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University of Capital University of Economics and

Business Dept. of Computer Science

IT222 Applications of Discrete

Structures Instructor Xiaoting Zhao

Module 9 Applications of Number Theory

- Rosen 5th ed., 2.4-2.6
- 33 slides, 1.5 lectures

Applications from 2.4

- Hashing Functions (hashes)
- Pseudorandom Numbers
- Cryptology

Hashing Functions

- Also known as
- hash functions, hash codes, or just hashes.
- Two major uses
- Indexing hash tables
- Data structures which support O(1)-time access.
- Creating short unique IDs for long documents.
- Used in digital signatures the short ID can be

signed, rather than the long document.

Hash Function Requirements

- A hash function hA?B is a map from a set A to a

smaller set B (i.e., A B). - An effective hash function should have the

following properties - It should cover (be onto) its codomain B.
- It should be efficient to calculate
- ideally, it should take O(log A) operations.
- The cardinality of each preimage of an element of

B should be about the same. - ?b1,b2?B h-1(b1) h-1(b2)
- That is, elements of B should be generated with

roughly uniform probability. - Ideally, the map should appear random, so that

clearly similar elements of A are not likely to

map to the same (or similar) elements of B. - Furthermore, for a cryptographically secure hash

function - Given an element b?B, the problem of finding an

a?A such that h(a)b should have average-case

time complexity of O(Bc) for some cgt0. - This ensures that it would take exponential time

in the length of an ID for an opponent to fake

a different document having the same ID.

A Simple Hash Using mod

- Let the domain and codomain be the sets of all

natural numbers below certain bounds - A a?N a lt alim, B b?N b lt

blim - Then an acceptable (although not great) hash

function from A to B (when alimblim) is h(a) a

mod blim. - It has the following desirable hash function

properties - It covers or is onto its codomain B (its range is

B). - When alim blim, then each b?B has a preimage of

about the same size, - Specifically, h-1(b) ?alim/blim? or

?alim/blim?. - However, it has the following limitations
- It is not very random.
- For example, if all as encountered happen to

have the same residue mod blim, they will all map

to the same b! - It is definitely not cryptographically secure.
- Given a b, it is easy to generate as that map to

it - Namely, we know that for any n?N, h(b nblim)

b.

Hash Table Characteristics

- A hash table is a type of container data

structure often used for representing a set. - It has these properties
- Every element e stored is assigned a unique key

k(e) - It identifies the element and can be easily

calculated from e. - It supports the following operations with O(1)

expected (average case) time - Looking up an element e given its key k.
- Adding a new element e to the hash table.
- Deleting an element e from the hash table.
- Listing the next element, in an enumeration of

all elements.

Simple Hash Table Implementation

- There is an array eb with blim locations for

storing elements. - procedure store(e element) a k(e)

calculate key a of element b h(a)

hash the key to a storage location

b while (eb ? null ? k(eb) ? a)

not e or empty b (b1) mod blim

go to next loc., circularly if eb null

then eb e store it if it wasnt

there - procedure lookup(a?A desired elements key) b

h(a) hash

it to a location b while (eb ? null ? k(eb) ? a)

not e or empty b (b1) mod

blim go to next loc., circularly

if k(eb) a then return eb else return null

Exercise What happens when the array is

full? How might you fix this problem?

Digital Signature Application

- Many digital signature systems use a

cryptographically secure (but public) hash

function h which maps arbitrarily long documents

down to fixed-length (e.g., 1,024-bit)

fingerprint strings. - Document signing procedure
- Given a document a to sign, quickly compute its

hash b h(a). - Compute a certain function c f(b) that is known

only to the signer - This step is generally slow, so we dont want to

apply it to the whole document. - Deliver the original document together with the

digital signature c. - Signature verification procedure
- Given a document a and signature c, quickly find

as hash b h(a). - Compute b' f -1(c). (Possible if fs inverse f

-1 is made public.) - Compare b to b' if they are equal then the

signature is valid. - Note that if h were not cryptographically secure,

then an opponent could easily forge a different

document a' that hashes to the same value b, and

thereby attach someones digital signature to a

different document than they actually signed, and

fool the verifier.

Pseudo-random Numbers

- Numbers that are generated deterministically, but

that appear random for all practical purposes. - Used in many applications, such as
- Hash functions
- Simulations, games, graphics
- Cryptographic algorithms
- One simple common pseudo-random number generating

procedure - The linear congruential method
- Uses the mod operator

Linear Congruential Method

- Requires four natural numbers
- The modulus m, the multiplier a, the increment c,

and the seed x0. - Where 2 a lt m, 0 c lt m, 0 x0 lt m.
- Generates the pseudo-random sequence xn with 0

xn lt m, via the following - xn1 (axn c) mod m.
- Tends to work best when a,c,m are prime, or at

least relatively prime. - If c0, the method is called a pure

multiplicative generator.

Example

- Let modulus m 1,000 2353.
- To generate outputs in the range 0-999.
- Pick increment c 467 (prime), multiplier a

293 (also prime), seed x0 426. - Then we get the pseudo-random sequence
- x1 (ax0 c) mod m 285
- x2 (ax1 c) mod m 972
- x3 (ax2 c) mod m 263 and so on

Note alternating odd and even values results

from m being even

Cryptology

- This is the study of secret (coded) messages. It

includes - Cryptography Methods for encrypting and

decrypting secret (coded) messages. - Cryptanalysis Methods for code-breaking.
- Some simple early codes include Caesars cipher
- Associate each letter w. its position 0-25 in the

alphabet - Encrypt by replacing letter n by letter (n3) mod

26. - Decrypt by replacing n with (n-3) mod 26.
- This a simple example of a shift cipher (nk) mod

m. - Can generalize this to affine transforms (linear

1-1 transforms) (an b) mod 26, e.g., (7n3) mod

26. - This is still very insecure however!

Modular Exponentiation Problem (from 2.5)

- Problem Given large integers b (base), n

(exponent), and m (modulus), efficiently compute

bn mod m. - Note that bn itself may be completely infeasible

to compute and store directly. - E.g. if n is a 1,000-bit number, then bn itself

will have far more digits than there are atoms in

the universe! - Yet, this is a type of calculation that is

commonly required in modern cryptographic

algorithms!

Modular Exponentiation

- procedure modularExponentiation(b integer, n

(nk-1 n0)2, m positive integers) x 1

result will be accumulated here b2i b mod m

mod m i0 initially for i 0 to k-1

go thru all k bits of n if ni 1 then x

(xb2i) mod m b2i (b2ib2i) mod m return x

Why that Algorithm Works

The binary expansion of n

- Note that
- We can compute b to various powers of 2 by

repeated squaring. - Then multiply them into the partial product, or

not, depending on whether the corresponding ni

bit is 1. - Crucially, we can do the mod m operations as we

go along, because of the various identity laws of

modular arithmetic. All the numbers stay small.

b1 b

2.6 More on Applications

- Misc. useful results
- Linear congruences
- Chinese Remainder Theorem
- Computer arithmetic w. large integers
- Pseudoprimes
- Fermats Little Theorem
- Public Key Cryptography
- The Rivest-Shamir-Adleman (RSA) cryptosystem

Some Misc. Results

- Theorem 0 (Euclid)
- ?a,b gt 0 gcd(a,b) gcd(b, a mod b)
- Theorem 1
- ?a,bgt0 ?s,t gcd(a,b) sa tb
- Lemma 1
- ?a,b,cgt0 gcd(a,b)1 ? a bc ? ac
- Lemma 2
- If p is prime and pa1a2
an (integers ai) then

?i pai. - Theorem 2
- If ac bc (mod m) and gcd(c,m)1, then a b

(mod m).

Proof Euclids Algorithm Works

- Theorem 0 gcd(a,b) gcd(b,c) if c a mod b.
- Proof First, c a mod b implies ?t a bt

c. Let g gcd(a,b), and g' gcd(b,c). Since

ga and gb (thus gbt) we know g(a-bt), i.e.

gc. Since gb ? gc, it follows that g

gcd(b,c) g'. Now, since g'b (thus g'bt) and

g'c, we know g'(btc), i.e., g'a. Since g'a

? g'b, it follows that g' gcd(a,b) g. Since

we have shown that both gg' and g'g, it must be

the case that gg'.

Proof of Theorem 1

- Theorem 1 ?ab0 ?st gcd(a,b) sa tb
- Proof (By induction over the value of the larger

argument a.) From theorem 0, we know that

gcd(a,b) gcd(b,c) if c a mod b, in which case

a kb c for some integer k, so c a - kb.

Now, since blta and cltb, by inductive hypothesis,

we can assume that ?uv gcd(b,c) ub vc.

Substituting for c, this is ubv(a-kb), which we

can regroup to get va (u-vk)b. So now let s

v, and let t u-vk, and were finished. The

base case is solved by s1, t0, which works for

gcd(a,0), or if ab originally.

Proof of Lemma 1

- Lemma 1 gcd(a,b)1 ? abc ? ac
- Proof Applying theorem 1, ?st satb1.

Multiplying through by c, we have that sac tbc

c. Since abc is given, we know that atbc,

and obviously asac. Thus (using the theorem on

p.154), it follows that a(sactbc) in other

words, that ac.

Proof of Lemma 2

- Lemma 2 Prime pa1 an ? ?i pai.
- Proof If n1, this is immediate since pa0 ?

pa0. Suppose the lemma is true for all nltk and

suppose pa1 ak. If pm where ma1 ak-1 then we

have it inductively. Otherwise, we have pmak

but (pm). Since m is not a multiple of p, and

p has no factors, m has no common factors with p,

thus gcd(m,p)1. So by applying lemma 1, pak.

Uniqueness of Prime Factorizations

The hard part of proving the Fundamental

Theorem of Arithmetic.

- The prime factorization of any number n is

unique. - Theorem If p1
ps q1
qt are equal products of

two nondecreasing sequences of primes, then st

and pi qi for all i. - Proof Assume (without loss of generality) that

all primes in common have already been divided

out, so that ?ij pi ? qj. But since p1 ps

q1 qt, we have that p1q1 qt, since p1(p2 ps)

q1 qt. Then applying lemma 2, ?j p1qj. Since

qj is prime, it has no divisors other than itself

and 1, so it must be that piqj. This contradicts

the assumption ?ij pi ? qj. The only resolution

is that after the common primes are divided out,

both lists of primes were empty, so we couldnt

pick out p1. In other words, the two lists must

have been identical to begin with!

Proof of Theorem 2

- Theorem 2 If ac bc (mod m) and gcd(c,m)1,

then a b (mod m). - Proof Since ac bc (mod m), this means m

ac-bc. Factoring the right side, we getr m c(a

- b). Since gcd(c,m)1, lemma 1 implies that m

a-b, in other words, that a b (mod m).

An Application of Theorem 2

- Suppose we have a pure-multiplicative

pseudo-random number generator xn using a

multiplier a that is relatively prime to the

modulus m. - Then the transition function that maps from xn to

xn1 is bijective. - Because if xn1 axn mod m axn' mod m, then

xnxn' (by theorem 2). - This in turn implies that the sequence of numbers

generated cannot repeat until the original number

is re-encountered. - And this means that on average, we will visit a

large fraction of the numbers in the range 0 to

m-1 before we begin to repeat! - Intuitively, because the chance of hitting the

first number in the sequence is 1/m, so it will

take T(m) tries on average to get to it. - Thus, the multiplier a ought to be chosen

relatively prime to the modulus, to avoid

repeating too soon.

Linear Congruences, Inverses

- A congruence of the form ax b (mod m) is called

a linear congruence. - To solve the congruence is to find the xs that

satisfy it. - An inverse of a, modulo m is any integer a' such

that a'a 1 (mod m). - If we can find such an a', notice that we can

then solve axb by multiplying through by it,

giving a'axa'b, thus 1xa'b, thus xa'b. - Theorem 3 If gcd(a,m)1 and mgt1, then a has a

unique (modulo m) inverse a'. - Proof By theorem 1, ?st satm 1, so satm 1

(mod m). Since tm0 (mod m), sa1 (mod m). Thus

s is an inverse of a (mod m). Theorem 2

guarantees that if rasa1 then rs, thus this

inverse is unique mod m. (All inverses of a are

in the same congruence class as s.)

Chinese Remainder Theorem

- Theorem (Chinese remainder theorem.) Let

m1, ,mn gt 0 be relatively prime. Then the system

of equations x ai (mod mi) (for i1 to n) has a

unique solution modulo m m1 mn. - Proof Let Mi m/mi. (Thus gcd(mi, Mi)1.) So by

theorem 3, ?yiMi' such that yiMi1 (mod mi).

Now let x ?i aiyiMi. Since miMk for k?i, Mk0

(mod mi), so xaiyiMiai (mod mi). Thus, the

congruences hold. (Uniqueness is an exercise.) ?

Computer Arithmetic w. Large Ints

- By Chinese Remainder Theorem, an integer a where

0altm?mi, gcd(mi,mj?i)1, can be represented by

as residues mod mi - (a mod m1, a mod m2, , a mod mn)
- To perform arithmetic upon large integers

represented in this way, - Simply perform ops on these separate residues!
- Each of these might be done in a single machine

op. - The ops may be easily parallelized on a vector

machine. - Works so long as m gt the desired result.

Computer Arithmetic Example

- For example, the following numbers are relatively

prime - m1 225-1 33,554,431 31 601 1,801
- m2 227-1 134,217,727 7 73 262,657
- m3 228-1 268,435,455 3 5 29 43 113

127 - m4 229-1 536,870,911 233 1,103 2,089
- m5 231-1 2,147,483,647 (prime)
- Thus, we can uniquely represent all numbers up to

m ?mi 1.41042 2139.5 by their residues ri

modulo these five mi. - E.g., 1030 (r1 20,900,945 r2

18,304,504 r3 65,829,085

r4 516,865,185 r5 1,234,980,730) - To add two such numbers in this representation,
- Just add their corresponding residues using

machine-native 32-bit integers. - Take the result mod 2k-1
- If result is the appropriate 2k-1 value,

subtract out 2k-1 - Or just take the low k bits and add 1.
- Note No carries are needed between the different

pieces!

Pseudoprimes

- Ancient Chinese mathematicians noticed that

whenever n is prime, 2n-11 (mod n). - Some also claimed that the converse was true.
- However, it turns out that the converse is not

true! - If 2n-11 (mod n), it doesnt follow that n is

prime. - For example, 3411131, but 23401 (mod 341).
- Composites n with this property are called

pseudoprimes. - More generally, if bn-11 (mod n) and n is

composite, then n is called a pseudoprime to the

base b.

Carmichael numbers

- These are sort of the ultimate pseudoprimes.
- A Carmichael number is a composite n such that

bn-11 (mod n) for all b relatively prime to n. - The smallest few are 561, 1105, 1729, 2465, 2821,

6601, 8911, 10585, 15841, 29341. - Well, so what? Who cares?
- Exercise for the student Do some research and

find me a useful interesting application of

Carmichael numbers. (Extra credit.)

Fermats Little Theorem

- Fermat generalized the ancient observation that

2p-11 (mod p) for primes p to the following more

general theorem - Theorem (Fermats Little Theorem.)
- If p is prime and a is any non-negative integer,

then apa (mod p). - Furthermore, if (pa), then ap-11 (mod p).

Public Key Cryptography

- In private key cryptosystems, the same secret

key string is used to both encode and decode

messages. - This raises the problem of how to securely

communicate the key strings. - In public key cryptosystems, instead there are

two complementary keys. - One key decrypts the messages that the other one

encrypts. - This means that one key (the public key) can be

made public, while the other (the private key)

can be kept secret from everyone. - Messages to the owner can be encrypted by anyone

using the public key, but can only be decrypted

by the owner using the private key. - Like having a private lock-box with a slot for

messages. - Or, the owner can encrypt a message with their

private key, and then anyone can decrypt it, and

know that only the owner could have encrypted it. - This is the basis of digital signature systems.
- The most famous public-key cryptosystem is RSA.
- It is based entirely on number theory!

Rivest-Shamir-Adleman (RSA)

- The private key consists of
- A pair p,q of large random prime numbers, and
- An exponent e that is relatively prime to

(p-1)(q-1). - The public key consists of
- The product n pq (but not p and q), and
- d, an inverse of e modulo (p-1)(q-1), but not e

itself. - To encrypt a message encoded as an integer Mltn
- Compute C Me mod n.
- To decrypt the encoded message C,
- Compute M Cd mod n.

Why RSA Works

- Theorem (Correctness of RSA) (Me)d M (mod n).

Proof - By the definition of d, we know that de 1 mod

(p-1)(q-1). - Thus by the definition of modular congruence, ?k

de 1 k(p-1)(q-1). - So, the result of decryption is Cd (Me)d Mde

M1k(p-1)(q-1) (mod n) - Assuming that M is not divisible by either p or

q, - Which is nearly always the case when p and q are

very large, - Fermats Little Theorem tells us that Mp-11 (mod

p) and Mq-11 (mod q) - Thus, we have that the following two congruences

hold - First Cd M(Mp-1)k(q-1) M1k(q-1) M

(mod p) - Second Cd M(Mq-1)k(p-1) M1k(p-1) M (mod

q) - And since gcd(p,q)1, we can use the Chinese

Remainder Theorem to show that therefore CdM

(mod pq) - If CdM (mod pq) then ?s CdspqM, so CdM (mod

p) and (mod q). Thus M is a solution to these

two congruences, so (by CRT) its the only

solution.