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Build Status

This library is deprecated, please see Krypto for the new implementation

fhe-core

Libraries for fully homomorphic encryption.

Overview

These are our core client side cryptography classes in Java. The following is included:

  • EnhancedBitMatrix, an alternate to the COLT bit matrix implementing commong linear operations over GF(2).

  • Monomial, an extension of the COLT BitVector representation of an individual monomial term over GF(2), such as x1x3x4. For a monomial of length n, each bit 0 <= i < n represents the presence of xi in the monomial. This implementations extends the CERN bitvector class.

  • PolynomialFunctionRepresentationGF2, a representation of a vectorial polynomial function over GF(2). Also contains Jackson serialization for marshalling the object as JSON.

  • PolynomialFunctionGF2, an extendsion of PolynomialFunctionRepresentationGF2, contains the logic for evaluating, composing, adding, and producting polynomial functions over GF(2).

  • CompoundPolynomialFunctionGF2, enables composing functions together without having to evaluate the function composition directly. It maintains a chain of functions and evaluation feeds through the chain.

  • BinaryPolynomialFunction and PolynomialFunctionJoiner enable combining the output of two functions using a third function. These functions cannot be composed int the normal sense, but can be used with CompoundPolynomialFunctionGF2. Additionally, BinaryPolynomialFunction and PolynomialFunctionJoiner can be used to combine CompoundPolynomialFunctionGF2 instances.

  • PrivateKey contains the logic for generating private keys and encrypting other polynomial functions efficiently, as compose is a very expensive operations.

  • PublicKey contains the logic for generating a possible public key for a given private key. Also contains logic for generating ciphertexts from plaintext bytes.

  • PolynomialFunctions contains static factory methods for generating common functions like XOR, AND, LSH, and RSH

Getting Started

Clone the project and build it. This will also run unit tests to make sure nothing is broken.

> git clone https://github.com/kryptnostic/fhe-core
> ./gradlew build

Setup for your IDE of choice:

> ./gradlew eclipse

Alternatively, if you like IntelliJ:

> ./gradlew idea	

Also, to run tests in parallel

> ./gradlew build -PmaxParallelForks=8

Enjoy!

Usage

###Key Generation

int ciphertextLength = 128 ,
	plaintextLength  = 64; 
		
PrivateKey privateKey = new PrivateKey( ciphertextLength , plaintextLength );
PublicKey publicKey   = new PublicKey( privateKey );

####Usage Notes

BitVector's internal representation is a long[] array and we've taken an implementation dependency on that internal representation. Use lengths that are multiple of 64 bits, i.e 8 byte longs.

###Encryption and Decryption

####Raw

byte[] plaintext  = "This is a test plaintext.".getBytes();
byte[] ciphertext = publicKey.encrypt( ciphertext );
	
String decryptedText = new String( privateKey.decrypt( ciphertext ) );

####Enveloped

byte[] plaintext  = "This is a test plaintext.".getBytes();
Ciphertext ciphertext = publicKey.encryptIntoEnvelope( ciphertext );

String decryptedText = new String( privateKey.decryptFromEnvelope( ciphertext ) ); 

####Usage Notes Raw encryption automatically pads on encryption, as required by the underlying implementation. Currently the default and only implemented padding scheme is zero padding. This padding is not removed when doing raw decryption.

When you encrypt enveloped data it also encrypts the length of the data and keeps it in the envelope. This enables things like string concatenation and automatically recovering the original bytestream exactly.

###Homomorphic Operations

In order to do homomorphic operations you first have to represent the desired function a vector function over GF(2). We've include examples for homomorphic xor and homomorphic and.

The example for the homomorphic and below is taken straight from the unit tests.

    SimplePolynomialFunction xor = PolynomialFunctions.XOR( 64 );
    SimplePolynomialFunction homomorphicXor = privKey.computeHomomorphicFunction( xor );
    
    BitVector v = BitUtils.randomBitVector( 64 );
    BitVector vConcatR = new BitVector( new long[] { 
            v.elements()[ 0 ] ,
            r.nextLong() } ,  
            128 );
    
    BitVector cv = pubKey.getEncrypter().apply( vConcatR );
    BitVector hResult = privKey.getDecryptor().apply( homomorphicXor.apply( cv ) );
    BitVector result = xor.apply( v );
    
    Assert.assertEquals( hResult, result );

The example for homomorphic and below is taken straight from the unit tests. Generating the representation of the homomorphic AND can take over a minute on a Core i7 2.3 GHz Macbook Pro.

	SimplePolynomialFunction and = PolynomialFunctions.AND( 64 );
    long start = System.currentTimeMillis();
    SimplePolynomialFunction homomorphicAnd = privKey.computeHomomorphicFunction( and );
    long stop = System.currentTimeMillis();
    logger.info( "Homomorphic AND generation took {} ms" , stop - start );
    
    BitVector v = BitUtils.randomBitVector( 64 );
    BitVector vConcatR = new BitVector( new long[] { 
            v.elements()[ 0 ] ,
            r.nextLong() } ,  
            128 );
    
    BitVector cv = pubKey.getEncrypter().apply( vConcatR );
    start = System.currentTimeMillis();
    BitVector hResult = privKey.getDecryptor().apply( homomorphicAnd.apply( cv ) );
    stop = System.currentTimeMillis();
    logger.info( "Homomorphic AND evaluation took {} ms" , stop - start );
    BitVector result = and.apply( v );
    
    Assert.assertEquals( hResult, result );

####Usage

See src/test/java/com/kryptnostic/multivariate/test/HomomorphicFunctionsTests.java. Notes that this evaluates the homomorphic circuits in a unary closed fashion. It XORs the 32 lower bits with the 32 higher bits. We are working on binary implementations, as well as efficient implementations for AND ( which requires some algebriac tricks to reduce ~ 8 XORs ), left shift, right shift, and negation. Once these are released they form a complete set of operators allowing any boolean circuit to be evaluated homomorphically by composing the circuits.

Not Production Ready

This code isn't production ready. As we're moving very quickly to get this out so other could play with it, we took some shortcuts, which we will be remedying. A few of our "anti-patterns":

  • Rolling our own crypto

  • Rolling our own numerics. Couldn't find any GF(2) numerics and we'd like to contribute our extensions back to COLT once the implementations are cleaner.

  • Not using a cryptographically secure PRNG. We are planning on moving to BouncyCastle ASAP.

  • Current monomial count in randomized polynomial function generating code is set low. The more monomials and the higher the order of the monomials the longer operations take. This means running unit tests can take 20 seconds instead of 2 seconds. We're planning on refactoring these classes, so we can control aggressiveness of random polynomial function generation so unit tests don't take forever to run.

  • Not every function has unit tests, but we have fairly decent coverage on the most important functions.

Contributing

Our contributor agreement is currently using the Harmony template. If you'd like to contribute and find this agreement too restrictive please reach out to us on twitter @kryptnostic or send us an e-mail at [email protected]. Our main goal with the contributor agreement is to leave ourselves the freedom to re-license as Apache 2.0 in the future and to continue using the code ourselves as part of the backend service we are building.

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