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Extensions of Coppersmith algorithm

The Coppersmith algorithm can be made even more general. There are two main extensions, first to an unknown modulus, then to multivariate polynomials.

hashtag
Unknown modulus

This extension of Coppersmith allows one to find small roots modulo an unknown some unknown factor of a number. More specifically, suppose that we have some unknown factorbbbofNNNsuch that b<NΞ²b<N^\betab<NΞ²and some monic polynomialfffof degreedddsuch that f(x0)=0(modb)f(x_0)=0\pmod bf(x0​)=0(modb)for some x0<NΞ²2dx_0<N^{\frac{\beta^2}d}x0​<NdΞ²2​. Then we can findx0x_0x0​in time polynomial in .

One key reason why this is possible is because we dont need to explicitly know the modulus to determine if a small root exists, i.e. is sufficient for a root less thanto exist. The algorithm here is extremely similar to the Coppersmith algorithm, except we add more polynomials into the lattice. The polynomials that we will use are

The latticegenerated by these polynomials would have

As we require the shortest vector to have length at most , repeating the computations from the previous section, we obtain

It turns out that the maxima of is as . One way to achieve this is by settingand we obtain

and this indeed achieves the bound. Similar to the Coppersmith algorithm, one chooses a sufficiently big such that the remainding bits can be brute forced in constant time while the algorithm still remains in polynomial time.

hashtag
Exercises

1) We show that the maximum ofis indeed . We can assume that . Since and , the maximum occurs when and , hence we have reduced this to maximizing which achieves its maximum of at .

log⁑N,d\log N,dlogN,d
βˆ₯f(Bx)βˆ₯2≀bd+1≀NΞ²d+1\left\lVert f(Bx)\right\rVert_2\leq\frac b{\sqrt{d+1}}\leq\frac{N^{\beta}}{\sqrt{d+1}}βˆ₯f(Bx)βˆ₯2​≀d+1​b​≀d+1​Nβ​
BBB
gi,j(x)=Nhβˆ’jf(x)jxi0≀i<d,0≀j<hgi,h(x)=f(x)hxi0≀i<t\begin{align*} g_{i,j}(x)&=N^{h-j}f(x)^jx^i&0\leq i<d,0\leq j<h\\ g_{i,h}(x)&=f(x)^hx^i&0\leq i<t \end{align*}gi,j​(x)gi,h​(x)​=Nhβˆ’jf(x)jxi=f(x)hxi​0≀i<d,0≀j<h0≀i<t​
LLL
dim⁑(L)=dh+t=nvol(L)=Ndh(h+1)2B(nβˆ’1)n2\dim(L)=dh+t=n\quad\text{vol}(L)=N^{\frac{dh(h+1)}{2}}B^{\frac{(n-1)n}2}dim(L)=dh+t=nvol(L)=N2dh(h+1)​B2(nβˆ’1)n​
NΞ²hn\frac{N^{\beta h}}{\sqrt{n}}n​NΞ²h​
B<4Ξ΄βˆ’14(1n)1nβˆ’1N2Ξ²hnβˆ’1βˆ’dh(h+1)n(nβˆ’1)B<\sqrt{\frac{4\delta-1}4}\left(\frac1n\right)^{\frac1{n-1}}N^{\frac{2\beta h}{n-1}-\frac{dh(h+1)}{n(n-1)}}B<44Ξ΄βˆ’1​​(n1​)nβˆ’11​Nnβˆ’12Ξ²hβ€‹βˆ’n(nβˆ’1)dh(h+1)​
2Ξ²hnβˆ’1βˆ’dh(h+1)n(nβˆ’1)\frac{2\beta h}{n-1}-\frac{dh(h+1)}{n(n-1)}nβˆ’12Ξ²hβ€‹βˆ’n(nβˆ’1)dh(h+1)​
Ξ²2d\frac{\beta^2}ddΞ²2​
n,hβ†’βˆžn,h\to\inftyn,hβ†’βˆž
n=dΞ²hn=\frac d\beta hn=Ξ²d​h
B<4Ξ΄βˆ’14(1n)1nβˆ’1N(hβˆ’1)Ξ²2dhβˆ’Ξ²B<\sqrt{\frac{4\delta-1}4}\left(\frac1n\right)^{\frac1{n-1}}N^{\frac{(h-1)\beta^2}{dh-\beta}}B<44Ξ΄βˆ’1​​(n1​)nβˆ’11​Ndhβˆ’Ξ²(hβˆ’1)Ξ²2​
O(NΞ²2d)O\left(N^{\frac{\beta^2}d}\right)O(NdΞ²2​)
h,nh,nh,n
2Ξ²hnβˆ’1βˆ’dh(h+1)n(nβˆ’1)\frac{2\beta h}{n-1}-\frac{dh(h+1)}{n(n-1)}nβˆ’12Ξ²hβ€‹βˆ’n(nβˆ’1)dh(h+1)​
Ξ²2d\frac{\beta^2}ddΞ²2​
dβ‰₯2,hβ‰₯1,0<β≀1,nβ‰₯2d\geq2,h\geq1,0<\beta\leq1,n\geq2dβ‰₯2,hβ‰₯1,0<β≀1,nβ‰₯2
hnβˆ’1(2Ξ²βˆ’dh+1n)\frac h{n-1}\left(2\beta-d\frac{h+1}{n}\right)nβˆ’1h​(2Ξ²βˆ’dnh+1​)
hnβˆ’1<h+1n\frac h{n-1}<\frac{h+1}nnβˆ’1h​<nh+1​
h,nβ†’βˆžh,n\to\inftyh,nβ†’βˆž
hnβˆ’1,h+1nβ†’x\frac h{n-1},\frac{h+1}n\to xnβˆ’1h​,nh+1​→x
2Ξ²xβˆ’dx22\beta x-dx^22Ξ²xβˆ’dx2
Ξ²2d\frac{\beta^2}ddΞ²2​
x=Ξ²dx=\frac\beta dx=dβ​