In group theory, a branch of mathematics, the baby-step giant-step is a meet-in-the-middle algorithm for computing the discrete logarithm. The discrete log problem is of fundamental importance to the area of public key cryptography. Many of the most commonly used cryptography systems are based on the assumption that the discrete log is extremely difficult to compute; the more difficult it is, the more security it provides a data transfer. One way to increase the difficulty of the discrete log problem is to base the cryptosystem on a larger group.
Contents
Theory
The algorithm is based on a space-time tradeoff. It is a fairly simple modification of trial multiplication, the naive method of finding discrete logarithms.
Given a cyclic group
The baby-step giant-step algorithm is based on rewriting
The algorithm precomputes
The algorithm
Input: A cyclic group G of order n, having a generator α and an element β.
Output: A value x satisfying
- m ← Ceiling(√n)
- For all j where 0 ≤ j < m:
- Compute αj and store the pair (j, αj) in a table. (See section "In practice")
- Compute α−m.
- γ ← β. (set γ = β)
- For i = 0 to (m − 1):
- Check to see if γ is the second component (αj) of any pair in the table.
- If so, return im + j.
- If not, γ ← γ • α−m.
In practice
The best way to speed up the baby-step giant-step algorithm is to use an efficient table lookup scheme. The best in this case is a hash table. The hashing is done on the second component, and to perform the check in step 1 of the main loop, γ is hashed and the resulting memory address checked. Since hash tables can retrieve and add elements in O(1) time (constant time), this does not slow down the overall baby-step giant-step algorithm.
The running time of the algorithm and the space complexity is O(