Modular Exponentiation of Integers (Handout November 12, 2008)
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The Enigmatic Number E: a History in Verse and Its Uses in the Mathematics Classroom
To appear in MAA Loci: Convergence The Enigmatic Number e: A History in Verse and Its Uses in the Mathematics Classroom Sarah Glaz Department of Mathematics University of Connecticut Storrs, CT 06269 [email protected] Introduction In this article we present a history of e in verse—an annotated poem: The Enigmatic Number e . The annotation consists of hyperlinks leading to biographies of the mathematicians appearing in the poem, and to explanations of the mathematical notions and ideas presented in the poem. The intention is to celebrate the history of this venerable number in verse, and to put the mathematical ideas connected with it in historical and artistic context. The poem may also be used by educators in any mathematics course in which the number e appears, and those are as varied as e's multifaceted history. The sections following the poem provide suggestions and resources for the use of the poem as a pedagogical tool in a variety of mathematics courses. They also place these suggestions in the context of other efforts made by educators in this direction by briefly outlining the uses of historical mathematical poems for teaching mathematics at high-school and college level. Historical Background The number e is a newcomer to the mathematical pantheon of numbers denoted by letters: it made several indirect appearances in the 17 th and 18 th centuries, and acquired its letter designation only in 1731. Our history of e starts with John Napier (1550-1617) who defined logarithms through a process called dynamical analogy [1]. Napier aimed to simplify multiplication (and in the same time also simplify division and exponentiation), by finding a model which transforms multiplication into addition. -
Efficient Regular Modular Exponentiation Using
J Cryptogr Eng (2017) 7:245–253 DOI 10.1007/s13389-016-0134-5 SHORT COMMUNICATION Efficient regular modular exponentiation using multiplicative half-size splitting Christophe Negre1,2 · Thomas Plantard3,4 Received: 14 August 2015 / Accepted: 23 June 2016 / Published online: 13 July 2016 © Springer-Verlag Berlin Heidelberg 2016 Abstract In this paper, we consider efficient RSA modular x K mod N where N = pq with p and q prime. The private exponentiations x K mod N which are regular and con- data are the two prime factors of N and the private exponent stant time. We first review the multiplicative splitting of an K used to decrypt or sign a message. In order to insure a integer x modulo N into two half-size integers. We then sufficient security level, N and K are chosen large enough take advantage of this splitting to modify the square-and- to render the factorization of N infeasible: they are typically multiply exponentiation as a regular sequence of squarings 2048-bit integers. The basic approach to efficiently perform always followed by a multiplication by a half-size inte- the modular exponentiation is the square-and-multiply algo- ger. The proposed method requires around 16% less word rithm which scans the bits ki of the exponent K and perform operations compared to Montgomery-ladder, square-always a sequence of squarings followed by a multiplication when and square-and-multiply-always exponentiations. These the- ki is equal to one. oretical results are validated by our implementation results When the cryptographic computations are performed on which show an improvement by more than 12% compared an embedded device, an adversary can monitor power con- approaches which are both regular and constant time. -
Miller-Rabin Primality Test (Java)
Miller-Rabin primality test (Java) Other implementations: C | C, GMP | Clojure | Groovy | Java | Python | Ruby | Scala The Miller-Rabin primality test is a simple probabilistic algorithm for determining whether a number is prime or composite that is easy to implement. It proves compositeness of a number using the following formulas: Suppose 0 < a < n is coprime to n (this is easy to test using the GCD). Write the number n−1 as , where d is odd. Then, provided that all of the following formulas hold, n is composite: for all If a is chosen uniformly at random and n is prime, these formulas hold with probability 1/4. Thus, repeating the test for k random choices of a gives a probability of 1 − 1 / 4k that the number is prime. Moreover, Gerhard Jaeschke showed that any 32-bit number can be deterministically tested for primality by trying only a=2, 7, and 61. [edit] 32-bit integers We begin with a simple implementation for 32-bit integers, which is easier to implement for reasons that will become apparent. First, we'll need a way to perform efficient modular exponentiation on an arbitrary 32-bit integer. We accomplish this using exponentiation by squaring: Source URL: http://www.en.literateprograms.org/Miller-Rabin_primality_test_%28Java%29 Saylor URL: http://www.saylor.org/courses/cs409 ©Spoon! (http://www.en.literateprograms.org/Miller-Rabin_primality_test_%28Java%29) Saylor.org Used by Permission Page 1 of 5 <<32-bit modular exponentiation function>>= private static int modular_exponent_32(int base, int power, int modulus) { long result = 1; for (int i = 31; i >= 0; i--) { result = (result*result) % modulus; if ((power & (1 << i)) != 0) { result = (result*base) % modulus; } } return (int)result; // Will not truncate since modulus is an int } int is a 32-bit integer type and long is a 64-bit integer type. -
Three Methods of Finding Remainder on the Operation of Modular
Zin Mar Win, Khin Mar Cho; International Journal of Advance Research and Development (Volume 5, Issue 5) Available online at: www.ijarnd.com Three methods of finding remainder on the operation of modular exponentiation by using calculator 1Zin Mar Win, 2Khin Mar Cho 1University of Computer Studies, Myitkyina, Myanmar 2University of Computer Studies, Pyay, Myanmar ABSTRACT The primary purpose of this paper is that the contents of the paper were to become a learning aid for the learners. Learning aids enhance one's learning abilities and help to increase one's learning potential. They may include books, diagram, computer, recordings, notes, strategies, or any other appropriate items. In this paper we would review the types of modulo operations and represent the knowledge which we have been known with the easiest ways. The modulo operation is finding of the remainder when dividing. The modulus operator abbreviated “mod” or “%” in many programming languages is useful in a variety of circumstances. It is commonly used to take a randomly generated number and reduce that number to a random number on a smaller range, and it can also quickly tell us if one number is a factor of another. If we wanted to know if a number was odd or even, we could use modulus to quickly tell us by asking for the remainder of the number when divided by 2. Modular exponentiation is a type of exponentiation performed over a modulus. The operation of modular exponentiation calculates the remainder c when an integer b rose to the eth power, bᵉ, is divided by a positive integer m such as c = be mod m [1]. -
RSA Power Analysis Obfuscation: a Dynamic FPGA Architecture John W
Air Force Institute of Technology AFIT Scholar Theses and Dissertations Student Graduate Works 3-22-2012 RSA Power Analysis Obfuscation: A Dynamic FPGA Architecture John W. Barron Follow this and additional works at: https://scholar.afit.edu/etd Part of the Electrical and Computer Engineering Commons Recommended Citation Barron, John W., "RSA Power Analysis Obfuscation: A Dynamic FPGA Architecture" (2012). Theses and Dissertations. 1078. https://scholar.afit.edu/etd/1078 This Thesis is brought to you for free and open access by the Student Graduate Works at AFIT Scholar. It has been accepted for inclusion in Theses and Dissertations by an authorized administrator of AFIT Scholar. For more information, please contact [email protected]. RSA POWER ANALYSIS OBFUSCATION: A DYNAMIC FPGA ARCHITECTURE THESIS John W. Barron, Captain, USAF AFIT/GE/ENG/12-02 DEPARTMENT OF THE AIR FORCE AIR UNIVERSITY AIR FORCE INSTITUTE OF TECHNOLOGY Wright-Patterson Air Force Base, Ohio APPROVED FOR PUBLIC RELEASE; DISTRIBUTION UNLIMITED. The views expressed in this thesis are those of the author and do not reflect the official policy or position of the United States Air Force, Department of Defense, or the United States Government. This material is declared a work of the U.S. Government and is not subject to copyright protection in the United States. AFIT/GE/ENG/12-02 RSA POWER ANALYSIS OBFUSCATION: A DYNAMIC FPGA ARCHITECTURE THESIS Presented to the Faculty Department of Electrical and Computer Engineering Graduate School of Engineering and Management Air Force Institute of Technology Air University Air Education and Training Command In Partial Fulfillment of the Requirements for the Degree of Master of Science in Electrical Engineering John W. -
THE MILLER–RABIN PRIMALITY TEST 1. Fast Modular
THE MILLER{RABIN PRIMALITY TEST 1. Fast Modular Exponentiation Given positive integers a, e, and n, the following algorithm quickly computes the reduced power ae % n. • (Initialize) Set (x; y; f) = (1; a; e). • (Loop) While f > 1, do as follows: { If f%2 = 0 then replace (x; y; f) by (x; y2 % n; f=2), { otherwise replace (x; y; f) by (xy % n; y; f − 1). • (Terminate) Return x. The algorithm is strikingly efficient both in speed and in space. To see that it works, represent the exponent e in binary, say e = 2f + 2g + 2h; 0 ≤ f < g < h: The algorithm successively computes (1; a; 2f + 2g + 2h) f (1; a2 ; 1 + 2g−f + 2h−f ) f f (a2 ; a2 ; 2g−f + 2h−f ) f g (a2 ; a2 ; 1 + 2h−g) f g g (a2 +2 ; a2 ; 2h−g) f g h (a2 +2 ; a2 ; 1) f g h h (a2 +2 +2 ; a2 ; 0); and then it returns the first entry, which is indeed ae. 2. The Fermat Test and Fermat Pseudoprimes Fermat's Little Theorem states that for any positive integer n, if n is prime then bn mod n = b for b = 1; : : : ; n − 1. In the other direction, all we can say is that if bn mod n = b for b = 1; : : : ; n − 1 then n might be prime. If bn mod n = b where b 2 f1; : : : ; n − 1g then n is called a Fermat pseudoprime base b. There are 669 primes under 5000, but only five values of n (561, 1105, 1729, 2465, and 2821) that are Fermat pseudoprimes base b for b = 2; 3; 5 without being prime. -
Modular Exponentiation: Exercises
Modular Exponentiation: Exercises 1. Compute the following using the method of successive squaring: (a) 250 (mod 101) (b) 350 (mod 101) (c) 550 (mod 101). 2. Using an example from this lecture, compute 450 (mod 101) with no effort. How did you do it? 3. Explain how we could have predicted the answer to problem 1(a) with no effort. 4. Compute the following using the method of successive squaring: 50 58 44 (a) (3) in Z=101Z (b) (3) in Z=61Z (c)(4) in Z=51Z. 5000 5. Compute (78) in Z=79Z, and explain why this calculation is so very trivial. 4999 What is (78) in Z=79Z? 60 6. Fermat's Little Theorem says that (3) = 1 in Z=61Z. Use this fact to 58 compute (3) in Z=61Z (see problem 4(b) above) without using successive squaring, but by computing the inverse of (3)2 instead, for instance by the Euclidean algorithm. Explain why this works. 7. We may see later on that the set of all a 2 Z=mZ such that gcd(a; m) = 1 is a group. Let '(m) be the number of elements in this group, which is often × × denoted by (Z=mZ) . It turns out that for each a 2 (Z=mZ) , some power × of a must be equal to 1. The order of any a in the group (Z=mZ) is by definition the smallest positive integer e such that (a)e = 1. × (a) Compute the orders of all the elements of (Z=11Z) . × (b) Compute the orders of all the elements of (Z=17Z) . -
1.3 Division of Polynomials; Remainder and Factor Theorems
1-32 CHAPTER 1. POLYNOMIAL AND RATIONAL FUNCTIONS 1.3 Division of Polynomials; Remainder and Factor Theorems Objectives • Perform long division of polynomials • Perform synthetic division of polynomials • Apply remainder and factor theorems In previous courses, you may have learned how to factor polynomials using various techniques. Many of these techniques apply only to special kinds of polynomial expressions. For example, the the previous two sections of this chapter dealt only with polynomials that could easily be factored to find the zeros and x-intercepts. In order to be able to find zeros and x-intercepts of polynomials which cannot readily be factored, we first introduce long division of polynomials. We will then use the long division algorithm to make a general statement about factors of a polynomial. Long division of polynomials Long division of polynomials is similar to long division of numbers. When divid- ing polynomials, we obtain a quotient and a remainder. Just as with numbers, if a remainder is 0, then the divisor is a factor of the dividend. Example 1 Determining Factors by Division Divide to determine whether x − 1 is a factor of x2 − 3x +2. Solution Here x2 − 3x +2is the dividend and x − 1 is the divisor. Step 1 Set up the division as follows: divisor → x − 1 x2−3x+2 ← dividend Step 2 Divide the leading term of the dividend (x2) by the leading term of the divisor (x). The result (x)is the first term of the quotient, as illustrated below. x ← first term of quotient x − 1 x2 −3x+2 1.3. -
Lecture 19 1 Readings 2 Introduction 3 Shor's Order-Finding Algorithm
C/CS/Phys 191 Shor’s order (period) finding algorithm and factoring 11/01/05 Fall 2005 Lecture 19 1 Readings Benenti et al., Ch. 3.12 - 3.14 Stolze and Suter, Quantum Computing, Ch. 8.3 Nielsen and Chuang, Quantum Computation and Quantum Information, Ch. 5.2 - 5.3, 5.4.1 (NC use phase estimation for this, which we present in the next lecture) literature: Ekert and Jozsa, Rev. Mod. Phys. 68, 733 (1996) 2 Introduction With a fast algorithm for the Quantum Fourier Transform in hand, it is clear that many useful applications should be possible. Fourier transforms are typically used to extract the periodic components in functions, so this is an immediate one. One very important example is finding the period of a modular exponential function, which is also known as order-finding. This is a key element of Shor’s algorithm to factor large integers N. In Shor’s algorithm, the quantum algorithm for order-finding is combined with a series of efficient classical computational steps to make an algorithm that is overall polynomial in the input size 2 n = log2N, scaling as O(n lognloglogn). This is better than the best known classical algorithm, the number field sieve, which scales superpolynomially in n, i.e., as exp(O(n1/3(logn)2/3)). In this lecture we shall first present the quantum algorithm for order-finding and then summarize how this is used together with tools from number theory to efficiently factor large numbers. 3 Shor’s order-finding algorithm 3.1 modular exponentiation Recall the exponential function ax. -
Grade 7/8 Math Circles Modular Arithmetic the Modulus Operator
Faculty of Mathematics Centre for Education in Waterloo, Ontario N2L 3G1 Mathematics and Computing Grade 7/8 Math Circles April 3, 2014 Modular Arithmetic The Modulus Operator The modulo operator has symbol \mod", is written as A mod N, and is read \A modulo N" or "A mod N". • A is our - what is being divided (just like in division) • N is our (the plural is ) When we divide two numbers A and N, we get a quotient and a remainder. • When we ask for A ÷ N, we look for the quotient of the division. • When we ask for A mod N, we are looking for the remainder of the division. • The remainder A mod N is always an integer between 0 and N − 1 (inclusive) Examples 1. 0 mod 4 = 0 since 0 ÷ 4 = 0 remainder 0 2. 1 mod 4 = 1 since 1 ÷ 4 = 0 remainder 1 3. 2 mod 4 = 2 since 2 ÷ 4 = 0 remainder 2 4. 3 mod 4 = 3 since 3 ÷ 4 = 0 remainder 3 5. 4 mod 4 = since 4 ÷ 4 = 1 remainder 6. 5 mod 4 = since 5 ÷ 4 = 1 remainder 7. 6 mod 4 = since 6 ÷ 4 = 1 remainder 8. 15 mod 4 = since 15 ÷ 4 = 3 remainder 9.* −15 mod 4 = since −15 ÷ 4 = −4 remainder Using a Calculator For really large numbers and/or moduli, sometimes we can use calculators to quickly find A mod N. This method only works if A ≥ 0. Example: Find 373 mod 6 1. Divide 373 by 6 ! 2. Round the number you got above down to the nearest integer ! 3. -
Basic Math Quick Reference Ebook
This file is distributed FREE OF CHARGE by the publisher Quick Reference Handbooks and the author. Quick Reference eBOOK Click on The math facts listed in this eBook are explained with Contents or Examples, Notes, Tips, & Illustrations Index in the in the left Basic Math Quick Reference Handbook. panel ISBN: 978-0-615-27390-7 to locate a topic. Peter J. Mitas Quick Reference Handbooks Facts from the Basic Math Quick Reference Handbook Contents Click a CHAPTER TITLE to jump to a page in the Contents: Whole Numbers Probability and Statistics Fractions Geometry and Measurement Decimal Numbers Positive and Negative Numbers Universal Number Concepts Algebra Ratios, Proportions, and Percents … then click a LINE IN THE CONTENTS to jump to a topic. Whole Numbers 7 Natural Numbers and Whole Numbers ............................ 7 Digits and Numerals ........................................................ 7 Place Value Notation ....................................................... 7 Rounding a Whole Number ............................................. 8 Operations and Operators ............................................... 8 Adding Whole Numbers................................................... 9 Subtracting Whole Numbers .......................................... 10 Multiplying Whole Numbers ........................................... 11 Dividing Whole Numbers ............................................... 12 Divisibility Rules ............................................................ 13 Multiples of a Whole Number ....................................... -
Number Theory
CS 5002: Discrete Structures Fall 2018 Lecture 5: October 4, 2018 1 Instructors: Tamara Bonaci, Adrienne Slaugther Disclaimer: These notes have not been subjected to the usual scrutiny reserved for formal publications. They may be distributed outside this class only with the permission of the Instructor. Number Theory Readings for this week: Rosen, Chapter 4.1, 4.2, 4.3, 4.4 5.1 Overview 1. Review: set theory 2. Review: matrices and arrays 3. Number theory: divisibility and modular arithmetic 4. Number theory: prime numbers and greatest common divisor (gcd) 5. Number theory: solving congruences 6. Number theory: modular exponentiation and Fermat's little theorem 5.2 Introduction In today's lecture, we will dive into the branch of mathematics, studying the set of integers and their properties, known as number theory. Number theory has very important practical implications in computer science, but also in our every day life. For example, secure online communication, as we know it today, would not be possible without number theory because many of the encryption algorithms used to enable secure communication rely heavily of some famous (and in some cases, very old) results from number theory. We will first introduce the notion of divisibility of integers. From there, we will introduce modular arithmetic, and explore and prove some important results about modular arithmetic. We will then discuss prime numbers, and show that there are infinitely many primes. Finaly, we will explain how to solve linear congruences, and systems of linear congruences. 5-1 5-2 Lecture 5: October 4, 2018 5.3 Review 5.3.1 Set Theory In the last lecture, we talked about sets, and some of their properties.