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ArticlePublished 7 Aug 20263 min readBy Kevin Jogin
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Engineering  /  Mathematics  — Primality Testing

Factoring and Computing Euler's Phi Function

The polynomial-time equivalence between factoring a modulus, computing phi, and recovering an RSA private exponent.

Page KV-MATH-0393Reading time 4 minReviewed 2026-08-07Author Kevin Jogin

Executive summary

Three problems that appear distinct are polynomial-time equivalent for RSA moduli: factoring n, computing phi(n), and recovering the private exponent d from the public key.

This equivalence is what gives RSA a single mathematical foundation rather than several independent ones.

Learning objectives

  1. Prove that phi(n) yields the factorisation for a semiprime.
  2. Sketch the reduction from d to the factorisation.
  3. State what the equivalence does and does not establish.

01Phi yields the factorisation

Theorem

Phi to factors

For n = pq with distinct primes, knowledge of φ(n) gives p and q in polynomial time.

Proof. φ(n) = (p−1)(q−1) = n − (p+q) + 1, so p + q = n − φ(n) + 1. With the sum S and product n known, p and q are the roots of x² − Sx + n = 0, obtained by an integer square root.

The converse direction is immediate: the factorisation gives φ(n) by the product formula. So the two problems are equivalent for semiprimes.

p, q = (S ± √(S² − 4n)) / 2,   S = n − φ(n) + 1

02The private exponent yields the factorisation

Recovering the factorisation from d is less immediate but also polynomial time, using a randomised procedure resembling Miller–Rabin.

  1. Form ed − 1

    This is a multiple of λ(n), hence a multiple of the group exponent.

  2. Write it as 2^s · t with t odd

    Separating the powers of two, as in Miller-Rabin.

  3. Pick a random base and square repeatedly

    Compute a^t, then square, watching for a non-trivial square root of 1.

  4. Extract a factor

    A non-trivial square root x of 1 gives gcd(x − 1, n) as a proper factor.

The procedure succeeds with probability at least one half per random base, so a handful of attempts suffices. The mechanism is the same structural fact Miller–Rabin exploits: a composite modulus has more than two square roots of unity.

Caution
This is why an RSA private exponent must never be disclosed or reused across moduli, and why revoking a compromised key requires generating a completely new modulus rather than a new exponent. Exposure of d is exposure of the factorisation.

03What the equivalence establishes

Reductions among RSA-related problems
ProblemReduces toDirection
Factor nCompute φ(n)Both ways
Factor nRecover dBoth ways
Break RSA encryptionFactor nOne way only — not known to be equivalent
Caution
The last row is the important caveat. Recovering a plaintext from a ciphertext is not known to be as hard as factoring. It is conceivable that RSA encryption could be broken without factoring, and no proof rules this out. The RSA problem — computing e-th roots modulo n — is a separate assumption, weaker than the factoring assumption.

So RSA's security rests on the RSA assumption, which is implied by but not known to imply the hardness of factoring. In practice the best known attack on the RSA problem is to factor, which is why the distinction is theoretical rather than operational.

04Frequently asked questions

Does this mean φ(n) must be kept secret?

Yes, as secret as the factorisation itself, because they are equivalent. Any protocol revealing φ(n) reveals the private key.

Is breaking RSA equivalent to factoring?

Not known. There is evidence suggesting the two may not be equivalent for small public exponents, but no attack exploiting the gap is known. In practice the assumption is treated as sound.

Why does recovering d need randomisation?

Because the extraction relies on finding a base whose squaring sequence exposes a non-trivial square root of unity, and not every base does. Random choice succeeds with constant probability per attempt.

Related pages

  • The RSA Cryptosystem
  • Euler's Phi Function
  • Perfect Power Testing and Prime Power Factoring
  • Deterministic Primality Testing: The Basic Idea

Sources and method

Structural reference: Victor Shoup, A Computational Introduction to Number Theory and Algebra, Version 1, Cambridge University Press, 2005 — book pages 262-267.

This page carries the durable method layer only: definitions, constructions, algorithms, complexity results and selection criteria, authored originally for KEVOS. No text is transcribed or paraphrased from the source, and no numeric tables or benchmark data are reproduced — these are routed to live authoritative sources instead.

Author: Kevin Jogin. Last reviewed 2026-08-07.

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