Question

Let \(p\) be a prime and let \(p-1=q_{1}^{e_{1}} \cdots q_{r}^{e_{r}}\) be the prime factorization of \(p-1\). Let \(\gamma\) be a generator for \(\mathbb{Z}_{p}^{*}\). Let \(y\) be a positive number, and let \(Q_{p}(y)\) be the product of all the prime powers \(q_{i}^{e_{i}}\) with \(q_{i} \leq y .\) Suppose you are given \(p, y,\) the primes \(q_{i}\) dividing \(p-1\) with \(q_{i} \leq y,\) along with \(\gamma,\) an element \(\alpha\) of \(\mathbb{Z}_{p}^{*},\) and a bound \(\hat{x},\) where \(x:=\log _{\gamma} \alpha<\hat{x} .\) Show how to compute \(x\) in time $$ \left(y^{1 / 2}+\left(\hat{x} / Q_{p}(y)\right)^{1 / 2}\right) \cdot \operatorname{len}(p)^{O(1)} $$

Short answer

Question: Using a variation of the Pohlig-Hellman algorithm, describe the process of finding the value \(x = \log_{\gamma} \alpha\) within the specified time complexity constraint. Answer: The process can be outlined in the following steps: 1. Find the prime powers \(q_i^{e_i}\) satisfying \(q_i \leq y\) in the factorization of \(p-1\). 2. Compute base powers of \(\alpha\) and \(\gamma\) modulo \(p\) for each prime power found in step 1. 3. Use the Chinese Remainder Theorem (CRT) to concatenate the partial logarithms obtained in step 2. 4. If needed, calculate the few remaining indices within the given time constraint by searching for the correct \(x\) using the bound \(\hat{x}\) and the available steps.

Step-by-step solution

Find the prime powers \(q_i^{e_i}\) satisfying \(q_i \leq y\)

First, we need to find all prime powers \(q_{i}^{e_{i}}\) in the factorization of \(p-1\) for which \(q_i \leq y\). We can do this using a simple method of checking each prime factor \(q_i\) if it satisfies the condition \(q_i \leq y\). If it does, include the associated prime power \(q_i^{e_i}\) into the product of \(Q_p (y)\).

Compute base powers of \(\alpha\) and \(\gamma\) modulo \(p\)

For each prime power \(q_i^{e_i}\) found in step 1, compute the modular powers \(\alpha^{(p-1)/q_i} \pmod{p}\) and \(\gamma^{(p-1)/q_i} \pmod{p}\). Store these values in variables \(A\) and \(B\) respectively for further calculations.

Use CRT to concatenate partial results

Now, we will utilize the Chinese Remainder Theorem (CRT) to combine the partial logarithms obtained from step 2. For each \(q_i^{e_i}\) dividing \(Q_p(y)\), let \(x_i\) be the unique integer (\(0 \le x_i < q_i^{e_i}\)) such that: \[\alpha \equiv \gamma^{x_i} \, (\text{mod } p) \, \text{and} \, x \equiv x_i \, (\text{mod } q_i^{e_i})\] Using CRT, calculate the unique value of \(x\) in the range of \(0 \le x < Q_p(y)\), which satisfies all the congruences from the previous paragraph.

Calculate the few remaining indices inside the time constraint

If the value of \(x\) obtained in step3 is less than the bound \(\hat{x}\), then we have found the desired \(x\) using the previous steps. However, if this is not the case, we need to extend our search for \(x\), considering we don't exceed the time complexity constraint mentioned in the problem. The time constraint requires us to spend at most \[y^{1/2} + (\hat{x}/Q_p(y))^{1/2}\] steps to find a proper \(x\). At this point, we have already spent \(y^{1/2}\) steps to find the prime powers \(q_i^{e_i}\). Therefore, we can spend up to an additional \((\hat{x}/Q_p(y))^{1/2}\) steps checking the remaining possible \(x\) values by sequentially increasing the calculated \(x\) by \(Q_p(y)\) until we either find the correct \(x\) or reach the bound \(\hat{x}\). With these steps, we have computed the value \(x = \log_{\gamma} \alpha\) within the given time constraint.

Key concepts

Prime Factorization

Prime factorization is the process of breaking down a composite number into its prime factors, which are the prime numbers that multiply together to give the original number. For example, the prime factorization of 15 is 3 and 5, since 3 x 5 = 15 and both 3 and 5 are prime numbers.

This concept is crucial in many areas of computational number theory, as it is often used for simplifying complex problems, such as finding discrete logarithms and solving systems of congruences using the Chinese Remainder Theorem. In the context of the given exercise, being able to efficiently determine the prime powers of a prime minus one, \(p-1\), which are less than or equal to a certain threshold \(y\), is part of the groundwork needed to solve for \(x\) using the described algorithm.

Chinese Remainder Theorem

The Chinese Remainder Theorem (CRT) is a cornerstone in number theory with multiple applications in computer science and cryptography. It provides a way to solve systems of congruences with different moduli. CRT asserts that if one has several congruences, like \(x \text{mod}\ m_i = a_i\) for \(i = 1, 2, \text{and}\ 3\), where the \(m_i\)'s are pairwise coprime, then there exists a unique solution \(x\) modulo the product of the \(m_i\)'s.

In practice, the CRT helps reconstruct a number from its residues modulo these coprime divisors. In the step by step solution, CRT is applied to the partial results obtained from relationships between \(\alpha\) and \(\gamma\), leading to finding the discrete logarithm within a specific range, contributing significantly to the goal of reducing computational complexity while ensuring accuracy.

Discrete Logarithm Problem

The discrete logarithm problem involves finding the exponent \(x\) in the equation \(\alpha = \gamma^x \text{mod}\ p\), where \(\gamma\) is a primitive root modulo \(p\), and \(p\) is a prime number. It's a hard problem in computational number theory, particularly in large prime fields, and forms the basis of the security of many cryptographic systems.

As shown in the exercise, calculating \(x\) can be time-consuming, but it's made feasible with the use of prime factorization and the CRT. If we know the factorization of \(p-1\) and have an upper bound \(\hat{x}\), we can use these tools to simplify the computation and find \(x\) within a specific time complexity, making the problem tractable even for large values of \(p\).