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Found 5 papers, 5 papers with code
Syft 0.5: A Platform for Universally Deployable Structured Transparency
We present Syft 0. 5, a general-purpose framework that combines a core group of privacy-enhancing technologies that facilitate a universal set of structured transparency systems.
Practical Defences Against Model Inversion Attacks for Split Neural Networks
We describe a threat model under which a split network-based federated learning system is susceptible to a model inversion attack by a malicious computational server.
PyVertical: A Vertical Federated Learning Framework for Multi-headed SplitNN
We introduce PyVertical, a framework supporting vertical federated learning using split neural networks.
U-Noise: Learnable Noise Masks for Interpretable Image Segmentation
Deep Neural Networks (DNNs) are widely used for decision making in a myriad of critical applications, ranging from medical to societal and even judicial.
Asymmetric Private Set Intersection with Applications to Contact Tracing and Private Vertical Federated Machine Learning
We present a multi-language, cross-platform, open-source library for asymmetric private set intersection (PSI) and PSI-Cardinality (PSI-C).
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