Open Source Homomorphic Cryptography
Written by Mike James   
Wednesday, 01 May 2013

How fast things move from theoretical, through experimental to implementation. It was only recently that  a semi-practical scheme for homomorphic encryption was invented and we already have an open source implementation in C++.

 

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Homomorphic encryption is a very desirable goal. Suppose you want to add two numbers that are stored in an encrypted file. Traditionally the only way to do it was to decrypt the file, add the two numbers and then re-encrypt the file. Of course, to do the addition you had to have access to the entire contents. This also meant that other people could access it while it was stored as plain text. 

There are lots of of situations where it would be good if the data could be stored in encrypted form, say in the cloud, and still operated on without having to decrypt it.  This is the goal of fully homomorphic encryption.

To be fully homomorphic the code has to be such that a third party can add and multiply numbers that it contains without needing to decrypt it. This may sound like magic but a fully homomorphic scheme was invented in 2009 by Craig Gentry (thesis: A Fully homomorphic Encryption Scheme). 

This was a step in the right direction but the problem was that it is very inefficient and computationally intensive. Since then there have been a number of improvements that make the scheme practical in the right situations. At the end of 2009 Marten van Dijk, Craig Gentry, Shai Halevi and Vinod Vaikuntanathan presented a simplified fully homomorphic system: Fully Homomorphic Encryption over the Integers - the BGV system. 

Now Victor Shoup and Shai Halevi of the IBM T J Watson Research Center have released an open source (GPL)  C++ library, HElib as a Github project. The code is said to incorporate many optimizations to make the encryption run faster:

HElib is a software library that implements homomorphic encryption (HE). Currently available is an implementation of the Brakerski-Gentry-Vaikuntanathan (BGV) scheme, along with many optimizations to make homomorphic evaluation runs faster, focusing mostly on effective use of the Smart-Vercauteren ciphertext packing techniques and the Gentry-Halevi-Smart optimizations.

Visit Github to download the code and contribute to the project. There is a lot of documentation to help you get started.

Homomorphic encryption has the potential to revolutionize security by allowing operations on data without the need to decrypt it. 

 

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