The Shortest Vector Problem (SVP) is a fundamental problem in computational geometry and lattice theory. It involves finding the shortest non-zero vector in a lattice, which is a discrete set of points in space formed by integer combinations of basis vectors. This problem is known to be NP-hard, meaning that no efficient algorithm is currently known to solve it in all cases. SVP has significant implications in areas such as cryptography, particularly in the security of lattice-based cryptographic systems. These systems rely on the difficulty of solving SVP to ensure that they are resistant to attacks, making them a promising alternative to traditional cryptographic methods like those based on the difficulty of factoring large numbers or computing discrete logarithms.