cl

arXiv:2605.00796v1 Announce Type: cross Abstract: Background: Patient-facing medical chatbots based on retrieval-augmented generation (RAG) are increasingly promoted to deliver accessible, grounded he

4 May 2026

Fidelity, Diversity, and Privacy: A Multi-Dimensional LLM Evaluation for Clinical Data Augmentation

arXiv:2604.27014v1 Announce Type: new Abstract: The scarcity of high-quality annotated medical data, particularly in mental health, poses a significant bottleneck for training robust machine learning

1 May 2026

A Survey on Split Learning for LLM Fine-Tuning: Models, Systems, and Privacy Optimizations

arXiv:2604.24468v1 Announce Type: cross Abstract: Fine-tuning unlocks large language models (LLMs) for specialized applications, but its high computational cost often puts it out of reach for resource

researcharxiv-cs-cl

28 Apr 2026

Sherpa.ai Privacy-Preserving Multi-Party Entity Alignment without Intersection Disclosure for Noisy Identifiers

arXiv:2604.19219v1 Announce Type: cross Abstract: Federated Learning (FL) enables collaborative model training among multiple parties without centralizing raw data. There are two main paradigms in FL:

22 Apr 2026

Preventing overfitting in deep learning using differential privacy

arXiv:2604.16334v1 Announce Type: new Abstract: The use of Deep Neural Network based systems in the real world is growing. They have achieved state-of-the-art performance on many image, speech and tex

21 Apr 2026

SafeLM: Unified Privacy-Aware Optimization for Trustworthy Federated Large Language Models

arXiv:2604.16606v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed in high-stakes domains, yet a unified treatment of their overlapping safety challenges remains

21 Apr 2026

Operationalising the Right to be Forgotten in LLMs: A Lightweight Sequential Unlearning Framework for Privacy-Aligned Deployment in Politically Sensitive Environments

arXiv:2604.12459v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed in politically sensitive environments, where memorisation of personal data or confidential conten

15 Apr 2026

CSA-Graphs: A Privacy-Preserving Structural Dataset for Child Sexual Abuse Research

arXiv:2604.07132v1 Announce Type: cross Abstract: Child Sexual Abuse Imagery (CSAI) classification is an important yet challenging problem for computer vision research due to the strict legal and ethi

10 Apr 2026

From Pixels to Privacy-Sensitive Features: An Information-Theoretic Framework for Reconstruction Bounds

arXiv:2610.13768v1 Announce Type: cross Abstract: What can an adversary recover from a model trained with DP-SGD? Its (arepsilon,elta) guarantee does not answer this question directly. We derive a dis

12 Oct 2026

When Routing Reveals Membership: Privacy Leakage from MoE Router Telemetry

arXiv:2610.10616v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) language models produce routing information during inference that may be logged or exposed for monitoring, debugging, load anal

9 Oct 2026

FaceKit: a Toolkit for Interpretable Facial Phenotyping, Synthetic Image Generation and Privacy Analysis in Rare Diseases