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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 -
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 . -
Enhancing the Securing RSA Algorithm from Attack
Journal of Basic and Applied Engineering Research Print ISSN: 2350-0077; Online ISSN: 2350-0255; Volume 1, Number 10; October, 2014 pp. 48-63 © Krishi Sanskriti Publications http://www.krishisanskriti.org/jbaer.html Enhancing the Securing RSA Algorithm from Attack Swati Srivastava 1, Meenu 2 1M.Tech Student, Department of CSE, Madan Mohan Malaviya University of Technology, Gorakhpur, U.P. 2Department of CSE, Madan MohanMalaviya University of Technology, Gorakhpur, U.P. Abstract: The RSA public key and signature scheme is often used authenticity, integrity, and limited access to data. In in modern communications technologies; it is one of the firstly Cryptography we differentiate between private key defined public key cryptosystem that enable secure cryptographic systems (also known as conventional communicating over public unsecure communication channels. cryptography systems) and public key cryptographic systems. In praxis many protocols and security standards use the RSA, Private Key Cryptography, also known as secret-key or thus the security of the RSA is critical because any weaknesses in the RSA crypto system may lead the whole system to become symmetric-key encryption, has an old history, and is based on vulnerable against attacks. This paper introduce a security using one shared secret key for encryption and decryption. enhancement on the RSA cryptosystem, it suggests the use of The development of fast computers and communication randomized parameters in the encryption process to make RSA technologies did allow us to define many -
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. -
Introducing Quaternions to Integer Factorisation
Journal of Physical Science and Application 5 (2) (2015) 101-107 doi: 10.17265/2159-5348/2015.02.003 D DAVID PUBLISHING Introducing Quaternions to Integer Factorisation HuiKang Tong 4500 Ang Mo Kio Avenue 6, 569843, Singapore Abstract: The key purpose of this paper is to open up the concepts of the sum of four squares and the algebra of quaternions into the attempts of factoring semiprimes, the product of two prime numbers. However, the application of these concepts here has been clumsy, and would be better explored by those with a more rigorous mathematical background. There may be real immediate implications on some RSA numbers that are slightly larger than a perfect square. Key words: Integer factorisation, RSA, quaternions, sum of four squares, euler factorisation method. Nomenclature In Section 3, we extend the Euler factoring method to one using the sum of four squares and the algebra p, q: prime factors n: semiprime pq, the product of two primes of quaternions. We comment on the development of P: quaternion with norm p the mathematics in Section 3.1, and introduce the a, b, c, d: components of a quaternion integral quaternions in Section 3.2, and its relationship 1. Introduction with the sum of four squares in Section 3.3. In Section 3.4, we mention an algorithm to generate the sum of We assume that the reader know the RSA four squares. cryptosystem [1]. Notably, the ability to factorise a In Section 4, we propose the usage of concepts of random and large semiprime n (the product of two the algebra of quaternions into the factorisation of prime numbers p and q) efficiently can completely semiprimes. -
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]. -
USING NUMBER FIELDS to COMPUTE LOGARITHMS in FINITE FIELDS 1. Introduction Let Q = Pn, Where P Is a Prime Number and N a Positiv
MATHEMATICS OF COMPUTATION Volume 69, Number 231, Pages 1267{1283 S 0025-5718(99)01137-0 Article electronically published on May 24, 1999 USING NUMBER FIELDS TO COMPUTE LOGARITHMS IN FINITE FIELDS OLIVER SCHIROKAUER Abstract. We describe an adaptation of the number field sieve to the problem of computing logarithms in a finite field. We conjecture that the running time of the algorithm, when restricted to finite fields of an arbitrary but fixed 1=3 degree, is Lq[1=3; (64=9) + o(1)]; where q is the cardinality of the field, s 1−s Lq [s; c]=exp(c(log q) (log log q) ); and the o(1) is for q !1.Thenumber field sieve factoring algorithm is conjectured to factor a number the size of q inthesameamountoftime. 1. Introduction n Let q = p ,wherep is a prime number and n a positive integer, and let Fq be the field of q elements. Let t and v be nonzero elements in Fq such that v is in the multiplicative subgroup generated by t,andletx be the smallest nonnegative integer such that tx = v. We call the exponent x the discrete logarithm of v with respect to the base t and write x =logt v. In this paper we present an algorithm to compute logt v. The most succesful methods to date to compute discrete logarithms in a finite field are all descendants of the index calculus method described by Kraitchik in the 1920's (see [14] and [15]) and rediscovered and modified by numerous mathe- maticians since then (see [25] and [31]). -
Question 1.1. What Is the RSA Laboratories' Frequently Asked
Copyright © 1996, 1998 RSA Data Security, Inc. All rights reserved. RSA BSAFE Crypto-C, RSA BSAFE Crypto-J, PKCS, S/WAN, RC2, RC4, RC5, MD2, MD4, and MD5 are trade- marks or registered trademarks of RSA Data Security, Inc. Other products and names are trademarks or regis- tered trademarks of their respective owners. For permission to reprint or redistribute in part or in whole, send e-mail to [email protected] or contact your RSA representative. RSA Laboratories’ Frequently Asked Questions About Today’s Cryptography, v4.0 2 Table of Contents Table of Contents............................................................................................ 3 Foreword......................................................................................................... 8 Section 1: Introduction .................................................................................... 9 Question 1.1. What is the RSA Laboratories’ Frequently Asked Questions About Today’s Cryptography? ................................................................................................................ 9 Question 1.2. What is cryptography? ............................................................................................10 Question 1.3. What are some of the more popular techniques in cryptography? ................... 11 Question 1.4. How is cryptography applied? ............................................................................... 12 Question 1.5. What are cryptography standards? ...................................................................... -
An Introduction to Modern Cryptology Within an Algebraic Framework John Szwast Eastern Washington University
Eastern Washington University EWU Digital Commons EWU Masters Thesis Collection Student Research and Creative Works 2012 An introduction to modern cryptology within an algebraic framework John Szwast Eastern Washington University Follow this and additional works at: http://dc.ewu.edu/theses Part of the Physical Sciences and Mathematics Commons Recommended Citation Szwast, John, "An introduction to modern cryptology within an algebraic framework" (2012). EWU Masters Thesis Collection. 13. http://dc.ewu.edu/theses/13 This Thesis is brought to you for free and open access by the Student Research and Creative Works at EWU Digital Commons. It has been accepted for inclusion in EWU Masters Thesis Collection by an authorized administrator of EWU Digital Commons. For more information, please contact [email protected]. AN INTRODUCTION TO MODERN CRYPTOLOGY WITHIN AN ALGEBRAIC FRAMEWORK A Thesis Presented To Eastern Washington University Cheney, Washington In Partial Fulfillment of the Requirements for the Degree Master of Science By John Szwast Fall 2012 THESIS OF JOHN SZWAST APPROVED BY DATE: DR. RON GENTLE, GRADUATE STUDY COMMITTEE DATE: DR. DALE GARRAWAY, GRADUATE STUDY COMMITTEE DATE: DR. PAUL SCHIMPF, GRADUATE STUDY COMMITTEE Contents List of Figures vii List of Tables viii 1 Introduction 1 1.1 Scope . .1 1.2 Background . .2 1.3 Conventions and Notations . .2 1.4 Overview . .3 1.5 General Definitions . .4 1.6 Bit Operations and Big-O Notation . .5 1.6.1 Overview . .5 1.6.2 Time Estimates for Integer Arithmetic . .8 1.6.3 Time estimates for modular arithmetic . 12 1.7 Probability . 15 iii CONTENTS CONTENTS 1.7.1 Discrete distributions . -
Notes for Number Theory Here Are the Notes I Wrote up for a Number Theory Course I Taught
1 Notes for Number Theory Here are the notes I wrote up for a number theory course I taught. The notes cover elementary number theory but don’t get into anything too advanced. My approach to things is fairly informal. I like to explain the ideas behind everything without getting too formal and also without getting too wordy. If you see anything wrong (including typos), please send me a note at [email protected]. Last updated: March 20, 2021. Contents 1 Divisibility 4 1.1 Definition of divisibility...............................................4 1.2 The division algorithm................................................5 1.3 The modulo operation................................................7 1.4 The greatest common divisor............................................7 1.5 Gcds and linear combinations...........................................9 1.6 The extended Euclidean algorithm........................................9 1.7 A few example proofs................................................ 11 1.8 The least common multiple............................................. 11 1.9 Relatively prime integers.............................................. 12 1.10 The gcd and lcm of more than two integers................................... 13 1.11 Some useful facts about divisibility and gcds.................................. 13 2 Primes 15 2.1 The fundamental theorem of arithmetic..................................... 15 2.2 There are infinitely many primes.......................................... 17 2.3 Finding primes.................................................... -
Selecting Polynomials for the Function Field Sieve
Selecting polynomials for the Function Field Sieve Razvan Barbulescu The Function Field Sieve (FFS) algorithm is dedicated to computing discrete logarithms in n a finite field Fqn , where q is a prime power, small compared to q . Introduced by Adleman in [Adl94] and inspired by the Number Field Sieve (NFS), the algorithm collects pairs of polynomials (a; b) 2 Fq[t] such that the norms of a − bx in two function fields are both smooth (the sieving stage), i.e having only irreducible divisors of small degree. It then solves a sparse linear system (the linear algebra stage), whose solutions, called virtual logarithms, allow to compute the discrete algorithm of any element during a final stage (individual logarithm stage). The choice of the defining polynomials f and g for the two function fields can be seen as a preliminary stage of the algorithm. It takes a small amount of time but it can greatly influence the sieving stage by slightly changing the probabilities of smoothness. In order to solve the discrete logarithm in Fqn , the main required property of f; g 2 Fq[t][x] is that their resultant Resx(f; g) has an irreducible factor '(t) of degree n. Various methods have been proposed to build such polynomials, but the best results in practice correspond to the method of Joux and Lercier [JL02]. Its particularity is that one of the two polynomials, say g, is linear. Moreover, for any polynomial f in Fq[t][x] and any input Fqn , one can associate a linear polynomial g satisfying the requirements of the FFS. -
The Impact of the Number Field Sieve on the Discrete Logarithm Problem In
Algorithmic Number Theory MSRI Publications Volume 44, 2008 The impact of the number field sieve on the discrete logarithm problem in finite fields OLIVER SCHIROKAUER 1. Introduction n Let p be a prime number and n a positive integer, and let q p . Let ކq D be the field of q elements and denote by ކq the multiplicative subgroup of ކq. Assume t and u are elements in ކq with the property that u is in the subgroup generated by t. The discrete logarithm of u with respect to the base t, written log u, is the least non-negative integer x such that t x u. t D In this paper we describe two methods to compute discrete logarithms, both of which derive from the number field sieve (NFS) factoring algorithm described in [Stevenhagen 2008] and [Lenstra and Lenstra 1993]. When factoring an integer N with the NFS, we first choose a number ring R as in [Stevenhagen 2008] for which there is a ring homomorphism R ޚ=N ޚ. Then we combine smooth W ! 2 2 elements in R and in ޚ to obtain squares ˛1 a R and ˛2 a ޚ R, D 1 2 D 2 2 Â such that .˛1/ .˛2/. If .a1/ .a2/, then the gcd of N and a a2, D 6D ˙ 10 where a10 is a representative in ޚ for .a1/, is a non-trivial factor of N . When using the strategy to compute discrete logarithms in ކq, we choose either two number rings or two polynomial rings, call them R1 and R2, such that there are ring homomorphisms 1 R1 ކq and 2 R2 ކq.