Cryptography Reference
In-Depth Information
n be integers, S n be a hashing family, and b and
Lemma 3.5.1: Let m
<
δ
be two
b
m
2 . Suppose that X n is a random variable
reals such that m
b
n and
δ
2
distributed over
{
0
,
1
}
n such that for every x , it holds that
Pr
[ X n =
x ]
2 b . Then
for every
α ∈{
0
,
1
}
m
and for all but at most a 2 ( b m )
δ 2
fraction of the h's in
S n , it holds that
Pr
[ h ( X n ) = α ] (1 ± δ ) · 2 m
The average value of
], when averaging over all h 's, equals 2 m . Hence the
lemma upper-bounds the fraction of h 's that deviate from the average value. Specifi-
cally, a function h not satisfying
Pr
[ h ( X n )
= α
α
and the random variable X n ). The lemma asserts that the fraction of bad functions
is at most 2 ( b m )
Pr
[ h ( X n )
= α
]
(1
± δ
)
·
2 m
is called bad (for
def
=
b
m
δ 2 . Typically we shall use
δ
2
1 (making the deviation
from average equal the fraction of bad h 's). Another useful choice is
3
1 (which
yields an even smaller fraction of bad h 's, yet here non-badness implies only that
Pr
δ
[ h ( X n )
= α
]
(1
+ δ
)
·
2 m , since
Pr
[ h ( X n )
= α
]
0 always holds).
Proof: Fix an arbitrary random variable X n satisfying the conditions of the lemma
and an arbitrary
def
= Pr
α ∈{
0
,
1
}
m . Denote
w x
[ X n =
x ]. For every h ,wehave
x w x ζ x ( h )
Pr
[ h ( X n ) = α ] =
ζ x ( h ) equals 1 if h ( x )
= α
where
, and 0 otherwise. Hence, we are interested in the
probability, taken over all possible choices of h , that
x w x ζ x ( h )
|
2 m
|
2 m .
Looking at the
ζ x 's as random variables defined over the random variable H n ,it
is left to show that
x w x ζ x · 2 m
2 ( b m )
δ
2 m
Pr
<
2
This is proved by applying Chebyshev's inequality, using the following facts:
2 m
1. The
ζ x 's are pairwise independent, and
Var
(
ζ x )
<
(since
ζ x =
1 with proba-
bility 2 m , and
ζ x =
0 otherwise).
(by the hypothesis), and x w x =
w x
2 b
2.
1.
Namely,
·
2 m
x w x ζ x
( δ · 2 m ) 2
x w x ζ x
Var
2 m
Pr
x w
x
· Var
(
ζ x )
=
δ
2
·
2 2 m
2 m 2 b
δ
<
· 2 2 m
2
The lemma follows.
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