CryptoDL

由EHesamifard著作·2017·被引用379次—Inthispaper,wedevelopnewtechniquestoadoptdeepneuralnetworkswithinthepracticallimitationofcurrenthomomorphicencryptionschemes ...,ThisprojectaimstoprovideDeepLearningwithaprivacypreservingcomputationbackend.Theprivacypreservingcomputationisbasedonhomomorphicencryption ...,CryptoDL:TowardsDeepLearningoverEncryptedData.EhsanHesamifard,HassanTakabi,MehdiGhasemi.2...

參考資訊如下
CryptoDL

由 E Hesamifard 著作 · 2017 · 被引用 379 次 — In this paper, we develop new techniques to adopt deep neural networks within the practical limitation of current homomorphic encryption schemes ...

inspire-labCryptoDL: Privacy

This project aims to provide Deep Learning with a privacy preserving computation backend. The privacy preserving computation is based on homomorphic encryption ...

Ehsan Hesamifard

CryptoDL: Towards Deep Learning over Encrypted Data. Ehsan Hesamifard, Hassan Takabi, Mehdi Ghasemi. 2016 Annual Computer Security Applications Conference ...

Ehsan Hesamifard

Cryptodl: Deep neural networks over encrypted data. E Hesamifard, H Takabi, M Ghasemi. arXiv preprint arXiv:1711.05189, 2017. 378 ...

CryptoDL

由 OL Usman 著作 · 2020 · 被引用 30 次 — CryptoDL: Predicting Dyslexia Biomarkers from Encrypted Neuroimaging Dataset Using Energy-Efficient Residue Number System and Deep Convolutional ...

(PDF) CryptoDL

2017年11月14日 — We demonstrate applicability of the proposed CryptoDL using a large number of datasets and evaluate its performance. The empirical results show ...