AI Privacy Risks and Protection

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19 papers in the last 28 days · 0.3% of indexed attention

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Differential PrivacyPrivacy-Preserving FrameworkHomomorphic EncryptionEfficient Privacy LossPrivacy-Utility Trade-OffsDiffie-Hellman

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Period ending 2026-09-21

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Period ending 2026-09-07

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  1. Idiobionics: The Unification of Privacy and Intelligent Robotic Prostheses

    Jul 8, 2026Kwesi Afari Darfoor, Patrick M. Pilarski, Bailey KacsmarLegsAI Privacy Risks and Protection

  2. Continual Learning With Participation Privacy: An Auditable Buffering-Aggregation Recipe

    Jul 8, 2026T-H. Hubert Chan, Elaine Shi, Mengshi Zhao +1Efficient Continual LearningAI Privacy Risks and Protection

  3. POPS: Recovering Unlearned Multi-Modality Knowledge in MLLMs with Prompt-Optimized Parameter Shaking

    Jul 7, 2026Zhangheng LI, Jianing Zhu, Junyuan Hong +4Large Language Model UnlearningMulti-Modal Large Language Models

  4. Measuring the practice of shared-decision making (OPTION12): An Investigation into Open-sourced Smaller LLMs (OS-sLLMs) for Better Privacy and Sustainability

    Jul 7, 2026Tamara Wit, Lifeng Han, Carly Heipon +3Large Language Model Decision-MakingClinical Decision Support

  5. Unlearnable Faces: Privacy Protection Surviving Extraction Pipeline

    Jul 7, 2026Byunghoon Oh, Sunghwan Park, Jaewoo LeeFacial RecognitionFace Embeddings

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

    Jul 7, 2026Adam Jenkins, Agnieszka Kitkowska, Caterina Maidhof +22Artificial Intelligence SafetySecurity

  7. TIER: Trajectory-Invariant Explanation Regularization for Membership Privacy

    Jul 3, 2026Varun Sharma, Kar Wai Fok, Vrizlynn L. L. ThingMembership Inference AttacksMembership Inference

  8. Unveiling the Non-Monotonic Effect of Privacy on Generalization under Byzantine Robustness

    Jul 1, 2026Thomas Boudou, Batiste Le Bars, Nirupam Gupta +1Differential PrivacyGeneralization Bounds

  9. Depth-Only Open-Vocabulary 3D Semantic Segmentation For Privacy-Preserving Robotic Applications

    Jul 1, 2026Xuying Huang, Sicong Pan, Maren Bennewitz3D Semantic SegmentationAI Privacy Risks and Protection

  10. Semantic Leakage and Privacy Preservation in Relay-Assisted Semantic Communications

    Jun 30, 2026Yalin E. Sagduyu, Tugba Erpek, Aylin Yener +1Semantic CommunicationsData Leakage

  11. TDGT: A Tabular Data Generation Toolkit supporting adaptive GPU-accelerated Bayesian mixture models, diffusion-based models, and latent-space generative modeling

    Jun 30, 2026Vasileios C. Pezoulas, Nikolaos S. Tachos, Eleni Georga +3Synthetic Tabular DataSynthetic Data

  12. Bit-ViP: Leveraging Bit-planes to Preserve Visual Privacy in Images through Obfuscation

    Jun 28, 2026Vishesh Kumar Tanwar, Ashish Gupta, Sanjay Madria +1ObfuscationAI Privacy Risks and Protection

  13. ToolPrivacyBench: Benchmarking Purpose-Bound Privacy in Tool-Using LLM Agents

    Jun 26, 2026Shijing Hu, Liang Liu, Zhu Meng +1Efficient Privacy LossAI Privacy Risks and Protection

  14. Agents That Know Too Much: A Data-Centric Survey of Privacy in LLM Agents

    Jun 25, 2026Nada Lahjouji, Ashwin Gerard ColacoLarge Language Model AgentsAI Privacy Risks and Protection

  15. Privacy Vulnerabilities of Attention Layers in Tabular Foundation Models and Protection of High-Risk Queries

    Jun 24, 2026Tânia Carvalho, Maxime CordyTabular Foundation ModelsMembership Inference Attacks

  16. Federated Hash Projected Latent Factor Learning

    Jun 24, 2026Jialan HeFederated LearningAI Privacy Risks and Protection

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

    Jun 24, 2026Balamurugan Palanisamy, G S S Chalapathi, Vikas Hassija +1Retrieval-Augmented Generation SystemsLarge Language Model Safety

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

    Jun 23, 2026Yuanhe Zhao, Tianyu Zhang, Huafei Xing +3AI Privacy Risks and ProtectionLarge Language Model Baselines

  19. Natural Identifiers for Privacy and Data Audits in Large Language Models

    Jun 23, 2026Lorenzo Rossi, Bartłomiej Marek, Franziska Boenisch +1Algorithm AuditingAI Privacy Risks and Protection

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

    Jun 22, 2026Raphaël Delécluse, Hazem Wannous, Laurent GuimasRe-IdentificationRgb-Depth Cameras

  21. MuPPET: A Benchmark for Contextual Privacy of LLM Assistants in Multi-Party Conversations

    Jun 22, 2026Elena Sofia Ruzzetti, Cornelius Emde, Sangdoo Yun +2Efficient Privacy LossAI Privacy Risks and Protection

  22. Minimax Quantile Lower Bounds for Interactive Statistical Decision Making with Privacy

    Jun 22, 2026Raghav Bongole, Amirreza Zamani, Tobias J. Oechtering +1MinimaxGeneralized Linear Bandit

  23. PrivacyAlign: Contextual Privacy Alignment for LLM Agents

    Jun 19, 2026Manveer Singh Tamber, Abhay Puri, Marc-Etienne Brunet +3Artificial Intelligence AlignmentLarge Language Model Agents

  24. Predictability as a Fine-Grained Measure for Privacy

    Jun 18, 2026Linda Lu, Karthik SridharanDifferential PrivacyAI Privacy Risks and Protection

  25. Quantum ring all-reduce: communication and privacy advantages for distributed learning

    Jun 18, 2026María Gragera Garcés, Lirandë PiraQuantum AdvantageQuantum Machine Learning

  26. Private Learning with Public Feature Conditioning

    Jun 17, 2026Shuli Jiang, Walid Krichene, Nicolas MayorazDifferential PrivacyAI Privacy Risks and Protection

  27. What Your Model Threw Away and Why You'll Want It Back: Masking, Fingerprinting, and Privacy from Discarded Geometry

    Jun 17, 2026Zachary P. BradshawFingerprintEquivariant Neural Networks

  28. Security and Privacy Prompts in the Wild: What Users Ask LLMs and How LLMs Respond

    Jun 16, 2026Hobin Kim, Xiaoyuan Wu, Omer Akgul +2Large Language Model ReliabilityChatbots

  29. Differential Privacy of Gaussian Process Posterior Sampling

    Jun 16, 2026Tomasz MaciazekDifferential PrivacyGaussian Process

  30. CheckMIABench: Firm Foundations For Membership Inference Attacks on Language Models

    Jun 16, 2026Jeffrey G. Wang, Jason Wang, Marvin Li +1Membership Inference AttacksLanguage Model Evasion Attacks

  31. Your Privacy My Cloak: Backdoor Attacks on Differentially Private Federated Learning

    Jun 15, 2026Xiaolin Li, Ning Wang, Ninghui Li +1Differential PrivacyFederated Learning

  32. Beyond Weights and Gradients: A Taxonomy of Federated Learning Messages

    Jun 15, 2026Alvaro Javier Vargas Guerrero, Xinguang Wang, Quang Manh Doan +1Federated LearningModel Weights

  33. SoK: Security and Privacy of Foundation-Model-Powered Robots

    Jun 15, 2026Xueluan Gong, Chen Chen, Jinxin Liu +2SecurityRobot Systems

  34. Cross-Silo De-Anonymization Under Local Differential Privacy: Threat Model, Phase Transition, and Coordination Necessity

    Jun 15, 2026Ziniu Liu, Aiping LiDifferential PrivacyAnonymization

  35. Privacy from Symmetry: Orthogonally Equivariant Transformers for LLM Inference

    Jun 15, 2026Alexander Yukhimchuk, Andrey Shulga, Mladen Kolar +1ObfuscationPrivacy-Preserving Framework

  36. Facial Affect Analysis for Service-Oriented Systems: Advances, Challenges, and Future Visions

    Jun 13, 2026Spyridon Georgiou, Aggelos Psiris, Thomas Lagkas +4MicroservicesSoftware

  37. Behavioral Audit of Machine Unlearning Has a Privacy Cost

    Jun 12, 2026Liou Tang, James Joshi, Ashish KunduMachine UnlearningEfficient Privacy Loss

  38. Let's Ask Gauss: Improved One-Run Privacy Auditing

    Jun 10, 2026Adya Agrawal, Yu Wei, Jaspal Singh +2Differential PrivacyAI Privacy Risks and Protection

  39. Fed-FBD: Federated Functional Block Diversification for Isolation, Privacy, and Surgical Unlearning

    Jun 10, 2026Weijie Chen, Alan B. McMillanFederated LearningFederated Averaging

  40. CAPED: Context-Aware Privacy Exposure Defense for Mobile GUI Agents

    Jun 10, 2026Siyu Shen, Fenghao Xu, Wenrui Diao +1Graphical User Interface AgentsAI Privacy Risks and Protection

  41. Detecting Sensitive Personal Information in Japanese Pre-Training Corpora for Large Language Models

    Jun 10, 2026Rei Minamoto, Yusuke Oda, Daisuke KawaharaAI Privacy Risks and ProtectionText Corpora

  42. The Vision Encoder as a Privacy Boundary: Visual-Token Side Channels in Encoder-Free Vision-Language Models

    Jun 10, 2026Chenyu Zhou, Qiliang Jiang, Shuning Wu +1Vision EncodersVisual Tokens

  43. Advancing the State-of-the-Art in Empirical Privacy Auditing

    Jun 9, 2026Nicole Mitchell, Galen Andrew, Arun Ganesh +2Efficient Privacy LossAlgorithm Auditing

  44. Local Is Not a Sufficient Privacy Boundary: Governing OS-Integrated On-Device AI

    Jun 8, 2026Jonghyun Chung, Sanket BadheArtificial Intelligence GovernanceAI Privacy Risks and Protection

  45. Clinically Grounded Privacy Evaluation of Medical LMs

    Jun 8, 2026Sasha Ronaghi, Sana Tonekaboni, Lena Stempfle +6Data LeakageAI Privacy Risks and Protection

  46. On Choosing the μμ Parameter in Gaussian Differential Privacy

    Jun 8, 2026Bogdan Kulynych, Antti HonkelaDifferential PrivacyAI Privacy Risks and Protection

  47. Benchmarking Empirical Privacy Protection for Adaptations of Large Language Models

    Jun 8, 2026Bartłomiej Marek, Lorenzo Rossi, Vincent Hanke +4Large Language Model AdaptationEfficient Privacy Loss

  48. Unveiling Privacy Risks in Multi-modal Large Language Models: Task-specific Vulnerabilities and Mitigation Challenges

    Jun 8, 2026Tiejin Chen, Pingzhi Li, Kaixiong Zhou +2Multi-Modal Large Language ModelsLarge Language Model Safety

  49. Differentially Private Range Subgraph Counting

    Jun 6, 2026Xian Chen, Ruobing Bai, Pan PengDifferential PrivacySubgraphs

  50. IDP-Bench: Benchmarking ability of LLMs to protect personal information in interdependent privacy contexts

    Jun 6, 2026Ayana Hussain, Soumya Sharma, Golnoosh Farnadi +3AI Privacy Risks and ProtectionCollective Behaviors

  51. CausShield: Sample Reconstruction-Resilient Vertical FL via Causal Representation Learning

    Jun 6, 2026Yongqi Jiang, Yansong Gao, Siguang Chen +1Privacy-Preserving FrameworkCausal Representation Learning

  52. Seeing Without Exposing: Adaptive Privacy Control for Open-World, Context-Hungry MLLMs

    Jun 5, 2026Siyuan Xu, Yibing Liu, Peilin Chen +3Multi-Modal Large Language ModelsAI Privacy Risks and Protection

  53. When Recovery Matters: The Blind Spot of Surrogate Privacy in MLLM Editing

    Jun 5, 2026Siyuan Xu, Yibing Liu, Peilin Chen +3Image EditingMultimodal Knowledge Editing

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

    Jun 5, 2026Bijaya DangolInteroperabilityMulti-Agent Workflows

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

    Jun 5, 2026Zifan Peng, Yini Huang, Aiwen Lu +7Efficient Privacy LossAI Privacy Risks and Protection

  56. Quantifying the Privacy of Counterfactuals by Leveraging Membership Inference Attacks Against Synthetic Data

    Jun 4, 2026Maryam Babaei, Yingke Wang, Hadrien Lautraite +3Membership Inference AttacksCounterfactual Reasoning

  57. Preserving Data Privacy in Learning Causal Structure with Fully Homomorphic Encryption

    Jun 3, 2026Jian Yang, Yuan Tong, Qinbin Li +2Homomorphic EncryptionDifferential Privacy

  58. Revisiting Privacy Amplification by Subsampling in Selective Release DPSGD

    Jun 3, 2026Xiaobo Huang, Fang XieDifferential PrivacyStochastic Gradient Descent

  59. Privacy-Robust Incrementality Measurement for Advertising Systems under Signal Loss

    Jun 2, 2026Prashant Shekhar, Caroline HowardAdsAI Privacy Risks and Protection

  60. Bayesian Membership Privacy for Graph Neural Networks

    Jun 2, 2026Sinan Yıldırım, Megha KhoslaGraph Neural NetworksMembership Inference