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rog3rsm1th.github.io | ||
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blog.openmined.org
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| | | | | From the math and the hard problem behind most of today's homomorphic encryption scheme to implementing your own in python. | |
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www.ayoub-benaissa.com
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| | | | | This is the first of a series of blog posts about the use of homomorphic encryption for deep learning. Here I introduce the basics and terminology as well as link to external resources that might help with a deeper understanding of the topic. | |
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kndrck.co
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| | | | | Motivation RSA (Rivest-Shamir-Adleman) is one of the first public-key cryptosystems and is widely used for secure data transmission. In such a cryptosystem, the encryption key is public and is different from the decryption key which is kept secret. If I wanted to comprehend zero knowledge proofs, then understanding the grand-daddy of public-key cryptosystems is a must. Background Maths Exponential Rules 1 $$ \begin{align} \label{eq:exponent_rule} g^{a-b} &= \dfrac{g^a}{g^b} \newline g^{a+b} &= g^a g^b \n... | |
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www.jeremykun.com
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| | | This article was written by my colleague, Cathie Yun. Cathie is an applied cryptographer and security engineer, currently working with me to make fully homomorphic encryption a reality at Google. She's also done a lot of cool stuff with zero knowledge proofs. In previous articles, we've discussed techniques used in Fully Homomorphic Encryption (FHE) schemes. The basis for many FHE schemes, as well as other privacy-preserving protocols, is the Learning With Errors (LWE) problem. | ||
