Privacy-preserving artificial intelligence: training on encrypted data
Privacy solutions to train Machine Learning models
Source: techradar.com
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Shiba Inu raises US$12 mln for blockchain expansion
Crypto venture capitalists back Shiba Inu's new blockchain project with a $12 million investment.
Source: yahoo.com
Shiba Inu Brings Privacy To SHIB Holders Through New Encryption Standards
The development team behind Dogecoin spinoff Shiba Inu has introduced a new tool for enhancing user privacy in the SHIB and Web 3 ecosystems. The innovation,…
Source: biztoc.com
Serverless Security: Forging Resilient Defenses In A Dynamic Landscape
Zoom in on traditional and novel ways to secure serverless computing, a growingly popular cloud infrastructure model for providing backend services on demand.
Source: forbes.com
"HeFUN: Homomorphic Encryption for Unconstrained Secure Neural Network " by Duy Tung Khanh Nguyen, Dung Hoang Duong et al.
Homomorphic encryption (HE) has emerged as a pivotal technology for secure neural network inference (SNNI), offering privacy-preserving computations on encrypted data. Despite active developments in this field, HE-based SNNI frameworks are impeded by three inherent limitations. Firstly, they cannot evaluate non-linear functions such as (Formula presented.), the most widely adopted activation function in neural networks. Secondly, the permitted number of homomorphic operations on ciphertexts is bounded, consequently limiting the depth of neural networks that can be evaluated. Thirdly, the compu...
Source: uow.edu.au