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Period ending 2026-09-21

17 new papers

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15 new papers

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  1. Private Decentralized Optimization with Noise Reduction and Bias Correction

    Sep 23, 2026Yizhao Fan, Wenjian Luo, Jiaojiao ZhangDifferential Privacy

  2. Empirical Auditing of Edge-Private Graph Generators

    Sep 21, 2026Anum Fatima, Stratis Limnios, James Adams +4Efficient Privacy LossTransformation-Based Attacks

  3. Feature Suppression and Differential Privacy for Residential Traffic Classification: A Two-Home Federated Study

    Sep 20, 2026Márton Pál Lipcsey-Magyar, Adrian PekarFederated LearningDifferential Privacy

  4. Perplexity Predicts Protection: Choosing Pretrained Backbones for Worst-Client Fairness in Federated Parameter-Efficient Fine-Tuning

    Sep 20, 2026Kiran Naseer, Samreen Azhar, Umar Shoaib +2Fairness-Aware LearningPrivacy-Preserving Framework

  5. Opinion Dynamics-based Coalition Formation for Federated Learning in Heterogeneous IoT Systems

    Sep 17, 2026Mohammed El Hanjri, Anas Abouaomar, Hamidou Tembine +1Federated LearningFederated Averaging

  6. ASLEval: Measuring Privacy Exposure Displacement in LLM Agent Sessions

    Sep 16, 2026Guosen Wu, Huizhen Huang, Guoxiong Long +2AI Privacy Risks and ProtectionAgentic Evaluations

  7. Beyond EER: Multi-Dimensional Evaluation of Information Leakage in Speaker De-Identification

    Sep 16, 2026Seungmin Seo, Oleg Aulov, P. Jonathon Phillips +2Speaker IdentityAnonymization

  8. OptiPrime: Optimizing Private Inference through Protocol-Hardware Co-design

    Sep 15, 2026Jiangrui Yu, Ye Yu, Si Chen +5Graph Neural Network InferenceHomomorphic Encryption

  9. Adaptive Bayesian Partner Selection for Federated Clinical Centers

    Sep 15, 2026Navid Seidi, Satyaki Roy, Sajal K. DasFederated LearningPrivacy-Preserving Framework

  10. Differentially Private Semantic Plans for Aggregate Insight Generation

    Sep 14, 2026Behrooz RazeghiDifferential PrivacyData Mining

  11. Privacy-Aligned Personalized Federated Learning with Compact Adaptation and Variable-Length Gaussian Communication

    Sep 14, 2026Yilin Xu, Chun Hei Michael Shiu, Chih Wei Ling +1Federated LearningDifferential Privacy

  12. Privacy-enhanced federated learning via asynchronous aggregation and local differential perturbation

    Sep 14, 2026Zhen Zhong, Shini Yang, Liesheng WeiFederated LearningDifferential Privacy

  13. LLM-Based Schema-Aware Split Learning for Privacy-Preserving Mental Distress Prediction Across Heterogeneous Surveys

    Sep 14, 2026Md Khalid Syfullah, Alvi Ataur KhalilPrivacy-Preserving FrameworkMental Health

  14. Don't Send What You Don't Need: Question-Guided Token Pruning as a Privacy Defense for Vision-Language Models

    Sep 14, 2026Md Khalid Syfullah, Alvi Ataur KhalilVisual Token PruningPruning

  15. RAG-CT: Mitigating Privacy Risks on Retrieval-Augmented Generation Systems via Scanning Prompt Distribution

    Sep 14, 2026Xingyu Lyu, Jiayimei Wang, Jianfeng He +3Retrieval-Augmented Generation SystemsAI Privacy Risks and Protection

  16. GRIN+: Towards Fast Yet Effective Machine Unlearning for Imbalanced Medical Data

    Sep 14, 2026Minghui Huang, Junxiao WangMachine UnlearningExtreme Class Imbalance

  17. SpliTEE: Improving LLM Inference on Trusted Hardware with Differentially Private GPU Outsourcing

    Sep 14, 2026Shashie Dilhara Batan Arachchige, Robin Carpentier, Hassan Jameel Asghar +1LLM Inference EfficiencyDifferential Privacy

  18. USPLIT-VQA: U-Shaped Split Learning for Visual Question Answering with Contribution-Aware Weighted Aggregation

    Sep 14, 2026Md Khalid Syfullah, Alvi Ataur KhalilTextvqaFederated Learning

  19. GraphProfiler: Source-Linked Sensitive Attribute Inference via Personal Knowledge Graphs

    Sep 14, 2026Ahmed Sohair Khan, Estrid He, Chenglong Ma +2ProfilingAI Privacy Risks and Protection

  20. Retrieval-Augmented Generation for Scientific Code Understanding

    Sep 14, 2026Aaron Nobile, Andreas Adelmann, Mohsen SadrPrivacy-Preserving Framework

  21. A Differentially Private Federated Proximal Optimization Framework for Customer Churn Prediction in Heterogeneous Federated Telecom Networks

    Sep 14, 2026Joydeb Kumar Sana, Subrata Chakraborty, M M Manjurul IslamFederated LearningChurn Prediction

  22. LLMs as Oracles: Reliance on LLMs for Subjective Personal Questions

    Sep 13, 2026Myra Cheng, Lujain Ibrahim, Grace Liu +5OraclesDeliberation

  23. Privacy Preserving Gossip Learning

    Sep 13, 2026Erkan Bayram, Mohamed-Ali Belabbas, Tamer BaşarDifferential PrivacyAI Privacy Risks and Protection

  24. CryptoL: Towards Scale Dominance and Physics Constraints Mitigation in Financial Multivariate Time Series Forecasting

    Sep 12, 2026Yalda Taheri, Mohammad Hassan Heydari, Armon Rasooli +3Decentralized FinanceMultivariate Time Series Forecasting

  25. Differentially Private EEG Feature Anonymization: A Privacy-Utility Case Study in Clinical Neurophysiology

    Sep 11, 2026Noman Sadiq, Mohsen TooraniElectroencephalography Spatial Super-ResolutionDifferential Privacy

  26. Component-Aware Differential Privacy for Federated Multilingual Speech-LLMs

    Sep 11, 2026Jordi Luque, Fernando López, Aleix SantSpeech-LlmsDifferential Privacy

  27. Predicting Privacy Leakage from Weight Spectral Density

    Sep 10, 2026Richard J. Preen, Jim SmithEfficient Privacy LossMembership Inference Attacks

  28. Maverick: Private and Verifiable LLM Inference Made Practical via Matrix-Vector Multiplication Delegation

    Sep 9, 2026Ben Merbaum, Mohammad Amin Raeisi, Wenhao Wang +3LLM Inference EfficiencyMatrix Multiplication

  29. AXON: A ROS 2 RMW with Shared-Memory/QUIC Transport and QKD/ML-KEM Key Establishment

    Sep 9, 2026Sergio Sánchez de la Fuente, Miguel Ángel González-Santamarta, Francisco Javier Rodríguez-Lera +2Robot Operating SystemPost-Quantum Cryptography

  30. Subgroup Membership Inference Audits of Differentially Private Synthetic Text

    Sep 9, 2026Yidan Sun, Viktor Schlegel, Srinivasan Nandakumar +2Membership Inference AttacksDifferential Privacy

  31. Privacy-Preserving Split Learning for Federated LLM Fine-Tuning

    Sep 9, 2026Heng Jin, Chaoyu Zhang, Hexuan Yu +2Federated LearningLarge Language Model Fine-Tuning

  32. Encrypt What Matters: When Selective Homomorphic Inference Is Efficient

    Sep 8, 2026Ali Backour, Juan Reyes, Jaime Punyed +1Homomorphic EncryptionText2Cypher

  33. Geographically Regularized AUC-Maximizing Personalized Federated Learning

    Sep 8, 2026Mayu Hiraishi, Kensuke Tanioka, Toshio ShimokawaFederated LearningPrivacy-Preserving Framework

  34. Privacy Leakage from a Thousand Words: Millipixel Location Recovery from Dot Maps

    Sep 7, 2026Yuntao Du, Tanishq Pauskar, Hao Wang +2MapAI Privacy Risks and Protection

  35. Characterizing Privacy Risks of Quantum Machine Learning with Emergent Quantum-Native Access

    Sep 4, 2026Liou Tang, James Joshi, Ashish KunduQuantum Machine LearningAI Privacy Risks and Protection

  36. OSR: Output Space Redistribution for Adaptive Label Removal in Classification Models

    Sep 3, 2026Minyi Peng, Darian Gunamardi, Ivan Tjuawinata +2RemovalBinary Classification

  37. Pushing the (Decision) Boundaries: Dynamically Calibrating Differentially Private Noise to Explainability in Federated Learning

    Sep 3, 2026Michael Khavkin, Kichang Lee, Jaeho Jin +2Federated LearningDifferential Privacy

  38. Mind the Gap: Robustness Risks in PII Detection Systems

    Sep 3, 2026Adeel Zafar, Slawomir NowaczykEfficient Privacy LossArtificial Intelligence Detection

  39. Privacy, Robustness, and Fairness Trade-offs in Federated Intrusion Detection: Geometric Indistinguishability at the Aggregation Interface

    Sep 3, 2026Adrita Rahman Tory, ABM Shawkat Ali, Md Abu Layek +1Federated LearningIntrusion Detection

  40. Spruce: Scalable Private Outsourced Retrieval Using Compact Embeddings

    Sep 3, 2026Peichun Hua, Yunming XiaoPrivacy-Preserving FrameworkText Corpora

  41. Differentially private federated learning with Byzantine-robust aggregation: A cross-domain framework for secure model training in banking and healthcare systems

    Sep 2, 2026Srikumar NayakFederated LearningByzantine Attacks

  42. Seeing Less Is Not Seeing Safely: Privacy Leakage from Task-Scoped Robot Perception Exports

    Sep 2, 2026Yuqiao Xu, Erman AydayRobotic PerceptionAI Privacy Risks and Protection

  43. Privacy Leakage in Federated Learning: Gradient-Based Client Identity Inference and Defenses for Inertial Sensing in Vehicular Edge Networks

    Sep 2, 2026Ali Akarma, Toqeer Ali Syed, Muhammad Khan +2Federated LearningPrivacy-Preserving Framework

  44. Privacy-Preserving Topology-Guided Safety for LLM-Based Multi-Agent Systems via Federated Graph Learning

    Sep 2, 2026Jinxi Yu, Eric Hanchen Jiang, Levina Li +6Federated Graph LearningFederated Learning

  45. Privacy Washing: Detecting Internal Contradictions in Privacy Policies

    Sep 2, 2026Thomas BrackinAI Privacy Risks and ProtectionPrevalence

  46. Pushing Forward Multi-Secret-Key Homomorphic Encryption for Private Average Aggregation

    Sep 1, 2026Miguel Morona-Mínguez, Fernando Pérez-González, Alberto Pedrouzo-UlloaHomomorphic EncryptionFederated Learning

  47. HEAT: Faster Fully Homomorphic Inference via Approximations-Weights Co-Adaptation

    Sep 1, 2026Alessandro Zirilli, Davide Marincione, Evgenios M. Kornaropoulos +2Homomorphic EncryptionAlternating Direction Method Of Multiplier

  48. Optimizing Byzantine Node Placement in Decentralized Federated Learning

    Sep 1, 2026Edoardo Gabrielli, Gabriele TolomeiByzantine AttacksFederated Learning

  49. Position: Privacy Is a Claim, Not a Property of Synthetic Data

    Sep 1, 2026Jiachen Zhao, Antonia Januszewicz, Taeho JungSynthetic DataAI Privacy Risks and Protection

  50. Differentially Private Paired Table-Image Multimodal Synthesis

    Sep 1, 2026Kai Chen, Josephine Lamp, Somesh Jha +1Synthetic Tabular DataMedical Image Generation

  51. The Privacy-Hallucination Tradeoff in Differentially Private Language Models

    Aug 31, 2026Krithika Ramesh, Krishna Pillutla, Danish Pruthi +1Large Language Model HallucinationDifferential Privacy

  52. NeuroPriv: Adversarial Representation Learning for Privacy in Wearable EEG Systems

    Aug 31, 2026Sarmistha Sarna Gomasta, Bhawana Chhaglani, Prashant ShenoyElectroencephalography Spatial Super-ResolutionRemote Physiological Measurement

  53. Balancing Privacy, Utility, and Safety in LLM Alignment through Preference Optimization

    Aug 31, 2026Dishu Yang, Jingjing Liu, Jize LiDirect Preference OptimizationAI Privacy Risks and Protection

  54. ECA-BLS: An Efficient Complex-Augmented Broad Learning System

    Aug 30, 2026A. Rahaman, A. Quadir, M. Sajid +2Homomorphic Encryption

  55. Creation begins with understanding: LLMs as strategy designers for privacy-preserving tabular data synthesis

    Aug 30, 2026Jinmeng Li, Quan Zhang, Hangting Ye +4Synthetic Tabular DataSynthetic Data

  56. PrivBench: A Holistic and Modular Benchmarking Platform for Evaluating Text-to-Text Privatization

    Aug 30, 2026Stephen Meisenbacher, Andreea-Elena Bodea, Ahmet Bilal Akın +3Privacy-Preserving FrameworkMachine-Generated Text Detection

  57. Performative Privacy: When Differential Privacy Maximizes Utility

    Aug 28, 2026Uddalak Mukherjee, Edwige Cyffers, Yann ChevaleyreDifferential PrivacyPrivacy-Preserving Framework

  58. Coordination on a Budget: Federated Active Learning with Few Labels

    Aug 19, 2026Liam Mohr, Daphna WeinshallActive LearningCandidate Label Distributions

  59. Beyond Visual Evidence: Revealing and Mitigating Relational Privacy Leakage in Document MLLMs

    Aug 13, 2026Beining Xu, Hairui Wang, Jiaxin Wang +2Efficient Privacy LossMulti-Modal Large Language Models

  60. SoK: From Generation to Consumption of Privacy Documents in Software Systems

    Aug 12, 2026Shidong Pan, Clark LaChance, Zhen Tao +1AI Privacy Risks and ProtectionDocumentation