Comprehensive analysis of privacy leakage in vertical federated learning during prediction X Jiang, X Zhou, J Grossklags Proceedings on Privacy Enhancing Technologies, 2022 | 47 | 2022 |
Signds-fl: Local differentially private federated learning with sign-based dimension selection X Jiang, X Zhou, J Grossklags ACM Transactions on Intelligent Systems and Technology (TIST) 13 (5), 1-22, 2022 | 17 | 2022 |
Privacy-preserving high-dimensional data collection with federated generative autoencoder X Jiang, X Zhou, J Grossklags Proceedings on Privacy Enhancing Technologies, 2022 | 17 | 2022 |
Distributed GAN-Based Privacy-Preserving Publication of Vertically-Partitioned Data X Jiang, Y Zhang, X Zhou, J Grossklags Proceedings on Privacy Enhancing Technologies, 2023 | 3 | 2023 |
Federated Hyperparameter Optimization Through Reward-Based Strategies: Challenges and Insights KK Nakka, A Frikha, R Mendis, X Jiang, X Zhou Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 1 | 2024 |
ObfuscaTune: Obfuscated Offsite Fine-tuning and Inference of Proprietary LLMs on Private Datasets A Frikha, N Walha, R Mendes, KK Nakka, X Jiang, X Zhou arXiv preprint arXiv:2407.02960, 2024 | | 2024 |
PII-Compass: Guiding LLM training data extraction prompts towards the target PII via grounding KK Nakka, A Frikha, R Mendes, X Jiang, X Zhou arXiv preprint arXiv:2407.02943, 2024 | | 2024 |
IncogniText: Privacy-enhancing Conditional Text Anonymization via LLM-based Private Attribute Randomization A Frikha, N Walha, KK Nakka, R Mendes, X Jiang, X Zhou arXiv preprint arXiv:2407.02956, 2024 | | 2024 |
Generating High-Dimensional, High Utility Synthetic Data X Jiang, X Zhou WO Patent 2021228404A1, 2021 | | 2021 |