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IEEE Transactions on Information Forensics and Security

Fully Homomorphic Encryption Using Hidden Ideal Lattice

Thomas Plantard, Willy Susilo, Zhenfei Zhang

Published Nov 19, 2013• 43 citations
Publisher

Abstract

All the existing fully homomorphic encryption schemes are based on three different problems, namely the bounded distance decoding problem over ideal lattice, the approximate greatest common divisor problem over integers, and the learning with error problem. In this paper, we unify the first two families of problems by introducing a new class of problems, which can be reduced from both problems. Based on this new problem, namely the bounded distance decoding over hidden ideal lattice, we present a new fully homomorphic encryption scheme. Since it is a combination of the two problems to some extent, the performance of our scheme lies between the ideal lattice based schemes and the integer based schemes. Furthermore, we also show a lower bound and upper bound of the problem that our scheme is based on. Assuming this security conjecture holds, we can incorporate smaller parameters, which will result in a scheme that is more efficient than both lattice based and integer based schemes. Hence, our scheme makes a perfect alternative to the state-of-art ring learning with error based schemes.

DOI
10.1109/tifs.2013.2287732

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•Jan 1, 2012•1,180 citations
All the existing fully homomorphic encryption schemes are based on three different problems, namely the bounded distance decoding problem over ideal lattice, the approximate greatest common divisor problem over integers, and the learning with error problem. In this paper, we unify the first two families of problems by introducing a new class of problems, which can be reduced from both problems. Based on this new problem, namely the bounded distance decoding over hidden ideal lattice, we present a new fully homomorphic encryption scheme. Since it is a combination of the two problems to some extent, the performance of our scheme lies between the ideal lattice based schemes and the integer based schemes. Furthermore, we also show a lower bound and upper bound of the problem that our scheme is based on. Assuming this security conjecture holds, we can incorporate smaller parameters, which will result in a scheme that is more efficient than both lattice based and integer based schemes. Hence, our scheme makes a perfect alternative to the state-of-art ring learning with error based schemes.
Abstract Data can be stored and processed in an encrypted format using fully homomorphic encryption, which makes cloud computing provider can process data well without even knowing data information. However, most existing homomorphic encryption schemes based on ring learning with errors, focus on the special classes of rings, such as power-of-two cyclotomic rings, which significantly limits its application efficiency in cloud computing. Therefore, in this letter, to solve this problem above, an efficient fully homomorphic encryption scheme is proposed based on ring learning with errors in arbitrary cyclotomic rings. Particularly, a “somewhat homomorphic encryption” scheme is firstly proposed based on ring learning with errors. A novel fully homomorphic encryption scheme is further presented using key-switching. With theoretical and experimental verification, the proposed scheme has advantage of high efficiency of encryption and decryption. The security of our scheme strictly reduces to hardness of decision ring learning with errors problem in the random oracle model.
Abstract: In this paper, we first introduce a new concept of approximate lattice problem (ALP), which is an extension of learning with errors (LWE). Next, we propose two ALP-based public key encryption schemes. Then, we construct two new fully homomorphic encryption scheme (FHE) based on respectively approximate principal ideal lattice problem with related modulus (APIP-RM) and approximate lattice problem with related modulus (ALP-RM). Moreover, we also extend our ALP-RM-based FHE to the ALP problem with unrelated modulus (ALP-UM). Our work is different from previous works in three aspects: (1) We extend the LWE problem to the ALP problem. This ALP problem is similar to the closest vector problem in lattice. We believe that this problem is independent of interest. (2) We construct a new FHE by using a re-randomizing method, which is different from the squashing decryption in previous works. (3) The expansion rate is merely O(k) with k a security parameter in Our FHE, which can be improved to O(logk) by using dimension reduction [BV11], whereas all previous schemes are at least O(k*logk) [BV11, Gen11, LNV11]. Our method can also decrease a factor k of the expansion rate in their schemes.
In this paper, we first introduce a new concept of approximate lattice problem (ALP), which is an extension of learning with errors (LWE). Next, we propose two ALP-based public key encryption schemes. Then, we construct two new fully homomorphic encryption scheme (FHE) based on respectively approximate principal ideal lattice problem with related modulus (APIP-RM) and approximate lattice problem with related modulus (ALP-RM). Moreover, we also extend our ALP-RM-based FHE to the ALP problem with unrelated modulus (ALP-UM). Our work is different from previous works in three aspects: (1) We extend the LWE problem to the ALP problem. This ALP problem is similar to the closest vector problem in lattice. We believe that this problem is independent of interest. (2) We construct a new FHE by using a re-randomizing method, which is different from the squashing decryption in previous works. (3) The expansion rate is merely O(k) with k a security parameter in Our FHE, which can be improved to O(logk) by using dimension reduction [BV11], whereas all previous schemes are at least O(k*logk) [BV11, Gen11, LNV11]. Our method can also decrease a factor k of the expansion rate in their schemes.
Abstract The security of most early fully homomorphic encryption schemes was based on the hardness of the Learning with Errors (LWE) problem. These schemes were inefficient in terms of per gate computations and public‐key size. More efficient schemes were later developed based on the hardness of the Ring‐LWE (RLWE) problem. While the hardness of the LWE problem is based on the hardness of the approximate shortest vector problem (GapSVP γ ) over regular lattices, the hardness of the RLWE problem is based on the hardness of the approximate shortest vector problem over ideal lattices. As of now, it has not been proved that the (GapSVP γ ) problem over ideal lattices is as difficult as the corresponding problem over regular lattices. In this work, the authors propose a multi‐bit levelled fully homomorphic encryption scheme using multivariate polynomial evaluations whose security depends on the hardness of the LWE problem. In terms of per gate computation cost, this scheme is more efficient than existing LWE‐based schemes. Further, for an appropriate choice of parameters, the per computation cost for homomorphic multiplication can be made asymptotically comparable to RLWE‐based schemes in a parallel computing environment. For homomorphic multiplication, the scheme uses a polynomial‐based technique that does not require relinearization (and key switching).
The efficiency of fully homomorphic encryption is a big question at present. To improve efficiency of fully homomorphic encryption, we use the technique of packed ciphertext to construct a multi-bit fully homomorphic encryption based on Learning with Errors problem. Our scheme has a short public key. Since our fully homomorphic encryption scheme builds on the basic encryption scheme that choose Learning with Errors samples from Gaussian distribution and add Gaussian error to it, which result in that the number of Learning with Errors samples decrease from 2nlogq to n+1. We prove that our fully homomorphic encryption scheme is feasible and its security relies on the hardness of Learning with Errors problem. In addition we adapt the optimization for the process of key switching from GHS13 and formal this new process of key switching for multi-bit fully homomorphic encryption. At last, we analyze the concert parameters and compare these parameters between our scheme and GHS13 scheme. The data show that our scheme has public key smaller by a factor of about logq than it in GHS13 scheme.
Abstract. In this paper we port Brakerski’s fully homomorphic scheme based on the Learning With Errors (LWE) problem to the ring-LWE setting. We introduce two optimised versions of relinearisation that not only result in a smaller relinearisation key, but also faster computations. We provide a detailed, but simple analysis of the various homomorphic operations, such as multiplication, relinearisation and bootstrapping, and derive tight worst case bounds on the noise caused by these operations. The analysis of the bootstrapping step is greatly simplified by using a modulus switching trick. Finally, we derive concrete parameters for which the scheme provides a given level of security and becomes fully homomorphic. 1