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Found 7 papers, 2 papers with code
EVA: An Encrypted Vector Arithmetic Language and Compiler for Efficient Homomorphic Computation
We believe that EVA would enable a wider adoption of FHE by making it easier to develop FHE applications and domain-specific FHE compilers.
Planting and Mitigating Memorized Content in Predictive-Text Language Models
Language models are widely deployed to provide automatic text completion services in user products.
CHET: Compiler and Runtime for Homomorphic Evaluation of Tensor Programs
Just as the hardware ISA interface enabled hardware advances to proceed independent of software advances in the compiler and language runtimes, HISA decouples compiler optimizations and runtimes for supporting FHE applications from advancements in the underlying FHE schemes.
PrivFT: Private and Fast Text Classification with Homomorphic Encryption
In the second part, we show how to train a model using fully encrypted data to generate an encrypted model.
HEAX: An Architecture for Computing on Encrypted Data
Building on top of NTT engine, we design a novel architecture for computation on homomorphically encrypted data.
Trustworthy AI Inference Systems: An Industry Research View
Additionally, such systems should also use Privacy-Enhancing Technologies (PETs) to protect customers' data at any time.
Exploring Design and Governance Challenges in the Development of Privacy-Preserving Computation
Homomorphic encryption, secure multi-party computation, and differential privacy are part of an emerging class of Privacy Enhancing Technologies which share a common promise: to preserve privacy whilst also obtaining the benefits of computational analysis.
Human-Computer Interaction
