1 research outputs found
Lower bounds of shortest vector lengths in random knapsack lattices and random NTRU lattices
Finding the shortest vector of a lattice is one of the most important
problems in computational lattice theory. For a random lattice,
one can estimate the length of the shortest vector using
the Gaussian heuristic. However, no rigorous proof can be provided
for some classes of lattices, as the
Gaussian heuristic may not hold for them.
In the paper we study two types of random lattices in cryptography: the knapsack
lattices and the NTRU lattices. For random knapsack lattices, we prove
lower bounds of shortest vector lengths, which are very close to
lengths predicted by the Gaussian heuristic. For a random NTRU
lattice, we prove that with a overwhelming probability,
the ratio between the
length of the shortest vector and the length of the target vector,
which corresponds to
the secret key, is at least a constant, independent of the dimension of the
lattice. The main technique we use is the incompressibility method
from the theory of Kolmogorov complexity