Number Theory and the RSA Public Key Cryptosystem#
Author: Minh Van Nguyen <nguyenminh2@gmail.com>
This tutorial uses Sage to study elementary number theory and the RSA public key cryptosystem. A number of Sage commands will be presented that help us to perform basic number theoretic operations such as greatest common divisor and Euler’s phi function. We then present the RSA cryptosystem and use Sage’s built-in commands to encrypt and decrypt data via the RSA algorithm. Note that this tutorial on RSA is for pedagogy purposes only. For further details on cryptography or the security of various cryptosystems, consult specialized texts such as [MenezesEtAl1996], [Stinson2006], and [TrappeWashington2006].
Elementary number theory#
We first review basic concepts from elementary number theory, including the notion of primes, greatest common divisors, congruences and Euler’s phi function. The number theoretic concepts and Sage commands introduced will be referred to in later sections when we present the RSA algorithm.
Prime numbers#
Public key cryptography uses many fundamental concepts from number
theory, such as prime numbers and greatest common divisors. A
positive integer \(n > 1\) is said to be prime if its factors are
exclusively 1 and itself. In Sage, we can obtain the first 20 prime
numbers using the command primes_first_n:
sage: primes_first_n(20)
[2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41, 43, 47, 53, 59, 61, 67, 71]
>>> from sage.all import *
>>> primes_first_n(Integer(20))
[2, 3, 5, 7, 11, 13, 17, 19, 23, 29, 31, 37, 41, 43, 47, 53, 59, 61, 67, 71]
Greatest common divisors#
Let \(a\) and \(b\) be integers, not both zero. Then the greatest common
divisor (GCD) of \(a\) and \(b\) is the largest positive integer which is
a factor of both \(a\) and \(b\). We use \(\gcd(a,b)\) to denote this
largest positive factor. One can extend this definition by setting
\(\gcd(0,0) = 0\). Sage uses gcd(a, b) to denote the GCD of \(a\)
and \(b\). The GCD of any two distinct primes is 1, and the GCD of 18
and 27 is 9.
sage: gcd(3, 59)
1
sage: gcd(18, 27)
9
>>> from sage.all import *
>>> gcd(Integer(3), Integer(59))
1
>>> gcd(Integer(18), Integer(27))
9
If \(\gcd(a,b) = 1\), we say that \(a\) is coprime (or relatively prime) to \(b\). In particular, \(\gcd(3, 59) = 1\) so 3 is coprime to 59 and vice versa.
Congruences#
When one integer is divided by a non-zero integer, we usually get a remainder. For example, upon dividing 23 by 5, we get a remainder of 3; when 8 is divided by 5, the remainder is again 3. The notion of congruence helps us to describe the situation in which two integers have the same remainder upon division by a non-zero integer. Let \(a,b,n \in \ZZ\) such that \(n \neq 0\). If \(a\) and \(b\) have the same remainder upon division by \(n\), then we say that \(a\) is congruent to \(b\) modulo \(n\) and denote this relationship by
This definition is equivalent to saying that \(n\) divides the
difference of \(a\) and \(b\), i.e. \(n \;|\; (a - b)\). Thus
\(23 \equiv 8 \pmod{5}\) because when both 23 and 8 are divided by 5, we
end up with a remainder of 3. The command mod allows us to
compute such a remainder:
sage: mod(23, 5)
3
sage: mod(8, 5)
3
>>> from sage.all import *
>>> mod(Integer(23), Integer(5))
3
>>> mod(Integer(8), Integer(5))
3
Euler’s phi function#
Consider all the integers from 1 to 20, inclusive. List all those integers that are coprime to 20. In other words, we want to find those integers \(n\), where \(1 \leq n \leq 20\), such that \(\gcd(n,20) = 1\). The latter task can be easily accomplished with a little bit of Sage programming:
sage: L = []
sage: for n in range(1, 21):
....: if gcd(n, 20) == 1:
....: L.append(n)
sage: L
[1, 3, 7, 9, 11, 13, 17, 19]
>>> from sage.all import *
>>> L = []
>>> for n in range(Integer(1), Integer(21)):
... if gcd(n, Integer(20)) == Integer(1):
... L.append(n)
>>> L
[1, 3, 7, 9, 11, 13, 17, 19]
The above programming statements can be saved to a text file called,
say, /home/mvngu/totient.sage, organizing it as follows to enhance
readability.
L = []
for n in range(1, 21):
if gcd(n, 20) == 1:
L.append(n)
L
We refer to totient.sage as a Sage script, just as one would refer
to a file containing Python code as a Python script. We use 4 space
indentations, which is a coding convention in Sage as well as Python
programming, instead of tabs.
The command load can be used to read the file containing our
programming statements into Sage and, upon loading the content of the
file, have Sage execute those statements:
load("/home/mvngu/totient.sage")
[1, 3, 7, 9, 11, 13, 17, 19]
From the latter list, there are 8 integers in the closed interval \([1, 20]\) that are coprime to 20. Without explicitly generating the list
1 3 7 9 11 13 17 19
how can we compute the number of integers in \([1, 20]\) that are
coprime to 20? This is where Euler’s phi function comes in handy.
Let \(n \in \ZZ\) be positive. Then Euler’s phi function counts the
number of integers \(a\), with \(1 \leq a \leq n\), such that
\(\gcd(a,n) = 1\). This number is denoted by \(\varphi(n)\). Euler’s phi
function is sometimes referred to as Euler’s totient function, hence
the name totient.sage for the above Sage script. The command
euler_phi implements Euler’s phi function. To compute
\(\varphi(20)\) without explicitly generating the above list, we proceed
as follows:
sage: euler_phi(20)
8
>>> from sage.all import *
>>> euler_phi(Integer(20))
8
How to keep a secret?#
Cryptography is the science (some might say art) of concealing data. Imagine that we are composing a confidential email to someone. Having written the email, we can send it in one of two ways. The first, and usually convenient, way is to simply press the send button and not care about how our email will be delivered. Sending an email in this manner is similar to writing our confidential message on a postcard and post it without enclosing our postcard inside an envelope. Anyone who can access our postcard can see our message. On the other hand, before sending our email, we can scramble the confidential message and then press the send button. Scrambling our message is similar to enclosing our postcard inside an envelope. While not 100% secure, at least we know that anyone wanting to read our postcard has to open the envelope.
In cryptography parlance, our message is called plaintext. The process of scrambling our message is referred to as encryption. After encrypting our message, the scrambled version is called ciphertext. From the ciphertext, we can recover our original unscrambled message via decryption. The following figure illustrates the processes of encryption and decryption. A cryptosystem is comprised of a pair of related encryption and decryption processes.
+ ---------+ encrypt +------------+ decrypt +-----------+
| plaintext| -----------> | ciphertext | -----------> | plaintext |
+----------+ +------------+ +-----------+
The following table provides a very simple method of scrambling a message written in English and using only upper case letters, excluding punctuation characters.
+----------------------------------------------------+
| A B C D E F G H I J K L M |
| 65 66 67 68 69 70 71 72 73 74 75 76 77 |
+----------------------------------------------------+
| N O P Q R S T U V W X Y Z |
| 78 79 80 81 82 83 84 85 86 87 88 89 90 |
+----------------------------------------------------+
Formally, let
be the set of capital letters of the English alphabet. Furthermore, let
be the American Standard Code for Information Interchange (ASCII) encodings of the upper case English letters. Then the above table explicitly describes the mapping \(f: \Sigma \longrightarrow \Phi\). (For those familiar with ASCII, \(f\) is actually a common process for encoding elements of \(\Sigma\), rather than a cryptographic “scrambling” process per se.) To scramble a message written using the alphabet \(\Sigma\), we simply replace each capital letter of the message with its corresponding ASCII encoding. However, the scrambling process described in the above table provides, cryptographically speaking, very little to no security at all and we strongly discourage its use in practice.
Keeping a secret with two keys#
The Rivest, Shamir, Adleman (RSA) cryptosystem is an example of a public key cryptosystem. RSA uses a public key to encrypt messages and decryption is performed using a corresponding private key. We can distribute our public keys, but for security reasons we should keep our private keys to ourselves. The encryption and decryption processes draw upon techniques from elementary number theory. The algorithm below is adapted from page 165 of [TrappeWashington2006]. It outlines the RSA procedure for encryption and decryption.
Choose two primes \(p\) and \(q\) and let \(n = pq\).
Let \(e \in \ZZ\) be positive such that \(\gcd \big( e, \varphi(n) \big) = 1\).
Compute a value for \(d \in \ZZ\) such that \(de \equiv 1 \pmod{\varphi(n)}\).
Our public key is the pair \((n, e)\) and our private key is the triple \((p,q,d)\).
For any non-zero integer \(m < n\), encrypt \(m\) using \(c \equiv m^e \pmod{n}\).
Decrypt \(c\) using \(m \equiv c^d \pmod{n}\).
The next two sections will step through the RSA algorithm, using Sage to generate public and private keys, and perform encryption and decryption based on those keys.
Generating public and private keys#
Positive integers of the form \(M_m = 2^m - 1\) are called
Mersenne numbers. If \(p\) is prime and \(M_p = 2^p - 1\) is also
prime, then \(M_p\) is called a Mersenne prime. For example, 31
is prime and \(M_{31} = 2^{31} - 1\) is a Mersenne prime, as can be
verified using the command is_prime(p). This command returns
True if its argument p is precisely a prime number;
otherwise it returns False. By definition, a prime must be a
positive integer, hence is_prime(-2) returns False
although we know that 2 is prime. Indeed, the number
\(M_{61} = 2^{61} - 1\) is also a Mersenne prime. We can use
\(M_{31}\) and \(M_{61}\) to work through step 1 in the RSA algorithm:
sage: p = (2^31) - 1
sage: is_prime(p)
True
sage: q = (2^61) - 1
sage: is_prime(q)
True
sage: n = p * q ; n
4951760154835678088235319297
>>> from sage.all import *
>>> p = (Integer(2)**Integer(31)) - Integer(1)
>>> is_prime(p)
True
>>> q = (Integer(2)**Integer(61)) - Integer(1)
>>> is_prime(q)
True
>>> n = p * q ; n
4951760154835678088235319297
A word of warning is in order here. In the above code example, the choice of \(p\) and \(q\) as Mersenne primes, and with so many digits far apart from each other, is a very bad choice in terms of cryptographic security. However, we shall use the above chosen numeric values for \(p\) and \(q\) for the remainder of this tutorial, always bearing in mind that they have been chosen for pedagogy purposes only. Refer to [MenezesEtAl1996], [Stinson2006], and [TrappeWashington2006] for in-depth discussions on the security of RSA, or consult other specialized texts.
For step 2, we need to find a positive integer that is coprime to
\(\varphi(n)\). The set of integers is implemented within the Sage
module sage.rings.integer_ring. Various operations on
integers can be accessed via the ZZ.* family of functions.
For instance, the command ZZ.random_element(n) returns a
pseudo-random integer uniformly distributed within the closed interval
\([0, n-1]\).
We can compute the value \(\varphi(n)\) by calling the sage function
euler_phi(n), but for arbitrarily large prime numbers \(p\) and \(q\),
this can take an enormous amount of time. Indeed, the private key
can be quickly deduced from the public key once you know \(\varphi(n)\),
so it is an important part of the security of the RSA cryptosystem that
\(\varphi(n)\) cannot be computed in a short time, if only \(n\) is known.
On the other hand, if the private key is available, we can compute
\(\varphi(n)=(p-1)(q-1)\) in a very short time.
Using a simple programming loop, we can compute the required value of \(e\) as follows:
sage: p = (2^31) - 1
sage: q = (2^61) - 1
sage: n = p * q
sage: phi = (p - 1)*(q - 1); phi
4951760152529835076874141700
sage: e = ZZ.random_element(phi)
sage: while gcd(e, phi) != 1:
....: e = ZZ.random_element(phi)
...
sage: e # random
1850567623300615966303954877
sage: e < n
True
>>> from sage.all import *
>>> p = (Integer(2)**Integer(31)) - Integer(1)
>>> q = (Integer(2)**Integer(61)) - Integer(1)
>>> n = p * q
>>> phi = (p - Integer(1))*(q - Integer(1)); phi
4951760152529835076874141700
>>> e = ZZ.random_element(phi)
>>> while gcd(e, phi) != Integer(1):
... e = ZZ.random_element(phi)
...
>>> e # random
1850567623300615966303954877
>>> e < n
True
As e is a pseudo-random integer, its numeric value changes
after each execution of e = ZZ.random_element(phi).
To calculate a value for d in step 3 of the RSA algorithm, we use
the extended Euclidean algorithm. By definition of congruence,
\(de \equiv 1 \pmod{\varphi(n)}\) is equivalent to
where \(k \in \ZZ\). From steps 1 and 2, we already know the numeric
values of \(e\) and \(\varphi(n)\). The extended Euclidean algorithm
allows us to compute \(d\) and \(-k\). In Sage, this can be accomplished
via the command xgcd. Given two integers \(x\) and \(y\),
xgcd(x, y) returns a 3-tuple (g, s, t) that satisfies
the Bézout identity \(g = \gcd(x,y) = sx + ty\). Having computed a
value for d, we then use the command
mod(d*e, phi) to check that d*e is indeed congruent
to 1 modulo phi.
sage: n = 4951760154835678088235319297
sage: e = 1850567623300615966303954877
sage: phi = 4951760152529835076874141700
sage: bezout = xgcd(e, phi); bezout # random
(1, 4460824882019967172592779313, -1667095708515377925087033035)
sage: d = Integer(mod(bezout[1], phi)) ; d # random
4460824882019967172592779313
sage: mod(d * e, phi)
1
>>> from sage.all import *
>>> n = Integer(4951760154835678088235319297)
>>> e = Integer(1850567623300615966303954877)
>>> phi = Integer(4951760152529835076874141700)
>>> bezout = xgcd(e, phi); bezout # random
(1, 4460824882019967172592779313, -1667095708515377925087033035)
>>> d = Integer(mod(bezout[Integer(1)], phi)) ; d # random
4460824882019967172592779313
>>> mod(d * e, phi)
1
Thus, our RSA public key is
and our corresponding private key is
Encryption and decryption#
Suppose we want to scramble the message HELLOWORLD using RSA
encryption. From the above ASCII table, our message maps to integers
of the ASCII encodings as given below.
+----------------------------------------+
| H E L L O W O R L D |
| 72 69 76 76 79 87 79 82 76 68 |
+----------------------------------------+
Concatenating all the integers in the last table, our message can be represented by the integer
There are other more cryptographically secure means for representing our message as an integer. The above process is used for demonstration purposes only and we strongly discourage its use in practice. In Sage, we can obtain an integer representation of our message as follows:
sage: m = "HELLOWORLD"
sage: m = [ord(x) for x in m]; m
[72, 69, 76, 76, 79, 87, 79, 82, 76, 68]
sage: m = ZZ(list(reversed(m)), 100) ; m
72697676798779827668
>>> from sage.all import *
>>> m = "HELLOWORLD"
>>> m = [ord(x) for x in m]; m
[72, 69, 76, 76, 79, 87, 79, 82, 76, 68]
>>> m = ZZ(list(reversed(m)), Integer(100)) ; m
72697676798779827668
To encrypt our message, we raise \(m\) to the power of \(e\) and reduce
the result modulo \(n\). The command mod(a^b, n) first computes
a^b and then reduces the result modulo n. If the exponent
b is a “large” integer, say with more than 20 digits, then
performing modular exponentiation in this naive manner takes quite
some time. Brute force (or naive) modular exponentiation is
inefficient and, when performed using a computer, can quickly
consume a huge quantity of the computer’s memory or result in overflow
messages. For instance, if we perform naive modular exponentiation
using the command mod(m^e, n), where m, n and e are as
given above, we would get an error message similar to the following:
mod(m^e, n)
Traceback (most recent call last)
...<ipython console> in <module>()
.../sage/rings/integer.so
in sage.rings.integer.Integer.__pow__ (sage/rings/integer.c:9650)()
RuntimeError: exponent must be at most 2147483647
There is a trick to efficiently perform modular exponentiation, called
the method of repeated squaring, cf. page 879 of [CormenEtAl2001].
Suppose we want to compute \(a^b \mod n\). First, let
\(d \mathrel{\mathop:}= 1\) and obtain the binary representation of \(b\),
say \((b_1, b_2, \dots, b_k)\) where each \(b_i \in \ZZ/2\ZZ\). For
\(i \mathrel{\mathop:}= 1, \dots, k\), let
\(d \mathrel{\mathop:}= d^2 \mod n\) and if \(b_i = 1\) then let
\(d \mathrel{\mathop:}= da \mod n\). This algorithm is implemented in
the function power_mod. We now use the function power_mod to
encrypt our message:
sage: m = 72697676798779827668
sage: e = 1850567623300615966303954877
sage: n = 4951760154835678088235319297
sage: c = power_mod(m, e, n); c
630913632577520058415521090
>>> from sage.all import *
>>> m = Integer(72697676798779827668)
>>> e = Integer(1850567623300615966303954877)
>>> n = Integer(4951760154835678088235319297)
>>> c = power_mod(m, e, n); c
630913632577520058415521090
Thus \(c = 630913632577520058415521090\) is the ciphertext. To recover
our plaintext, we raise c to the power of d and reduce the
result modulo n. Again, we use modular exponentiation via
repeated squaring in the decryption process:
sage: m = 72697676798779827668
sage: c = 630913632577520058415521090
sage: d = 4460824882019967172592779313
sage: n = 4951760154835678088235319297
sage: power_mod(c, d, n)
72697676798779827668
sage: power_mod(c, d, n) == m
True
>>> from sage.all import *
>>> m = Integer(72697676798779827668)
>>> c = Integer(630913632577520058415521090)
>>> d = Integer(4460824882019967172592779313)
>>> n = Integer(4951760154835678088235319297)
>>> power_mod(c, d, n)
72697676798779827668
>>> power_mod(c, d, n) == m
True
Notice in the last output that the value 72697676798779827668 is the same as the integer that represents our original message. Hence we have recovered our plaintext.
Acknowledgements#
2009-07-25: Ron Evans (Department of Mathematics, UCSD) reported a typo in the definition of greatest common divisors. The revised definition incorporates his suggestions.
2008-11-04: Martin Albrecht (Information Security Group, Royal Holloway, University of London), John Cremona (Mathematics Institute, University of Warwick) and William Stein (Department of Mathematics, University of Washington) reviewed this tutorial. Many of their invaluable suggestions have been incorporated into this document.
Bibliography#
T. H. Cormen, C. E. Leiserson, R. L. Rivest, and C. Stein. Introduction to Algorithms. The MIT Press, USA, 2nd edition, 2001.
A. J. Menezes, P. C. van Oorschot, and S. A. Vanstone. Handbook of Applied Cryptography. CRC Press, Boca Raton, FL, USA, 1996.