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SVP in Hard to Approximate to within some constant Based on Article by Daniele Micciancio - 1998 IEEE Symposium on Foundations of Computer Science (FOCS ‘98)
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OverviewCVP NP-hard to approximate app. alg. 1O(logn) n O(1) 2 n/2 O(1) 22 1+1/n 2 loglog n n 1/ loglog n SVP app. alg.
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Approximate SVP & CVP GapSVP g (B,d) B is a Lattice base in R n, d R –Yes Instances z Z n \{0} || Bz || d –No Instances z Z n \{0} || Bz || > gd GapCVP g (B,y,d) B Z kxn, y R k, d R Yes Instances z Z n || Bz - y|| d No Instances z Z n || Bz - y|| > gd We actually want to prove: GapSVP 2 is NP-Hard
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n GapCVP g (B,y,d) B Z kxn, y R k, d R –Yes Instances z {0,1} n || Bz - y|| d –No Instances z Z n, w Z n \{0}|| Bz - wy|| > gd Modified CVP GapCVP and GapCVP’ were proven NP-Hard[Babai97] We show a reduction GapCVP c (B,y,d) GapSVP g (V,t) g= 2(1+2 ) c= 2/ ) t= 1+2
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n There is a probabilistic ploy-time algorithm which creates >0, for input 1 k (input size k) the following: Sauer’s Lemma s.t. with probability arbitrarily close to 1 - z Z m || Lz|| 2 > 2 - x {0,1} m, z Z m s.t. Cz=x and ||Lz-s|| > 1+ LatticeL R (m+1) x m Vectors R (m+1) MatrixC Z k x m 0 -b -s logP 1 logP 2 logP m 0 0 logP 1 logP m L m+1 x m+1 -y-y CVP lattice BnxkBnxk ° CkxmCkxm y Z n, B Z nxk
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Sauer’s Lemma Sauer’s Lemma (visualization) Copied from Micc98 article.
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Proving GapSVP NP-hardness (B,y,d) and c = (2/ ) (V,t) and g = (2/1+2 ) t = (2/1+2 ) = /d Yes Instance 1. (B,y,d) is Yes Instance a s.t. ||Va|| 2 < t 2 0 b logP 1 logP 2 logP m 0 0 logP 1 logP m = /d BnxkBnxk ° CkxmCkxm -y-y V = a=[z 1] Z m+1 (for some z Z m) ||Va|| 2 = ||Lz-s|| 2 + 2 ||Bx-y|| 2 t 2 1+2 = t 2 1+ /d 2 d 2
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Proving GapSVP NP-hardness (cont) (B,y,d) and c= (2/ ) (V,t) and g= (2/1+2 ) No Instance 2. (B,y,d) is No Instance a=[z w] z Z m ||Va|| 2 > g 2 t 2 = 2 ||Va|| 2 > ||Lz|| 2 > 2 !! z 0 I. w=0 without CVP help II. w 0 with CVP help ||Va|| 2 > 2 ||Bz-wy|| 2 2 c 2 d 2 = 2 /d 2 2/ 0 b -y-y logP 1 logP 2 logP m 0 0 logP 1 logP m BnxkBnxk ° CkxmCkxm [ z w ] = /d
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