Position Paper: Assessing Robustness, Privacy, and Fairness in Federated Learning Integrated with Foundation Models
Authors: Xi Li, Jiaqi Wang | Published: 2024-02-02
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BrainLeaks: On the Privacy-Preserving Properties of Neuromorphic Architectures against Model Inversion Attacks
Authors: Hamed Poursiami, Ihsen Alouani, Maryam Parsa | Published: 2024-02-01 | Updated: 2024-05-07
Integrating Differential Privacy and Contextual Integrity
Authors: Sebastian Benthall, Rachel Cummings | Published: 2024-01-28
GuardML: Efficient Privacy-Preserving Machine Learning Services Through Hybrid Homomorphic Encryption
Authors: Eugene Frimpong, Khoa Nguyen, Mindaugas Budzys, Tanveer Khan, Antonis Michalas | Published: 2024-01-26
MedBlindTuner: Towards Privacy-preserving Fine-tuning on Biomedical Images with Transformers and Fully Homomorphic Encryption
Authors: Prajwal Panzade, Daniel Takabi, Zhipeng Cai | Published: 2024-01-17
Local Privacy-preserving Mechanisms and Applications in Machine Learning
Authors: Likun Qin, Tianshuo Qiu | Published: 2024-01-08
Adaptive Differential Privacy in Federated Learning: A Priority-Based Approach
Authors: Mahtab Talaei, Iman Izadi | Published: 2024-01-04
Locally Differentially Private Embedding Models in Distributed Fraud Prevention Systems
Authors: Iker Perez, Jason Wong, Piotr Skalski, Stuart Burrell, Richard Mortier, Derek McAuley, David Sutton | Published: 2024-01-03
An Empirical Study of Efficiency and Privacy of Federated Learning Algorithms
Authors: Sofia Zahri, Hajar Bennouri, Ahmed M. Abdelmoniem | Published: 2023-12-24
Harnessing Inherent Noises for Privacy Preservation in Quantum Machine Learning
Authors: Keyi Ju, Xiaoqi Qin, Hui Zhong, Xinyue Zhang, Miao Pan, Baoling Liu | Published: 2023-12-18 | Updated: 2024-03-07