Machine learning for healthcare wearable devices: the big picture
Using artificial intelligence and machine learning techniques in healthcare applications has
been actively researched over the last few years. It holds promising opportunities as it is …
been actively researched over the last few years. It holds promising opportunities as it is …
Homomorphic encryption for machine learning in medicine and bioinformatics
Machine learning and statistical techniques are powerful tools for analyzing large amounts
of medical and genomic data. On the other hand, ethical concerns and privacy regulations …
of medical and genomic data. On the other hand, ethical concerns and privacy regulations …
Efficient multi-key homomorphic encryption with packed ciphertexts with application to oblivious neural network inference
Homomorphic Encryption (HE) is a cryptosystem which supports computation on encrypted
data. Ló pez-Alt et al.(STOC 2012) proposed a generalized notion of HE, called Multi-Key …
data. Ló pez-Alt et al.(STOC 2012) proposed a generalized notion of HE, called Multi-Key …
A guide to fully homomorphic encryption
Fully homomorphic encryption (FHE) has been dubbed the holy grail of cryptography, an
elusive goal which could solve the IT world's problems of security and trust. Research in the …
elusive goal which could solve the IT world's problems of security and trust. Research in the …
Improved bootstrapping for approximate homomorphic encryption
Since Cheon et al. introduced a homomorphic encryption scheme for approximate arithmetic
(Asiacrypt'17), it has been recognized as suitable for important real-life usecases of …
(Asiacrypt'17), it has been recognized as suitable for important real-life usecases of …
Secure large-scale genome-wide association studies using homomorphic encryption
M Blatt, A Gusev, Y Polyakov… - Proceedings of the …, 2020 - National Acad Sciences
Genome-wide association studies (GWASs) seek to identify genetic variants associated with
a trait, and have been a powerful approach for understanding complex diseases. A critical …
a trait, and have been a powerful approach for understanding complex diseases. A critical …
Functional genomics data: privacy risk assessment and technological mitigation
The generation of functional genomics data by next-generation sequencing has increased
greatly in the past decade. Broad sharing of these data is essential for research …
greatly in the past decade. Broad sharing of these data is essential for research …
When homomorphic encryption marries secret sharing: Secure large-scale sparse logistic regression and applications in risk control
Logistic Regression (LR) is the most widely used machine learning model in industry for its
efficiency, robustness, and interpretability. Due to the problem of data isolation and the …
efficiency, robustness, and interpretability. Due to the problem of data isolation and the …
Scalable privacy-preserving distributed learning
D Froelicher, JR Troncoso-Pastoriza, A Pyrgelis… - arXiv preprint arXiv …, 2020 - arxiv.org
In this paper, we address the problem of privacy-preserving distributed learning and the
evaluation of machine-learning models by analyzing it in the widespread MapReduce …
evaluation of machine-learning models by analyzing it in the widespread MapReduce …
Veritas: Plaintext encoders for practical verifiable homomorphic encryption
S Chatel, C Knabenhans, A Pyrgelis… - Proceedings of the …, 2024 - dl.acm.org
Homomorphic encryption has become a practical solution for protecting the privacy of
computations on sensitive data. However, existing homomorphic encryption pipelines do not …
computations on sensitive data. However, existing homomorphic encryption pipelines do not …