Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
End-to-end privacy preserving deep learning on multi-institutional medical imaging
Using large, multi-national datasets for high-performance medical imaging AI systems
requires innovation in privacy-preserving machine learning so models can train on sensitive …
requires innovation in privacy-preserving machine learning so models can train on sensitive …
On protecting the data privacy of large language models (llms): A survey
Large language models (LLMs) are complex artificial intelligence systems capable of
understanding, generating and translating human language. They learn language patterns …
understanding, generating and translating human language. They learn language patterns …
Survey on cyberspace security
Along with the rapid development and wide application of information technology, human
society has entered the information era. In this era, people live and work in cyberspace …
society has entered the information era. In this era, people live and work in cyberspace …
Efficient pseudorandom correlation generators: Silent OT extension and more
Secure multiparty computation (MPC) often relies on correlated randomness for better
efficiency and simplicity. This is particularly useful for MPC with no honest majority, where …
efficiency and simplicity. This is particularly useful for MPC with no honest majority, where …
Prio: Private, robust, and scalable computation of aggregate statistics
This paper presents Prio, a privacy-preserving system for the collection of aggregate
statistics. Each Prio client holds a private data value (eg, its current location), and a small set …
statistics. Each Prio client holds a private data value (eg, its current location), and a small set …
Wolverine: Fast, scalable, and communication-efficient zero-knowledge proofs for boolean and arithmetic circuits
Efficient zero-knowledge (ZK) proofs for arbitrary boolean or arithmetic circuits have recently
attracted much attention. Existing solutions suffer from either significant prover overhead (ie …
attracted much attention. Existing solutions suffer from either significant prover overhead (ie …
Sigma: Secure gpt inference with function secret sharing
Abstract Secure 2-party computation (2PC) enables secure inference that offers protection
for both proprietary machine learning (ML) models and sensitive inputs to them. However …
for both proprietary machine learning (ML) models and sensitive inputs to them. However …
Function secret sharing: Improvements and extensions
Function Secret Sharing (FSS), introduced by Boyle et al.(Eurocrypt 2015), provides a way
for additively secret-sharing a function from a given function family F. More concretely, an m …
for additively secret-sharing a function from a given function family F. More concretely, an m …
Piranha: A {GPU} platform for secure computation
Secure multi-party computation (MPC) is an essential tool for privacy-preserving machine
learning (ML). However, secure training of large-scale ML models currently requires a …
learning (ML). However, secure training of large-scale ML models currently requires a …
Threshold cryptosystems from threshold fully homomorphic encryption
We develop a general approach to adding a threshold functionality to a large class of (non-
threshold) cryptographic schemes. A threshold functionality enables a secret key to be split …
threshold) cryptographic schemes. A threshold functionality enables a secret key to be split …