Implementation of a New Primality Test
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Fast Tabulation of Challenge Pseudoprimes Andrew Shallue and Jonathan Webster
THE OPEN BOOK SERIES 2 ANTS XIII Proceedings of the Thirteenth Algorithmic Number Theory Symposium Fast tabulation of challenge pseudoprimes Andrew Shallue and Jonathan Webster msp THE OPEN BOOK SERIES 2 (2019) Thirteenth Algorithmic Number Theory Symposium msp dx.doi.org/10.2140/obs.2019.2.411 Fast tabulation of challenge pseudoprimes Andrew Shallue and Jonathan Webster We provide a new algorithm for tabulating composite numbers which are pseudoprimes to both a Fermat test and a Lucas test. Our algorithm is optimized for parameter choices that minimize the occurrence of pseudoprimes, and for pseudoprimes with a fixed number of prime factors. Using this, we have confirmed that there are no PSW-challenge pseudoprimes with two or three prime factors up to 280. In the case where one is tabulating challenge pseudoprimes with a fixed number of prime factors, we prove our algorithm gives an unconditional asymptotic improvement over previous methods. 1. Introduction Pomerance, Selfridge, and Wagstaff famously offered $620 for a composite n that satisfies (1) 2n 1 1 .mod n/ so n is a base-2 Fermat pseudoprime, Á (2) .5 n/ 1 so n is not a square modulo 5, and j D (3) Fn 1 0 .mod n/ so n is a Fibonacci pseudoprime, C Á or to prove that no such n exists. We call composites that satisfy these conditions PSW-challenge pseudo- primes. In[PSW80] they credit R. Baillie with the discovery that combining a Fermat test with a Lucas test (with a certain specific parameter choice) makes for an especially effective primality test[BW80]. -
Primality Testing and Integer Factorisation
Primality Testing and Integer Factorisation Richard P. Brent, FAA Computer Sciences Laboratory Australian National University Canberra, ACT 2601 Abstract The problem of finding the prime factors of large composite numbers has always been of mathematical interest. With the advent of public key cryptosystems it is also of practical importance, because the security of some of these cryptosystems, such as the Rivest-Shamir-Adelman (RSA) system, depends on the difficulty of factoring the public keys. In recent years the best known integer factorisation algorithms have improved greatly, to the point where it is now easy to factor a 60-decimal digit number, and possible to factor numbers larger than 120 decimal digits, given the availability of enough computing power. We describe several recent algorithms for primality testing and factorisation, give examples of their use and outline some applications. 1. Introduction It has been known since Euclid’s time (though first clearly stated and proved by Gauss in 1801) that any natural number N has a unique prime power decomposition α1 α2 αk N = p1 p2 ··· pk (1.1) αj (p1 < p2 < ··· < pk rational primes, αj > 0). The prime powers pj are called αj components of N, and we write pj kN. To compute the prime power decomposition we need – 1. An algorithm to test if an integer N is prime. 2. An algorithm to find a nontrivial factor f of a composite integer N. Given these there is a simple recursive algorithm to compute (1.1): if N is prime then stop, otherwise 1. find a nontrivial factor f of N; 2. -
An Analysis of Primality Testing and Its Use in Cryptographic Applications
An Analysis of Primality Testing and Its Use in Cryptographic Applications Jake Massimo Thesis submitted to the University of London for the degree of Doctor of Philosophy Information Security Group Department of Information Security Royal Holloway, University of London 2020 Declaration These doctoral studies were conducted under the supervision of Prof. Kenneth G. Paterson. The work presented in this thesis is the result of original research carried out by myself, in collaboration with others, whilst enrolled in the Department of Mathe- matics as a candidate for the degree of Doctor of Philosophy. This work has not been submitted for any other degree or award in any other university or educational establishment. Jake Massimo April, 2020 2 Abstract Due to their fundamental utility within cryptography, prime numbers must be easy to both recognise and generate. For this, we depend upon primality testing. Both used as a tool to validate prime parameters, or as part of the algorithm used to generate random prime numbers, primality tests are found near universally within a cryptographer's tool-kit. In this thesis, we study in depth primality tests and their use in cryptographic applications. We first provide a systematic analysis of the implementation landscape of primality testing within cryptographic libraries and mathematical software. We then demon- strate how these tests perform under adversarial conditions, where the numbers being tested are not generated randomly, but instead by a possibly malicious party. We show that many of the libraries studied provide primality tests that are not pre- pared for testing on adversarial input, and therefore can declare composite numbers as being prime with a high probability. -
Fast Generation of RSA Keys Using Smooth Integers
1 Fast Generation of RSA Keys using Smooth Integers Vassil Dimitrov, Luigi Vigneri and Vidal Attias Abstract—Primality generation is the cornerstone of several essential cryptographic systems. The problem has been a subject of deep investigations, but there is still a substantial room for improvements. Typically, the algorithms used have two parts – trial divisions aimed at eliminating numbers with small prime factors and primality tests based on an easy-to-compute statement that is valid for primes and invalid for composites. In this paper, we will showcase a technique that will eliminate the first phase of the primality testing algorithms. The computational simulations show a reduction of the primality generation time by about 30% in the case of 1024-bit RSA key pairs. This can be particularly beneficial in the case of decentralized environments for shared RSA keys as the initial trial division part of the key generation algorithms can be avoided at no cost. This also significantly reduces the communication complexity. Another essential contribution of the paper is the introduction of a new one-way function that is computationally simpler than the existing ones used in public-key cryptography. This function can be used to create new random number generators, and it also could be potentially used for designing entirely new public-key encryption systems. Index Terms—Multiple-base Representations, Public-Key Cryptography, Primality Testing, Computational Number Theory, RSA ✦ 1 INTRODUCTION 1.1 Fast generation of prime numbers DDITIVE number theory is a fascinating area of The generation of prime numbers is a cornerstone of A mathematics. In it one can find problems with cryptographic systems such as the RSA cryptosystem. -
Primes and Primality Testing
Primes and Primality Testing A Technological/Historical Perspective Jennifer Ellis Department of Mathematics and Computer Science What is a prime number? A number p greater than one is prime if and only if the only divisors of p are 1 and p. Examples: 2, 3, 5, and 7 A few larger examples: 71887 524287 65537 2127 1 Primality Testing: Origins Eratosthenes: Developed “sieve” method 276-194 B.C. Nicknamed Beta – “second place” in many different academic disciplines Also made contributions to www-history.mcs.st- geometry, approximation of andrews.ac.uk/PictDisplay/Eratosthenes.html the Earth’s circumference Sieve of Eratosthenes 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 Sieve of Eratosthenes We only need to “sieve” the multiples of numbers less than 10. Why? (10)(10)=100 (p)(q)<=100 Consider pq where p>10. Then for pq <=100, q must be less than 10. By sieving all the multiples of numbers less than 10 (here, multiples of q), we have removed all composite numbers less than 100. -
The Quadratic Sieve Factoring Algorithm
The Quadratic Sieve Factoring Algorithm Eric Landquist MATH 488: Cryptographic Algorithms December 14, 2001 1 1 Introduction Mathematicians have been attempting to find better and faster ways to fac- tor composite numbers since the beginning of time. Initially this involved dividing a number by larger and larger primes until you had the factoriza- tion. This trial division was not improved upon until Fermat applied the factorization of the difference of two squares: a2 b2 = (a b)(a + b). In his method, we begin with the number to be factored:− n. We− find the smallest square larger than n, and test to see if the difference is square. If so, then we can apply the trick of factoring the difference of two squares to find the factors of n. If the difference is not a perfect square, then we find the next largest square, and repeat the process. While Fermat's method is much faster than trial division, when it comes to the real world of factoring, for example factoring an RSA modulus several hundred digits long, the purely iterative method of Fermat is too slow. Sev- eral other methods have been presented, such as the Elliptic Curve Method discovered by H. Lenstra in 1987 and a pair of probabilistic methods by Pollard in the mid 70's, the p 1 method and the ρ method. The fastest algorithms, however, utilize the− same trick as Fermat, examples of which are the Continued Fraction Method, the Quadratic Sieve (and it variants), and the Number Field Sieve (and its variants). The exception to this is the El- liptic Curve Method, which runs almost as fast as the Quadratic Sieve. -
Primality Testing for Beginners
STUDENT MATHEMATICAL LIBRARY Volume 70 Primality Testing for Beginners Lasse Rempe-Gillen Rebecca Waldecker http://dx.doi.org/10.1090/stml/070 Primality Testing for Beginners STUDENT MATHEMATICAL LIBRARY Volume 70 Primality Testing for Beginners Lasse Rempe-Gillen Rebecca Waldecker American Mathematical Society Providence, Rhode Island Editorial Board Satyan L. Devadoss John Stillwell Gerald B. Folland (Chair) Serge Tabachnikov The cover illustration is a variant of the Sieve of Eratosthenes (Sec- tion 1.5), showing the integers from 1 to 2704 colored by the number of their prime factors, including repeats. The illustration was created us- ing MATLAB. The back cover shows a phase plot of the Riemann zeta function (see Appendix A), which appears courtesy of Elias Wegert (www.visual.wegert.com). 2010 Mathematics Subject Classification. Primary 11-01, 11-02, 11Axx, 11Y11, 11Y16. For additional information and updates on this book, visit www.ams.org/bookpages/stml-70 Library of Congress Cataloging-in-Publication Data Rempe-Gillen, Lasse, 1978– author. [Primzahltests f¨ur Einsteiger. English] Primality testing for beginners / Lasse Rempe-Gillen, Rebecca Waldecker. pages cm. — (Student mathematical library ; volume 70) Translation of: Primzahltests f¨ur Einsteiger : Zahlentheorie - Algorithmik - Kryptographie. Includes bibliographical references and index. ISBN 978-0-8218-9883-3 (alk. paper) 1. Number theory. I. Waldecker, Rebecca, 1979– author. II. Title. QA241.R45813 2014 512.72—dc23 2013032423 Copying and reprinting. Individual readers of this publication, and nonprofit libraries acting for them, are permitted to make fair use of the material, such as to copy a chapter for use in teaching or research. Permission is granted to quote brief passages from this publication in reviews, provided the customary acknowledgment of the source is given. -
Miller–Rabin Test
Lecture 31: Miller–Rabin Test Miller–Rabin Test Recall In the previous lecture we considered an efficient randomized algorithm to generate prime numbers that need n-bits in their binary representation This algorithm sampled a random element in the range f2n−1; 2n−1 + 1;:::; 2n − 1g and test whether it is a prime number or not By the Prime Number Theorem, we are extremely likely to hit a prime number So, all that remains is an algorithm to test whether the random sample we have chosen is a prime number or not Miller–Rabin Test Primality Testing Given an n-bit number N as input, we have to ascertain whether N is a prime number or not in time polynomial in n Only in 2002, Agrawal–Kayal–Saxena constructed a deterministic polynomial time algorithm for primality testing. That is, the algorithm will always run in time polynomial in n. For any input N (that has n-bits in its binary representation), if N is a prime number, the AKS primality testing algorithm will return 1; otherwise (if, the number N is a composite number), the AKS primality testing algorithm will return 0. In practice, this algorithm is not used for primality testing because this turns out to be too slow. In practice, we use a randomized algorithm, namely, the Miller–Rabin Test, that successfully distinguishes primes from composites with very high probability. In this lecture, we will study a basic version of this Miller–Rabin primality test. Miller–Rabin Test Assurance of Miller–Rabin Test Miller–Rabin outputs 1 to indicate that it has classified the input N as a prime. -
Cryptology and Computational Number Theory (Boulder, Colorado, August 1989) 41 R
http://dx.doi.org/10.1090/psapm/042 Other Titles in This Series 50 Robert Calderbank, editor, Different aspects of coding theory (San Francisco, California, January 1995) 49 Robert L. Devaney, editor, Complex dynamical systems: The mathematics behind the Mandlebrot and Julia sets (Cincinnati, Ohio, January 1994) 48 Walter Gautschi, editor, Mathematics of Computation 1943-1993: A half century of computational mathematics (Vancouver, British Columbia, August 1993) 47 Ingrid Daubechies, editor, Different perspectives on wavelets (San Antonio, Texas, January 1993) 46 Stefan A. Burr, editor, The unreasonable effectiveness of number theory (Orono, Maine, August 1991) 45 De Witt L. Sumners, editor, New scientific applications of geometry and topology (Baltimore, Maryland, January 1992) 44 Bela Bollobas, editor, Probabilistic combinatorics and its applications (San Francisco, California, January 1991) 43 Richard K. Guy, editor, Combinatorial games (Columbus, Ohio, August 1990) 42 C. Pomerance, editor, Cryptology and computational number theory (Boulder, Colorado, August 1989) 41 R. W. Brockett, editor, Robotics (Louisville, Kentucky, January 1990) 40 Charles R. Johnson, editor, Matrix theory and applications (Phoenix, Arizona, January 1989) 39 Robert L. Devaney and Linda Keen, editors, Chaos and fractals: The mathematics behind the computer graphics (Providence, Rhode Island, August 1988) 38 Juris Hartmanis, editor, Computational complexity theory (Atlanta, Georgia, January 1988) 37 Henry J. Landau, editor, Moments in mathematics (San Antonio, Texas, January 1987) 36 Carl de Boor, editor, Approximation theory (New Orleans, Louisiana, January 1986) 35 Harry H. Panjer, editor, Actuarial mathematics (Laramie, Wyoming, August 1985) 34 Michael Anshel and William Gewirtz, editors, Mathematics of information processing (Louisville, Kentucky, January 1984) 33 H. Peyton Young, editor, Fair allocation (Anaheim, California, January 1985) 32 R. -
15-251: Great Theoretical Ideas in Computer Science Recitation 14 Solutions PRIMES ∈ NP
15-251: Great Theoretical Ideas In Computer Science Recitation 14 Solutions PRIMES 2 NP The set of PRIMES of all primes is in co-NP, because if n is composite and k j n, we can verify this in polynomial time. In fact, the AKS primality test means that PRIMES is in P. We'll just prove PRIMES 2 NP. ∗ (a) We know n is prime iff φ(n) = n−1. Additionally, if n is prime then Zn is cyclic with order n−1. ∗ Given a generator a of Zn and a (guaranteed correct) prime factorization of n − 1, can we verify n is prime? If a has order n − 1, then we are done. So we must verify a has order dividing n − 1: an−1 ≡ 1 mod n and doesn't have smaller order, i.e. for all prime p j n − 1: a(n−1)=p 6≡ 1 mod n a is smaller than n, and there are at most log(n) factors each smaller than n, so our certificate is polynomial in n's representation. Similarly, each arithmetic computation is polynomial in log(n), and there are O(log(n)) of them. 1 (b) What else needs to be verified to use this as a primality certificate? Do we need to add more information? We also need to verify that our factorization (p1; α1); (p2; α2);:::; (pk; αk) of n − 1 is correct, two conditions: α1 α2 αk 1. p1 p2 : : : pk = n − 1 can be verified by multiplying and comparing, polynomial in log(n). 2. -
Pseudoprimes and Classical Primality Tests
Pseudoprimes and Classical Primality Tests Sebastian Pancratz 2 March 2009 1 Introduction This brief introduction concerns various notions of pseudoprimes and their relation to classical composite tests, that is, algorithms which can prove numbers composite, but might not identify all composites as such and hence cannot prove numbers prime. In the talk I hope to also present one of the classical algorithms to prove a number n prime. In contrast to modern algorithms, these are often either not polynomial-time algorithms, heavily depend on known factorisations of numbers such as n − 1 or are restricted to certain classes of candidates n. One of the simplest composite tests is based on Fermat's Little Theorem, stating that for any prime p and any integer a coprime to p we have ap−1 ≡ 1 (mod p). Hence we can prove an integer n > 1 composite by nding an integer b coprime to n with the property that bn−1 6≡ 1 (mod n). Denition 1. Let n > 1 be an odd integer and b > 1 with (b, n) = 1. We call n a pseudo-prime to base b if bn−1 ≡ 1 (mod n), that is, if the pair n, b satises the conclusion of Fermat's Little Theorem. Denition 2. If n is a positive odd composite integer which is a pseudo-prime to all bases b, we call n a Carmichael number. Using this criterion, we can easily check that e.g. 561 = 3 × 11 × 17 is a Carmichael number. It has been shown that there are innitely many Carmichael numbers [1]. -
Tables of Fibonacci and Lucas Factorizations
MATHEMATICS OF COMPUTATION VOLUME 50, NUMBER 181 JANUARY 1988, PAGES 251-260 Tables of Fibonacci and Lucas Factorizations By John Brillhart, Peter L. Montgomery, and Robert D. Silverman Dedicated to Dov Jarden Abstract. We list the known prime factors of the Fibonacci numbers Fn for n < 999 and Lucas numbers Ln for n < 500. We discuss the various methods used to obtain these factorizations, and primality tests, and give some history of the subject. 1. Introduction. In the Supplements section at the end of this issue we give in two tables the known prime factors of the Fibonacci numbers Fn, 3 < n < 999, n odd, and the Lucas numbers Ln, 2 < n < 500. The sequences Fn and Ln are defined recursively by the formulas . ^n+2 = Fn+X + Fn, Fo = 0, Fi = 1, Ln+2 = Ln+i + Ln, in = 2, L\ = 1. The use of a different subscripting destroys the divisibility properties of these numbers. We also have the formulas an - 3a (1-2) Fn = --£-, Ln = an + ßn, a —ß where a = (1 + \/B)/2 and ß — (1 - v^5)/2. This paper is concerned with the multiplicative structure of Fn and Ln. It includes both theoretical and numerical results. 2. Multiplicative Structure of Fn and Ln. The identity (2.1) F2n = FnLn follows directly from (1.2). Although the Fibonacci and Lucas numbers are defined additively, this is one of many multiplicative identities relating these sequences. The identities in this paper are derived from the familiar polynomial factorization (2.2) xn-yn = ]\*d(x,y), n>\, d\n where $d(x,y) is the dth cyclotomic polynomial in homogeneous form.