Ring learning with errors: Difference between revisions

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{{technical|date=September 2015}}

'''Ring Learninglearning with Errorserrors''' ('''RLWE''') is a [[computational problem]] which serves as the foundation of new cryptographic [[algorithm]]s designed to protect against [[cryptanalysis]] by [[quantum computers]] and also to provide the basis for [[homomorphic encryption]]. RLWE is more properly called Learning with Errors over Rings and is simply the larger [[Learninglearning with errors|Learning with Errors]] (LWE) problem specialized to [[polynomial rings]] over finite fields.<ref name=":0" /> Because of the presumed difficulty of solving the RLWE problem even on a quantum computer, RLWE based cryptography may form the fundamental base for [[Publicpublic-key cryptography|public key cryptography]] in the future just as the [[integer factorization]] and [[discrete logarithm]] problem have served as the base for public key cryptography since the early 1980s.<ref name=":2">{{Cite book|title = Lattice Cryptography for the Internet|url = http://link.springer.com/chapter/10.1007/978-3-319-11659-4_12|publisher = Springer International Publishing|isbn = 978-3-319-11658-7|pages = 197–219|series = Lecture Notes in Computer Science|first = Chris|last = Peikert|editor-first = Michele|editor-last = Mosca}}</ref> An important feature of basing cryptography on the Ringring Learninglearning with Errorserrors problem is the fact that the solution to the RLWE problem may be reducible to the [[NP-hard|NP-Hard]] [[Shortest vector problem|Shortest Vector Problem]] (SVP) in a Lattice.<ref name=":0" />

== Background ==

The security of modern cryptography, in particular [[Public-key cryptography|Public Key Cryptography]], is based on the assumed intractability of solving certain computational problems if the size of the problem is large enough and the instance of the problem to be solved is chosen randomly. The classic example that has been used since the 1970s is the [[integer factorization]] problem. It is believed that it is computationally intractable to factor the product of two prime numbers if those prime numbers are large enough and chosen at random. As of 2015 research has led to the factorization of the product of two 384-bit primes but not the product of two 512-bit primes. [[Integer factorization]] forms the basis of the widely used [[RSA (cryptosystem)|RSA]] cryptographic algorithm.

The Ringring Learninglearning with Errorserrors (RLWE) problem is built on the arithmetic of [[polynomials]] with coefficients from a [[finite field]].<ref name=":0" /> A typical polynomial <math display="inline">a(x)</math> is expressed as:

:<math>a(x) = a_0 + a_1x + a_2x^2 + \ldots + a_{n-2}x^{n-2} + a_{n-1}x^{n-1}</math>

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== The RLWE Problem ==

The RLWE problem can be stated in two different ways: a "search" version and a "decision" version. Both begin with the same construction. Let

* <math>a_i(x)</math> be a set of random but '''known''' polynomials from <math>\mathbf{Z}_q[x]/\Phi(x)</math> with coefficients from all of <math>\mathbf{F}_q</math>.

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== Security Reduction ==

In cases where the polynomial <math>\Phi(x)</math> is a [[cyclotomic polynomial]], the difficulty of solving the search version of RLWE problem is equivalent to finding a short vector (but not necessarily the shortest) vector in an ideal lattice formed from elements of <math>\mathbf{Z}[x]/\Phi(x)</math> represented as integer vectors.<ref name=":0">{{Cite journal|title = On Ideal Lattices and Learning with Errors Over Rings|url = http://eprint.iacr.org/2012/230|date = 2012|first = Vadim|last = Lyubashevsky|first2 = Chris|last2 = Peikert|first3 = Oded|last3 = Regev}}</ref> This problem is commonly known as the [[Shortest vector problem|Approximate Shortest Vector Problem (α-SVP)]] and it is the problem of finding a vector shorter than α times the shortest vector. The authors of the proof for this equivalence write:

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In that quote, The ring <math>\mathbf{R}</math> is <math>\mathbf{Z}[x]/\Phi(x)</math> and the ring <math>\mathbf{R}_q</math> is <math>\mathbf{Z}_q[x]/\Phi(x)</math>.

The α-SVP in regular lattices is known to be [[NP-hard]] due to work by Daniele Micciancio in 2001, although not for values of α required for a reduction to general Learninglearning Withwith Errorserrors problem.<ref name=":1">{{Cite journal|title = The Shortest Vector in a Lattice is Hard to Approximate to within Some Constant|url = http://epubs.siam.org/doi/abs/10.1137/S0097539700373039|journal = SIAM Journal on Computing|date = January 1, 2001|issn = 0097-5397|pages = 2008–2035|volume = 30|issue = 6|doi = 10.1137/S0097539700373039|first = D.|last = Micciancio}}</ref> However, there is not yet a proof to show that the difficulty of the α-SVP for ideal lattices is equivalent to the average α-SVP. Rather we have a proof that if there are ''any'' α-SVP instances that are hard to solve in ideal lattices then the RLWE Problem will be hard in random instances.<ref name=":0" />

Regarding the difficulty of Shortest Vector Problems in Ideal Lattices, researcher Michael Schneider writes, ''"So far there is no SVP algorithm making use of the special structure of ideal lattices. It is widely believed that solving SVP (and all other lattice problems) in ideal lattices is as hard as in regular lattices."''<ref>{{Cite journal|title = Sieving for Shortest Vectors in Ideal Lattices|url = http://eprint.iacr.org/2011/458|date = 2011|first = Michael|last = Schneider}}</ref> The difficulty of these problems on regular lattices is provably [[NP-hard]].<ref name=":1" /> There are, however, a minority of researchers who do not believe that ideal lattices share the same security properties as regular lattices.<ref>{{Cite web|title = cr.yp.to: 2014.02.13: A subfield-logarithm attack against ideal lattices|url = http://blog.cr.yp.to/20140213-ideal.html|website = blog.cr.yp.to|accessdate = 2015-07-03}}</ref>

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== RLWE Cryptography ==

A major advantage that RLWE based cryptography has over the original [[Learninglearning with errors|Learning With Errors]] (LWE) based cryptography is found in the size of the public and private keys. RLWE keys are roughly the square root of keys in LWE.<ref name=":0" /> For 128 bits of security an RLWE cryptographic algorithm would use public keys around 7000 bits in length.<ref>{{Cite journal|title = A Practical Key Exchange for the Internet using Lattice Cryptography|url = http://eprint.iacr.org/2015/138|date = 2015|first = Vikram|last = Singh}}</ref> The corresponding LWE scheme would require public keys of 49 million bits for the same level of security.<ref name=":0" />{{failed verification|date=August 2016}} On the other hand, RLWE keys are larger than the keys sizes for currently used public key algorithms like RSA and Elliptic Curve Diffie-Hellman which require public [[key size]]s of 3072 bits and 256 bits, respectively, to achieve a 128-bit level of security. From a computational standpoint, however, RLWE algorithms have been shown to be the equal of or better than existing public key systems.<ref>{{Cite journal|title = Efficient Software Implementation of Ring-LWE Encryption|url = http://eprint.iacr.org/2014/725|date = 2014|first = Ruan de Clercq, Sujoy Sinha Roy, Frederik Vercauteren, Ingrid|last = Verbauwhede}}</ref>

A major advantage that RLWE based cryptography has over the original [[Learning with errors|Learning With Errors]] (LWE) based cryptography is found in the size of the public and private keys. RLWE keys are roughly the square root of keys in LWE.<ref name=":0" /> For 128 bits of security an RLWE cryptographic algorithm would use public keys around 7000 bits in length.<ref>{{Cite journal|title = A Practical Key Exchange for the Internet using Lattice Cryptography|url = http://eprint.iacr.org/2015/138|date = 2015|first = Vikram|last = Singh}}</ref> The corresponding LWE scheme would require public keys of 49 million bits for the same level of security.<ref name=":0" />{{failed verification|date=August 2016}} On the other hand, RLWE keys are larger than the keys sizes for currently used public key algorithms like RSA and Elliptic Curve Diffie-Hellman which require public [[key size]]s of 3072 bits and 256 bits, respectively, to achieve a 128-bit level of security. From a computational standpoint, however, RLWE algorithms have been shown to be the equal of or better than existing public key systems.<ref>{{Cite journal|title = Efficient Software Implementation of Ring-LWE Encryption|url = http://eprint.iacr.org/2014/725|date = 2014|first = Ruan de Clercq, Sujoy Sinha Roy, Frederik Vercauteren, Ingrid|last = Verbauwhede}}</ref>

Three groups of RLWE cryptographic algorithms exist:

=== [[Ring learning with errors key exchange|Ring Learning with Errors Key Exchanges]]exchanges (RLWE-KEX) ===

{{main|Ring learning with errors key exchange}}

The fundamental idea of using LWE and Ring LWE for key exchange was proposed and filed at the University of Cincinnati in 2011 by Jintai Ding. The basic idea comes from the associativity of matrix multiplications, and the errors are used to provide the security. The paper<ref>{{Cite journal|last=Ding|first=Jintai|last2=Xie|first2=Xiang|last3=Lin|first3=Xiaodong|date=2012-01-01|title=A Simple Provably Secure Key Exchange Scheme Based on the Learning with Errors Problem|url=http://eprint.iacr.org/2012/688|journal=|volume=|issue=|doi=|pmid=|access-date=|via=}}</ref> appeared in 2012 after a provisional patent application was filed in 2012.

In 2014, Peikert<ref>{{Cite journal|last=Peikert|first=Chris|date=2014-01-01|title=Lattice Cryptography for the Internet|url=http://eprint.iacr.org/2014/070|journal=|volume=|issue=|doi=|pmid=|access-date=|via=}}</ref> presented a key transport scheme following the same basic idea of Ding's, where the new idea of sending additional 1 bit signal for rounding in Ding's construction is also utilized. An RLWE version of the classic MQV variant of a Diffie-Hellman key exchange was later published by Zhang et al.<ref>{{Cite journal|title = Authenticated Key Exchange from Ideal Lattices|url = http://eprint.iacr.org/2014/589|date = 2014|first = Jiang|last = Zhang|first2 = Zhenfeng|last2 = Zhang|first3 = Jintai|last3 = Ding|first4 = Michael|last4 = Snook|first5 = Özgür|last5 = Dagdelen}}</ref> The security of both key exchanges is directly related to the problem of finding approximate short vectors in an ideal lattice.

=== [[Ring learning with errors signature|Ring Learning with Errors Signatures]] (RLWE-SIG) ===

{{main|Ring learning with errors signature}}

A RLWE version of the classic [[Feige–Fiat–Shamir identification scheme|Feige–Fiat–Shamir Identification protocol]] was created and converted to a digital signature in 2011 by Lyubashevsky.<ref>{{Cite journal|title = Lattice Signatures Without Trapdoors|url = http://eprint.iacr.org/2011/537|date = 2011|first = Vadim|last = Lyubashevsky}}</ref> The details of this signature were extended in 2012 by Gunesyu, Lyubashevsky, and Popplemann in 2012 and published in their paper "Practical Lattice Based Cryptography – A Signature Scheme for Embedded Systems."<ref>{{Cite book|title = Practical Lattice-Based Cryptography: A Signature Scheme for Embedded Systems|url = http://link.springer.com/chapter/10.1007/978-3-642-33027-8_31|publisher = Springer Berlin Heidelberg|date = 2012|isbn = 978-3-642-33026-1|pages = 530–547|series = Lecture Notes in Computer Science|first = Tim|last = Güneysu|first2 = Vadim|last2 = Lyubashevsky|first3 = Thomas|last3 = Pöppelmann|editor-first = Emmanuel|editor-last = Prouff|editor-first2 = Patrick|editor-last2 = Schaumont}}</ref> These papers laid the groundwork for a variety of recent signature algorithms some based directly on the Ringring Learninglearning with Errorserrors problem and some which are not tied to the same hard RLWE problems.<ref>{{Cite web|title = BLISS Signature Scheme|url = http://bliss.di.ens.fr/|website = bliss.di.ens.fr|accessdate = 2015-07-04}}</ref>

=== [[Homomorphic encryption|Ring Learning with Errors Homomorphic Encryption]] (RLWE-HOM) ===

=== Ring learning with errors homomorphic encryption (RLWE-HOM) ===

{{main|Homomorphic encryption}}

The purpose of [[homomorphic encryption]] is to allow the computations on sensitive data to occur on computing devices that should not be trusted with the data. These computing devices are allowed to process the ciphertext which is output from a homomorphic encryption. In 2011, Brakersky and Vaikuntanathan, published "Fully Homomorphic Encryption from Ring-LWE and Security for Key Dependent Messages" which builds a homomorphic encryption scheme directly on the RLWE problem.<ref>{{Cite book|title = Fully Homomorphic Encryption from Ring-LWE and Security for Key Dependent Messages|url = http://link.springer.com/chapter/10.1007/978-3-642-22792-9_29|publisher = Springer Berlin Heidelberg|date = 2011|isbn = 978-3-642-22791-2|pages = 505–524|series = Lecture Notes in Computer Science|first = Zvika|last = Brakerski|first2 = Vinod|last2 = Vaikuntanathan|editor-first = Phillip|editor-last = Rogaway}}</ref>

The various sets of parameters that have been proposed by different groups of researchers for Ringring Learninglearning with Errorserrors Keykey Exchangeexchange and Signaturessignatures are found at the Ringring Learninglearning with Errorserrors information site ([http://www.ringlwe.info/parameters-for-rlwe.html ringlwe.info])<ref>{{Cite web

| url = http://www.ringlwe.info/parameters-for-rlwe.html

| title = Parameters for RLWE