Difference between revisions of "BGV"

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Correctness is easy to verify, whereas we refer to the paper for details upon security.
 
Correctness is easy to verify, whereas we refer to the paper for details upon security.
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== Key switching (Dimension reduction)==
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Recall that in the above scheme, the decryption equation for a ciphertext <math> c </math> that encrypts a message <math> m </math> under the secret key <math> s</math> can be written as
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<math>m = E.Dec(params, s,c) = [[L_{c}(s)]_q]_2,</math> where <math>L_c </math> is a linear operator which depends on <math>c </math>. To be precise, the latter is just the inner product <math>L_c(s) = <c,s> </math> between two vectors in <math>R_q^2</math>.
  
 
== References ==
 
== References ==

Revision as of 13:39, 6 January 2021

In 2011, Brakerski, Gentry and Vaikuntanathan (BGV) published the paper [1] in which they introduce a new (leveled) fully homomorphic encryption (FHE) that improves performance and bases security on weaker assumptions than schemes from the previous generation.

A central conceptual contribution of this work is a new way of constructing leveled fully homomorphic encryption schemes (capable of evaluating arbitrary polynomial-size circuits), without Gentry’s bootstrapping procedure.

Until recently, the BGV scheme was considered to be the most efficient homomorphic encryption scheme when performing the same operations on multiple ciphertexts at once.

Modulus switching

@TODO

New noise management technique

@TODO

Leveled Fully Homomorphic Encryption

Most of the work done by the will focus on the construction of a leveled fully homomorphic scheme, in the sense that the parameters of the scheme depend (polynomially) on the depth of the circuits that the scheme is capable of evaluating.

Definition. We say that a family of homomorphic encryption schemes is leveled fully homomorphic if, for all , they all use the same decryption circuit, compactly evaluates all circuits of depth at most (that use some specified complete set of gates), and the computational complexity of 's algorithms is polynomial (a fixed polynomial for all ) in the security parameter , and the size of the circuit (in the case of the evaluation algorithm).

The construction: FHE without bootstrapping

The authors base the security of their scheme on the hardness of Ring-Learning with errors problems, a generalisation of the classical LWE problem.

Let be a security parameter, representing security against known attacks.

Let be a ring. For any integer , we write for the quotient .

Let be an odd modulus and a ``noise" distribution over . Let be an additional parameter of the system which is larger than .

Let us assume that the plaintext is .

  • E.Setup(): Choose a -bit modulus and choose the other parameters , and , appropriately to ensure that the scheme is based on a Ring-LWE instance that achieves security against known attacks. Let and let params = .
  • E.SecretKetGen(params): Draw . Set .
  • E.PublicKeyGen(params, sk): Recall that the secret key is . This algorithm generates a (column) vector , uniformly and a vector . The algorithm computes

. Then, set to be the matrix obtained by setting on the first column followed by the entries of . We remark that . The algorithm outputs the public key .

  • E.Enc(params, pk,m): To encrypt a message , set , sample uniformly and output the ciphertext .
  • E.Dec(params, sk, c): Output . Where denotes reduction into the range .

Correctness is easy to verify, whereas we refer to the paper for details upon security.

Key switching (Dimension reduction)

Recall that in the above scheme, the decryption equation for a ciphertext that encrypts a message under the secret key can be written as where is a linear operator which depends on . To be precise, the latter is just the inner product between two vectors in .

References

  1. Z. Brakerski, C. Gentry, and V. Vaikuntanathan. 2014. (Leveled) Fully Homomorphic Encryption without Bootstrapping. ACM Trans. Comput. Theory 6, 3, Article 13 (July 2014), 36 pages. DOI:https://doi.org/10.1145/2633600