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Cryptanalysis of RSA Factorization - Library(ISI Kolkata) - Indian ...

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Chapter 2: Mathematical Preliminaries 38<br />

2.6 Solving Integer Polynomials<br />

Although there exist several techniques for solving univariate polynomials over<br />

integers, it is not so easy to solve bivariate integer polynomials. Coppersmith [22]<br />

introduced a method to find small integer roots for a bivariate polynomial f(x,y).<br />

Without loss <strong>of</strong> generality, we can assume that f(x,y) is irreducible. If f(x,y) is<br />

reducible, we can factor f(x,y) by the method <strong>of</strong> Wang and Rothschild [129] and<br />

try to find the roots <strong>of</strong> its factors individually. Coron [28] reformulated Coppersmith’s<br />

method to propose the following idea.<br />

2.6.1 Coron’s Method<br />

The main aim is to find a polynomial h(x,y) which is algebraically independent<br />

<strong>of</strong> f(x,y) and which shares the integer root (x 0 ,y 0 ) <strong>of</strong> f(x,y). Let, |x 0 | ≤ X,<br />

|y 0 | ≤ Y, and assume that f(x,y) = ∑ i,j a ijx i y j . Now, define W = max|a ij X i Y j |.<br />

i,j<br />

Define R = X l 1<br />

Y l 2<br />

W for some non-negative integers l 1 ,l 2 . Further let us define<br />

g ij (x,y) = x i y j R<br />

f(x,y) and h<br />

WX i Y j ij (x,y) = x i y j R,<br />

for some pair <strong>of</strong> integers i,j. Note that these g ij (x,y)’s are analogous to the shift<br />

polynomials as in Section 2.5.2. To ensure that all the shift polynomials g ij (x,y)<br />

have integer coefficients, choose l 1 ≥ i and l 2 ≥ j. Also note that g ij (x 0 ,y 0 ) ≡ 0<br />

(mod R) and h ij (x 0 ,y 0 ) ≡ 0 (mod R). Now, construct a lattice L using the coefficient<br />

vectors <strong>of</strong> g ij (xX,yY) and h ij (xX,yY) as a basis. Let ω be the dimension<br />

<strong>of</strong> the lattice L, and assume that r 1 (xX,yY),...,r ω (xX,yY) are the polynomials<br />

corresponding to the vectors <strong>of</strong> the LLL reduced basis <strong>of</strong> L.<br />

Now, from Lemma 2.20, we know that ||r 1 (xX,yY)|| ≤ 2 ω−1<br />

4 det(L) 1 ω. Also,<br />

from Theorem 2.22, we know that if ||r 1 (xX,yY)|| < R √ ω<br />

, then r 1 (x 0 ,y 0 ) = 0.<br />

So, when 2 ω−1<br />

4 det(L) 1 ω < R √ ω<br />

, then r 1 (x 0 ,y 0 ) = 0. Since we choose R = X l 1<br />

Y l 2<br />

W,<br />

r 1 (x,y) is divisible byX l 1<br />

Y l 2<br />

. Now it can be shown that r 1 (x,y) is algebraically independent<br />

<strong>of</strong> f(x,y). One can deduce this from the following result by Coron [28].<br />

Theorem 2.25. If h(x,y) is a multiple <strong>of</strong> f(x,y), then h(x,y) is divisible by<br />

X l 1<br />

Y l 2<br />

if and only if it has norm at least 2 −(ρ+1)2 +1 X l 1<br />

Y l 2<br />

W, where ρ is the maximum<br />

degree <strong>of</strong> the polynomials f,h in each variable separately.<br />

Hence, if ||r 1 (xX,yY)|| ≤ 2 ω−1<br />

4 det(L) 1 ω ≤ 2 −(ρ+1)2 +1 X l 1<br />

Y l 2<br />

W = 2 −(ρ+1)2 +1 R,

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