ch04 cryptography and network security.ppt

Cryptography and
Network Security
Chapter 4
Fourth Edition
by William Stallings
Lecture slides by Lawrie Brown

Chapter 4 – Finite Fields
The next morning at daybreak, Star flew indoors,
seemingly keen for a lesson. I said, "Tap eight." She did
a brilliant exhibition, first tapping it in 4, 4, then giving me
a hasty glance and doing it in 2, 2, 2, 2, before coming
for her nut. It is astonishing that Star learned to count up
to 8 with no difficulty, and of her own accord discovered
that each number could be given with various different
divisions, this leaving no doubt that she was consciously
thinking each number. In fact, she did mental arithmetic,
although unable, like humans, to name the numbers. But
she learned to recognize their spoken names almost
immediately and was able to remember the sounds of
the names. Star is unique as a wild bird, who of her own
free will pursued the science of numbers with keen
interest and astonishing intelligence.
— Living with Birds, Len Howard

Introduction
 will now introduce finite fields
 of increasing importance in cryptography
 AES, Elliptic Curve, IDEA, Public Key
 concern operations on “numbers”
 where what constitutes a “number” and the
type of operations varies considerably
 start with concepts of groups, rings, fields
from abstract algebra

Group
 a set of elements or “numbers”
 with some operation whose result is also
in the set (closure)
 obeys:
 associative law: (a.b).c = a.(b.c)
 has identity e: e.a = a.e = a
 has inverses a-1: a.a-1 = e
 if commutative a.b = b.a
 then forms an abelian group

Cyclic Group
 define exponentiation as repeated
application of operator
 example: a-3 = a.a.a
 and let identity be: e=a0
 a group is cyclic if every element is a
power of some fixed element
 ie b = ak for some a and every b in group
 a is said to be a generator of the group

Ring
 a set of “numbers”
 with two operations (addition and multiplication)
which form:
 an abelian group with addition operation
 and multiplication:
 has closure
 is associative
 distributive over addition: a(b+c) = ab + ac
 if multiplication operation is commutative, it
forms a commutative ring
 if multiplication operation has an identity and no
zero divisors, it forms an integral domain

Field
 a set of numbers
 with two operations which form:
 abelian group for addition
 abelian group for multiplication (ignoring 0)
 ring
 have hierarchy with more axioms/laws
 group -> ring -> field

Modular Arithmetic
 define modulo operator “a mod n” to be
remainder when a is divided by n
 use the term congruence for: a = b mod n
 when divided by n, a & b have same remainder
 eg. 100 = 34 mod 11
 b is called a residue of a mod n
 since with integers can always write: a = qn + b
 usually chose smallest positive remainder as residue
• ie. 0 <= b <= n-1
 process is known as modulo reduction
• eg. -12 mod 7 = -5 mod 7 = 2 mod 7 = 9 mod 7

Divisors
 say a non-zero number b divides a if for
some m have a=mb (a,b,m all integers)
 that is b divides into a with no remainder
 denote this b|a
 and say that b is a divisor of a
 eg. all of 1,2,3,4,6,8,12,24 divide 24

Modular Arithmetic Operations
 is 'clock arithmetic'
 uses a finite number of values, and loops
back from either end
 modular arithmetic is when do addition &
multiplication and modulo reduce answer
 can do reduction at any point, ie
 a+b mod n = [a mod n + b mod n] mod n

Modular Arithmetic
 can do modular arithmetic with any group of
integers: Zn = {0, 1, … , n-1}
 form a commutative ring for addition
 with a multiplicative identity
 note some peculiarities
 if (a+b)=(a+c) mod n
then b=c mod n
 but if (a.b)=(a.c) mod n
then b=c mod n only if a is relatively prime to n

Modulo 8 Addition Example
+ 0 1 2 3 4 5 6 7
0 0 1 2 3 4 5 6 7
1 1 2 3 4 5 6 7 0
2 2 3 4 5 6 7 0 1
3 3 4 5 6 7 0 1 2
4 4 5 6 7 0 1 2 3
5 5 6 7 0 1 2 3 4
6 6 7 0 1 2 3 4 5
7 7 0 1 2 3 4 5 6

Greatest Common Divisor (GCD)
 a common problem in number theory
 GCD (a,b) of a and b is the largest number
that divides evenly into both a and b
 eg GCD(60,24) = 12
 often want no common factors (except 1)
and hence numbers are relatively prime
 eg GCD(8,15) = 1
 hence 8 & 15 are relatively prime

Euclidean Algorithm
 an efficient way to find the GCD(a,b)
 uses theorem that:
 GCD(a,b) = GCD(b, a mod b)
 Euclidean Algorithm to compute GCD(a,b) is:
EUCLID(a,b)
1. A = a; B = b
2. if B = 0 return A = gcd(a, b)
3. R = A mod B
4. A = B
5. B = R
6. goto 2

Example GCD(1970,1066)
1970 = 1 x 1066 + 904 gcd(1066, 904)
1066 = 1 x 904 + 162 gcd(904, 162)
904 = 5 x 162 + 94 gcd(162, 94)
162 = 1 x 94 + 68 gcd(94, 68)
94 = 1 x 68 + 26 gcd(68, 26)
68 = 2 x 26 + 16 gcd(26, 16)
26 = 1 x 16 + 10 gcd(16, 10)
16 = 1 x 10 + 6 gcd(10, 6)
10 = 1 x 6 + 4 gcd(6, 4)
6 = 1 x 4 + 2 gcd(4, 2)
4 = 2 x 2 + 0 gcd(2, 0)

Galois Fields
 finite fields play a key role in cryptography
 can show number of elements in a finite
field must be a power of a prime pn
 known as Galois fields
 denoted GF(pn)
 in particular often use the fields:
 GF(p)
 GF(2n)

Galois Fields GF(p)
 GF(p) is the set of integers {0,1, … , p-1}
with arithmetic operations modulo prime p
 these form a finite field
 since have multiplicative inverses
 hence arithmetic is “well-behaved” and
can do addition, subtraction, multiplication,
and division without leaving the field GF(p)

GF(7) Multiplication Example
 0 1 2 3 4 5 6
0 0 0 0 0 0 0 0
1 0 1 2 3 4 5 6
2 0 2 4 6 1 3 5
3 0 3 6 2 5 1 4
4 0 4 1 5 2 6 3
5 0 5 3 1 6 4 2
6 0 6 5 4 3 2 1

Finding Inverses
EXTENDED EUCLID(m, b)
1. (A1, A2, A3)=(1, 0, m);
(B1, B2, B3)=(0, 1, b)
2. if B3 = 0
return A3 = gcd(m, b); no inverse
3. if B3 = 1
return B3 = gcd(m, b); B2 = b–1 mod m
4. Q = A3 div B3
5. (T1, T2, T3)=(A1 – Q B1, A2 – Q B2, A3 – Q B3)
6. (A1, A2, A3)=(B1, B2, B3)
7. (B1, B2, B3)=(T1, T2, T3)
8. goto 2

Inverse of 550 in GF(1759)
Q A1 A2 A3 B1 B2 B3
— 1 0 1759 0 1 550
3 0 1 550 1 –3 109
5 1 –3 109 –5 16 5
21 –5 16 5 106 –339 4
1 106 –339 4 –111 355 1

Polynomial Arithmetic
 can compute using polynomials
f(x) = anxn + an-1xn-1 + … + a1x + a0 = ∑ aixi
• nb. not interested in any specific value of x
• which is known as the indeterminate
 several alternatives available
 ordinary polynomial arithmetic
 poly arithmetic with coords mod p
 poly arithmetic with coords mod p and
polynomials mod m(x)

Ordinary Polynomial Arithmetic
 add or subtract corresponding coefficients
 multiply all terms by each other
 eg
let f(x) = x3 + x2 + 2 and g(x) = x2 – x + 1
f(x) + g(x) = x3 + 2x2 – x + 3
f(x) – g(x) = x3 + x + 1
f(x) x g(x) = x5 + 3x2 – 2x + 2

Polynomial Arithmetic with
Modulo Coefficients
 when computing value of each coefficient
do calculation modulo some value
 forms a polynomial ring
 could be modulo any prime
 but we are most interested in mod 2
 ie all coefficients are 0 or 1
 eg. let f(x) = x3 + x2 and g(x) = x2 + x + 1
f(x) + g(x) = x3 + x + 1
f(x) x g(x) = x5 + x2

Polynomial Division
 can write any polynomial in the form:
 f(x) = q(x) g(x) + r(x)
 can interpret r(x) as being a remainder
 r(x) = f(x) mod g(x)
 if have no remainder say g(x) divides f(x)
 if g(x) has no divisors other than itself & 1
say it is irreducible (or prime) polynomial
 arithmetic modulo an irreducible
polynomial forms a field

Polynomial GCD
 can find greatest common divisor for polys
 c(x) = GCD(a(x), b(x)) if c(x) is the poly of greatest
degree which divides both a(x), b(x)
 can adapt Euclid’s Algorithm to find it:
EUCLID[a(x), b(x)]
1. A(x) = a(x); B(x) = b(x)
2. if B(x) = 0 return A(x) = gcd[a(x), b(x)]
3. R(x) = A(x) mod B(x)
4. A(x) ¨ B(x)
5. B(x) ¨ R(x)
6. goto 2

Modular Polynomial
Arithmetic
 can compute in field GF(2n)
 polynomials with coefficients modulo 2
 whose degree is less than n
 hence must reduce modulo an irreducible poly
of degree n (for multiplication only)
 form a finite field
 can always find an inverse
 can extend Euclid’s Inverse algorithm to find

Computational
Considerations
 since coefficients are 0 or 1, can represent
any such polynomial as a bit string
 addition becomes XOR of these bit strings
 multiplication is shift & XOR
 cf long-hand multiplication
 modulo reduction done by repeatedly
substituting highest power with remainder
of irreducible poly (also shift & XOR)

Computational Example
 in GF(23) have (x2+1) is 1012 & (x2+x+1) is 1112
 so addition is
 (x2+1) + (x2+x+1) = x
 101 XOR 111 = 0102
 and multiplication is
 (x+1).(x2+1) = x.(x2+1) + 1.(x2+1)
= x3+x+x2+1 = x3+x2+x+1
 011.101 = (101)<<1 XOR (101)<<0 =
1010 XOR 101 = 11112
 polynomial modulo reduction (get q(x) & r(x)) is
 (x3+x2+x+1 ) mod (x3+x+1) = 1.(x3+x+1) + (x2) = x2
 1111 mod 1011 = 1111 XOR 1011 = 01002

Using a Generator
 equivalent definition of a finite field
 a generator g is an element whose
powers generate all non-zero elements
 in F have 0, g0, g1, …, gq-2
 can create generator from root of the
irreducible polynomial
 then implement multiplication by adding
exponents of generator

Summary
 have considered:
 concept of groups, rings, fields
 modular arithmetic with integers
 Euclid’s algorithm for GCD
 finite fields GF(p)
 polynomial arithmetic in general and in GF(2n)

ch04 cryptography and network security.ppt

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