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Improvements in Computing Discrete Logarithms in Finite Fields
ISSN (Print): 2476-8316 ISSN (Online): 2635-3490 Dutse Journal of Pure and Applied Sciences (DUJOPAS), Vol. 5 No. 1a June 2019 Improvements in Computing Discrete Logarithms in Finite Fields 1*Ali Maianguwa Shuaibu, 2Sunday Babuba & 3James Andrawus 1, 2,3 Department of Mathematics, Federal University Dutse, Jigawa State Email: [email protected] Abstract The discrete logarithm problem forms the basis of numerous cryptographic systems. The most efficient attack on the discrete logarithm problem in the multiplicative group of a finite field is via the index calculus. In this paper, we examined a non-generic algorithm that uses index calculus. If α is a generator × × for 퐹푝 then the discrete logarithm of 훽 ∈ 퐹푝 with respect to 훼 is also called the index of 훽 (with respect to 훼), whence the term index calculus. This algorithm depends critically on the distribution of smooth numbers (integers with small prime factors), which naturally leads to a discussion of two algorithms for factoring integers that also depend on smooth numbers: the Pollard 푝 − 1method and the elliptic curve method. In conclusion, we suggest improved elliptic curve as well as hyperelliptic curve cryptography methods as fertile ground for further research. Keywords: Elliptic curve, Index calculus, Multiplicative group, Smooth numbers Introduction 푥 It is known that the logarithm 푙표푔푏 푎 is a number x such that 푏 = 푎, for given numbers a and b. Similarly, in any group G, powers 푏푘 can be defined for all integers 푘, and 푘 the discrete logarithm푙표푔푏 푎 is an integer k such that 푏 = 푎. In number theory,푥 = 푥 푖푛푑푟푎(푚표푑 푚) is read as the index of 푎 to the base r modulo m which is equivalent to 푟 = 푎(푚표푑 푚) if r is the primitive root of m and greatest common divisor, 푔푐푑( 푎, 푚) = 1. -
The Index Calculus Method Using Non-Smooth Polynomials
MATHEMATICS OF COMPUTATION Volume 70, Number 235, Pages 1253{1264 S 0025-5718(01)01298-4 Article electronically published on March 7, 2001 THE INDEX CALCULUS METHOD USING NON-SMOOTH POLYNOMIALS THEODOULOS GAREFALAKIS AND DANIEL PANARIO Abstract. We study a generalized version of the index calculus method for n the discrete logarithm problem in Fq ,whenq = p , p is a small prime and n !1. The database consists of the logarithms of all irreducible polynomials of degree between given bounds; the original version of the algorithm uses lower bound equal to one. We show theoretically that the algorithm has the same asymptotic running time as the original version. The analysis shows that the best upper limit for the interval coincides with the one for the original version. The lower limit for the interval remains a free variable of the process. We provide experimental results that indicate practical values for that bound. We also give heuristic arguments for the running time of the Waterloo variant and of the Coppersmith method with our generalized database. 1. Introduction Let G denote a group written multiplicatively and hgi the cyclic subgroup gen- erated by g 2 G.Giveng and y 2hgi,thediscrete logarithm problem for G is to find the smallest integer x such that y = gx.Theintegerx is called the discrete logarithm of y in the base g, and is written x =logg y. The main reason for the intense current interest on the discrete logarithm prob- lem (apart from being interesting on a purely mathematical level) is that the se- curity of many public-key cryptosystems depends on the assumption that finding discrete logarithms is hard, at least for certain groups. -
Sieve Algorithms for the Discrete Logarithm in Medium Characteristic Finite Fields Laurent Grémy
Sieve algorithms for the discrete logarithm in medium characteristic finite fields Laurent Grémy To cite this version: Laurent Grémy. Sieve algorithms for the discrete logarithm in medium characteristic finite fields. Cryptography and Security [cs.CR]. Université de Lorraine, 2017. English. NNT : 2017LORR0141. tel-01647623 HAL Id: tel-01647623 https://tel.archives-ouvertes.fr/tel-01647623 Submitted on 24 Nov 2017 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. AVERTISSEMENT Ce document est le fruit d'un long travail approuvé par le jury de soutenance et mis à disposition de l'ensemble de la communauté universitaire élargie. Il est soumis à la propriété intellectuelle de l'auteur. Ceci implique une obligation de citation et de référencement lors de l’utilisation de ce document. D'autre part, toute contrefaçon, plagiat, reproduction illicite encourt une poursuite pénale. Contact : [email protected] LIENS Code de la Propriété Intellectuelle. articles L 122. 4 Code de la Propriété Intellectuelle. articles L 335.2- L 335.10 http://www.cfcopies.com/V2/leg/leg_droi.php -
Index Calculus in the Trace Zero Variety 3
INDEX CALCULUS IN THE TRACE ZERO VARIETY ELISA GORLA AND MAIKE MASSIERER Abstract. We discuss how to apply Gaudry’s index calculus algorithm for abelian varieties to solve the discrete logarithm problem in the trace zero variety of an elliptic curve. We treat in particular the practically relevant cases of field extensions of degree 3 or 5. Our theoretical analysis is compared to other algorithms present in the literature, and is complemented by results from a prototype implementation. 1. Introduction Given an elliptic curve E defined over a finite field Fq, consider the group E(Fqn ) of rational points over a field extension of prime degree n. Since E is defined over Fq, the group E(Fqn ) contains the subgroup E(Fq) of Fq-rational points of E. Moreover, it contains the subgroup Tn of − points P E(F n ) whose trace P + ϕ(P )+ ... + ϕn 1(P ) is zero, where ϕ denotes the Frobenius ∈ q homomorphism on E. The group Tn is called the trace zero subgroup of E(Fqn ), and it is the group of Fq-rational points of the trace zero variety relative to the field extension Fqn Fq. In this paper, we study the hardness of the DLP in the trace zero variety. Our| interest in this question has several motivations. First of all, supersingular trace zero varieties can achieve higher security per bit than supersingular elliptic curves, as shown by Rubin and Silverberg in [RS02, RS09] and by Avanzi and Cesena in [AC07, Ces10]. Ideally, in pairing-based proto- F∗ cols the embedding degree k is such that the DLP in Tn and in qkn have the same complexity. -
Integer Factorization and Computing Discrete Logarithms in Maple
Integer Factorization and Computing Discrete Logarithms in Maple Aaron Bradford∗, Michael Monagan∗, Colin Percival∗ [email protected], [email protected], [email protected] Department of Mathematics, Simon Fraser University, Burnaby, B.C., V5A 1S6, Canada. 1 Introduction As part of our MITACS research project at Simon Fraser University, we have investigated algorithms for integer factorization and computing discrete logarithms. We have implemented a quadratic sieve algorithm for integer factorization in Maple to replace Maple's implementation of the Morrison- Brillhart continued fraction algorithm which was done by Gaston Gonnet in the early 1980's. We have also implemented an indexed calculus algorithm for discrete logarithms in GF(q) to replace Maple's implementation of Shanks' baby-step giant-step algorithm, also done by Gaston Gonnet in the early 1980's. In this paper we describe the algorithms and our optimizations made to them. We give some details of our Maple implementations and present some initial timings. Since Maple is an interpreted language, see [7], there is room for improvement of both implementations by coding critical parts of the algorithms in C. For example, one of the bottle-necks of the indexed calculus algorithm is finding and integers which are B-smooth. Let B be a set of primes. A positive integer y is said to be B-smooth if its prime divisors are all in B. Typically B might be the first 200 primes and y might be a 50 bit integer. ∗This work was supported by the MITACS NCE of Canada. 1 2 Integer Factorization Starting from some very simple instructions | \make integer factorization faster in Maple" | we have implemented the Quadratic Sieve factoring al- gorithm in a combination of Maple and C (which is accessed via Maple's capabilities for external linking). -
The Number Field Sieve for Discrete Logarithms
The Number Field Sieve for Discrete Logarithms Henrik Røst Haarberg Master of Science Submission date: June 2016 Supervisor: Kristian Gjøsteen, MATH Norwegian University of Science and Technology Department of Mathematical Sciences Abstract We present two general number field sieve algorithms solving the discrete logarithm problem in finite fields. The first algorithm pre- sented deals with discrete logarithms in prime fields Fp, while the second considers prime power fields Fpn . We prove, using the standard heuristic, that these algorithms will run in sub-exponential time. We also give an overview of different index calculus algorithms solving the discrete logarithm problem efficiently for different possible relations between the characteristic and the extension degree. To be able to give a good introduction to the algorithms, we present theory necessary to understand the underlying algebraic structures used in the algorithms. This theory is largely algebraic number theory. 1 Contents 1 Introduction 4 1.1 Discrete logarithms . .4 1.2 The general number field sieve and L-notation . .4 2 Theory 6 2.1 Number fields . .6 2.1.1 Dedekind domains . .7 2.1.2 Module structure . .9 2.1.3 Norm of ideals . .9 2.1.4 Units . 10 2.2 Prime ideals . 10 2.3 Smooth numbers . 13 2.3.1 Density . 13 2.3.2 Exponent vectors . 13 3 The number field sieve in prime fields 15 3.1 Overview . 15 3.2 Calculating logarithms . 15 3.3 Sieving . 17 3.4 Schirokauer maps . 18 3.5 Linear algebra . 20 3.5.1 A note about smooth t and g .............. 22 3.6 Run time . -
11.6 Discrete Logarithms Over Finite Fields
Algorithms 61 11.6 Discrete logarithms over finite fields Andrew Odlyzko, University of Minnesota Surveys and detailed expositions with proofs can be found in [7, 25, 26, 28, 33, 34, 47]. 11.6.1 Basic definitions 11.6.1 Remark Discrete exponentiation in a finite field is a direct analog of ordinary exponentiation. The exponent can only be an integer, say n, but for w in a field F , wn is defined except when w = 0 and n ≤ 0, and satisfies the usual properties, in particular wm+n = wmwn and (for u and v in F )(uv)m = umvm. The discrete logarithm is the inverse function, in analogy with the ordinary logarithm for real numbers. If F is a finite field, then it has at least one primitive element g; i.e., all nonzero elements of F are expressible as powers of g, see Chapter ??. 11.6.2 Definition Given a finite field F , a primitive element g of F , and a nonzero element w of F , the discrete logarithm of w to base g, written as logg(w), is the least non-negative integer n such that w = gn. 11.6.3 Remark The value logg(w) is unique modulo q − 1, and 0 ≤ logg(w) ≤ q − 2. It is often convenient to allow it to be represented by any integer n such that w = gn. 11.6.4 Remark The discrete logarithm of w to base g is often called the index of w with respect to the base g. More generally, we can define discrete logarithms in groups. -
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International Journal of Electrical and Computer Engineering (IJECE) Vol. 10, No. 2, April 2020, pp. 1469~1476 ISSN: 2088-8708, DOI: 10.11591/ijece.v10i2.pp1469-1476 1469 The new integer factorization algorithm based on fermat’s factorization algorithm and euler’s theorem Kritsanapong Somsuk Department of Computer and Communication Engineering, Faculty of Technology, Udon Thani Rajabhat University, Udon Thani, 41000, Thailand Article Info ABSTRACT Article history: Although, Integer Factorization is one of the hard problems to break RSA, many factoring techniques are still developed. Fermat’s Factorization Received Apr 7, 2019 Algorithm (FFA) which has very high performance when prime factors are Revised Oct 7, 2019 close to each other is a type of integer factorization algorithms. In fact, there Accepted Oct 20, 2019 are two ways to implement FFA. The first is called FFA-1, it is a process to find the integer from square root computing. Because this operation takes high computation cost, it consumes high computation time to find the result. Keywords: The other method is called FFA-2 which is the different technique to find prime factors. Although the computation loops are quite large, there is no Computation loops square root computing included into the computation. In this paper, Euler’s theorem the new efficient factorization algorithm is introduced. Euler’s theorem is Fermat’s factorization chosen to apply with FFA to find the addition result between two prime Integer factorization factors. The advantage of the proposed method is that almost of square root Prime factors operations are left out from the computation while loops are not increased, they are equal to the first method. -
INDEX CALCULUS in the TRACE ZERO VARIETY 1. Introduction
INDEX CALCULUS IN THE TRACE ZERO VARIETY ELISA GORLA AND MAIKE MASSIERER Abstract. We discuss how to apply Gaudry's index calculus algorithm for abelian varieties to solve the discrete logarithm problem in the trace zero variety of an elliptic curve. We treat in particular the practically relevant cases of field extensions of degree 3 or 5. Our theoretical analysis is compared to other algorithms present in the literature, and is complemented by results from a prototype implementation. 1. Introduction Given an elliptic curve E defined over a finite field Fq, consider the group E(Fqn ) of rational points over a field extension of prime degree n. Since E is defined over Fq, the group E(Fqn ) contains the subgroup E(Fq) of Fq-rational points of E. Moreover, it contains the subgroup Tn of n−1 points P 2 E(Fqn ) whose trace P + '(P ) + ::: + ' (P ) is zero, where ' denotes the Frobenius homomorphism on E. The group Tn is called the trace zero subgroup of E(Fqn ), and it is the group of Fq-rational points of the trace zero variety relative to the field extension Fqn jFq. In this paper, we study the hardness of the DLP in the trace zero variety. Our interest in this question has several motivations. First of all, supersingular trace zero varieties can achieve higher security per bit than supersingular elliptic curves, as shown by Rubin and Silverberg in [RS02, RS09] and by Avanzi and Cesena in [AC07, Ces10]. Ideally, in pairing-based proto- ∗ cols the embedding degree k is such that the DLP in Tn and in Fqkn have the same complexity. -
Modern Computer Arithmetic (Version 0.5. 1)
Modern Computer Arithmetic Richard P. Brent and Paul Zimmermann Version 0.5.1 arXiv:1004.4710v1 [cs.DS] 27 Apr 2010 Copyright c 2003-2010 Richard P. Brent and Paul Zimmermann This electronic version is distributed under the terms and conditions of the Creative Commons license “Attribution-Noncommercial-No Derivative Works 3.0”. You are free to copy, distribute and transmit this book under the following conditions: Attribution. You must attribute the work in the manner specified • by the author or licensor (but not in any way that suggests that they endorse you or your use of the work). Noncommercial. You may not use this work for commercial purposes. • No Derivative Works. You may not alter, transform, or build upon • this work. For any reuse or distribution, you must make clear to others the license terms of this work. The best way to do this is with a link to the web page below. Any of the above conditions can be waived if you get permission from the copyright holder. Nothing in this license impairs or restricts the author’s moral rights. For more information about the license, visit http://creativecommons.org/licenses/by-nc-nd/3.0/ Contents Contents iii Preface ix Acknowledgements xi Notation xiii 1 Integer Arithmetic 1 1.1 RepresentationandNotations . 1 1.2 AdditionandSubtraction . .. 2 1.3 Multiplication . 3 1.3.1 Naive Multiplication . 4 1.3.2 Karatsuba’s Algorithm . 5 1.3.3 Toom-Cook Multiplication . 7 1.3.4 UseoftheFastFourierTransform(FFT) . 8 1.3.5 Unbalanced Multiplication . 9 1.3.6 Squaring.......................... 12 1.3.7 Multiplication by a Constant . -
The Past, Evolving Present and Future of Discrete Logarithm
The Past, evolving Present and Future of Discrete Logarithm Antoine Joux, Andrew Odlyzko and Cécile Pierrot Abstract The first practical public key cryptosystem ever published, the Diffie-Hellman key exchange algorithm, relies for its security on the assumption that discrete logarithms are hard to compute. This intractability hypothesis is also the foundation for the security of a large variety of other public key systems and protocols. Since the introduction of the Diffie-Hellman key exchange more than three decades ago, there have been substantial algorithmic advances in the computation of discrete logarithms. However, in general the discrete logarithm problem is still considered to be hard. In particular, this is the case for the multiplicative group of finite fields with medium to large characteristic and for the additive group of a general elliptic curve. This paper presents a current survey of the state of the art concerning discrete logarithms and their computation. 1 Introduction 1.1 The Discrete Logarithm Problem Many popular public key cryptosystems are based on discrete exponentiation. If G is a multi- plicative group, such as the group of invertible elements in a finite field or the group of points on an elliptic curve, and g is an element of G, then gx is the discrete exponentiation of base g to the power x. This operation shares basic properties with ordinary exponentiation, for example gx+y = gx · gy. The inverse operation is, given h in G, to determine a value of x, if it exists, such that h = gx. Such a number x is called a discrete logarithm of h to the base g, since it shares many properties with the ordinary logarithm. -
The Factoring Dead: Preparing for the Cryptopocalypse
THE FACTORING DEAD: PREPARING FOR THE CRYPTOPOCALYPSE Javed Samuel — javed[at]isecpartners[dot]com iSEC Partners, Inc 123 Mission Street, Suite 1020 San Francisco, CA 94105 https://www.isecpartners.com March 20, 2014 Abstract This paper will explain the latest breakthroughs in the academic cryptography community and look ahead at what practical issues could arise for popular cryptosystems. Specifically, we will focus on the recent major devel- opments in discrete mathematics and their potential ability to undermine our trust in the most basic asymmetric primitives, including RSA. We will explain the basic theories behind RSA and the state-of-the-art in large number- ing factoring, and how several recent papers may point the way to massive improvements in this area. The paper will then switch to the practical aspects of the doomsday scenario, and will answer the question “What happens the day after RSA is broken?” We will point out the many obvious and hidden uses of RSA and related algorithms and outline how software engineers and security teams can operate in a post-RSA world. We will also discuss the results of our survey of popular products and software, and point out the ways in which individuals can prepare for the “zombie cryptopocalypse”. 1 INTRODUCTION Over the past few years, there have been numerous attacks on the current SSL infrastructure. These have ranged from BEAST [97], CRIME [88], Lucky 13 [2][86], RC4 bias attacks [1][91] and BREACH [42]. These attacks all show the fragility of the current SSL architecture as vulnerabilities have been found in a variety of features ranging from compression, timing and padding [90].