Protect privacy of your data by encrypting it. Outsource computations on the encrypted data, and decrypt at your end to view results.

Fifth part of the series CKKS explained where we see how to define rescaling

Fourth part of the series CKKS explained where we see how to define ciphertext multiplication and relinearization

Third part of the series CKKS explained where we see how to build an HE system from RLWE, implement encryption, decryption, addition and multiplication.

Second part of the series CKKS explained where we see how to implement CKKS encoder and decoder.

First part of the series CKKS explained where we see how to implement a vanilla encoder and decoder.

This post is part of our Privacy-Preserving Data Science, Explained series.

This post introduces the Paillier cryptosystem, which is a partial homomorphic encryption scheme. In a subsequent post we’ll see how this can be used as the basis for a private set intersection protocol.

In this blog, Sadegh Riazi explains Microsoft's Project HEAX. One of the main obstacles in leveraging Fully Homomorphic Encryption at large-

In this blog series, we’ll explain common topics in privacy-preserving data science, from a single sentence to code examples. We hope these posts serve as a useful resource for you to figure out the best techniques for your organization.

This post is part of our Privacy-Preserving Data Science, Explained series. Private set intersection (PSI) is a powerful cryptographic techn

This blog post aims at explaining the basic mathematical concepts behind most of today's homomorphic encryption schemes, and then build upon this to implement our own scheme (similar to BFV) from scratch using Python.

In this post we showcase a new tensor type that leverages the CKKS homomorphic encryption scheme implemented on the SEAL Microsoft library to evaluate tensor operations on encrypted data.