Discrete Logarithm

Created: 2023-03-29
Updated: 2023-12-14

Discrete logarithm is a fundamental concept in modern cryptography, with numerous applications in key exchange, digital signatures, and other cryptographic protocols.

This post explores the basics of discrete logarithm, some important cryptographic protocols derived from it and the most important attacks.

Discrete Logarithm

Given g a generator for a cyclic group G with order n, the modular exponentiation function is defined as a mapping from Zₙ to G.

exp: Zₙ → G,    exp(i) = gⁱ

Where gⁱ represents the application of the group operation i times on g.

For example, if G = Zₚ* and the operation is the product then gⁱ = ∏ₖ g mod p, for k = 1..i and i ∈ Zₙ

When applied to a generator of a cyclic group, exp is injective and surjective (by definition of generator), we can thus define the inverse function.

The discrete logarithm function is defined as:

ind: G → Zₙ,    ind(gⁱ) = i

Discrete logarithm is not a monotonic function, and currently we don’t know any efficient algorithm to compute it.

Proposition. Given x, y ∈ G and a generator g of order n:

ind(x·y) = (ind(x) + ind(y)) mod n

This can be easily proven by considering that the group is cyclic and g has a cycle with period n (i.e. gⁱ = g^(i + k·n) ∀ k ∈ Z).

For example, if G = Zₚ* and n = φ(p)

ind(x) ≡ A (mod m), ind(y) ≡ B (mod p)

→ x = gᴬ mod p , y = gᴮ mod p
→ x·y ≡ gᴬ·gᴮ ≡ gᴬ⁺ᴮ ≡ g^[(A + B) mod φ(p)] (mod p)
→ ind(x·y) = (A + B) mod φ(p)

→ ind(x·y) = (ind(x) + ind(y)) mod φ(p)


Based on what is the group operation, the practical details of the discrete logarithm function changes, but the semantics is the same: how many times we apply the group operation to the generator.

Exponential notation is used when the group operation is the multiplication (e.g. multiplication of scalars in some prime group):

x = g·..·g = gᵏ

Multiplicative notation is used when the group operation is the addition (e.g. addition of points in some elliptic curve group):

x = g+..+g = k·g

In both cases we write ind(x) = k.

To be abstract and generic, if not specifically required, the group operation will not be specified, and exponential notation is used.

Where we have to manipulate a message m we assume the existence of a bijective mapping from the message domain M to the group domain G. For example, we may need to interpret m as a number in Zₚ* or as a point in an elliptic curve.

We also may need to map the output of an operation in G to a value in n = |G|. In this case we define the abstract function map_to_group_ord: G → Zₙ.

For example:

  • G is an elliptic curve and a a point: map_to_group_ord(a) = a.x mod n
  • G is Zₚ* and a a scalar: map_to_group_ord(a) = a mod n

Discrete Logarithm Problem

The discrete logarithm problem (DLP) is about finding the exponent to which a given group element must be raised to obtain another given group element, within a specific mathematical group.

The security of all the schemes in this post is attributed to the computational hardness of solving the discrete logarithm problem and the lack of efficient solution techniques.

ElGamal Cipher


  • G: cyclic group with order n
  • g ∈ G: generator for G
  • x ∈ Zₙ: secret key
  • y ∈ G: public key such that y = gˣ

Note that as a general rule we never choose as secret key 0 or 1 since these are trivially identifiable (by definition of generator):

g⁰ = 1 and g¹ = g


Given a message m ∈ G, pick a random k ∈ Zₙ*.

E = gᵏ     (ephemeral key)
M = yᵏ     (masking key)
c = M·m    (encrypted message)

The ciphertext is the tuple (E, c).


M = Eˣ     (recovery of M using secret key)
m = M⁻¹·c

To simplify a bit the decryption, we can first observe that if (k,n) = 1, then E = gᵏ is another generator. Now, because, by definition of generator E⁰ = Eⁿ = 1 then ∀ x ∈ Z, Eⁿ⁻ˣ⁺ˣ = Eⁿ⁻ˣ·Eˣ = 1 which implies E⁻ˣ = Eⁿ⁻ˣ.


Given the ciphertext (E, c = M·m) the corresponding plaintext can be predictably multiplied by a factor z by multiplying c by z.

c' = z·c  →  m' = M⁻¹·c' = M⁻¹·z·c = M⁻¹·z·M·m = z·m

ElGamal Signature

The scheme parameters are the same as the ElGamal cipher.

Given the message m, the secret key x and public key y = gˣ, pick a random scalar k which is relatively prime with the group order n.

R = gᵏ
r = map_to_group_ord(R)
s = (m - x·r)·k⁻¹ mod n

If s = 0 we repeat with a different k.

The signature is the couple (R, s).


Check if

 Rˢ·yʳ = gᵐ


Rˢ = gᵏˢ = g^[k·(m - x·r)·k⁻¹] = g^(m - x·r)
yʳ = gˣʳ
→ Rˢ·yʳ = g^(m - x·r + x·r) = gᵐ

The verifier can’t discover the secret x as he first needs to recover k, which imply finding the discrete logarithm for r.

The signer can’t forge valid signatures without knowing the secret x.

Existential forgery

Select e ∈ Zₙ and v ∈ Zₙ*.

Set R = gᵉ·yᵛ and s = -r·v⁻¹. Then the tuple (r, s) is a valid signature for the message m = e·s.

This vulnerability is easily addressed by replacing m with H(m) in the signature and verification procedures. With H a cryptographic hash function.

Reusing random secret

If the same value k is used to sign different messages then the secret key x can be easily recovered.

s₁ = (m₁ - x·r)·k⁻¹ mod n
s₂ = (m₂ - x·r)·k⁻¹ mod n
s₁ - s₂ = (m₁ - m₂)·k⁻¹ mod n
→  k = (m₁ - m₂)·(s₁ - s₂)⁻¹ mod n
→  x = (m₁ - s₁·k)·r⁻¹ mod n

The only requirement is that both s₁ - s₂ and r are in Zₙ*.

Digital Signature Standard

Also known as DSA (Digital Signature Algorithm), is a slightly modified version of ElGamal signature to address some of its weakness.


  • G: cyclic group with prime order n
  • g ∈ G: a generator for G
  • x ∈ Zₙ: secret key
  • y ∈ G: public key such that y = gˣ
  • H: a cryptographic hash such that H(m) ∈ Zₙ, for any message m

Given a message m, we pick a random scalar k ∈ Zₙ*.

R = gᵏ
r = map_to_group_ord(R)
s = (H(m) + x·r)·k⁻¹ mod n

If s = 0 we repeat with a different k.

The signature is the couple (r, s).


u = H(m)·s⁻¹ mod n
w = r·s⁻¹ mod n

V = gᵘ·yʷ
v = map_to_group_ord(V)

Valid if v = r


gᵘ·yʷ = g^(u + x·w)

u + x·w ≡ H(m)·s⁻¹ + x·r·s⁻¹ ≡ s⁻¹·(H(m) + x·r) ≡ s⁻¹·s·k ≡ k (mod n)

→ gᵘ·yʷ = r

DSA is more efficient than ElGamal signatures as:

  • It uses smaller exponents and still provides the same security. It works with a group with prime order which in general provides the same security as one bigger group with non-prime order (see Pohlig-Hellman attack).
  • It produces signatures that are shorter as both r and s are in Zₙ. In ElGamal we send the full R ∈ G as we need it for verification.
  • On verification, only two exponentiation in G are performed, in contrast to three with ElGamal.

Reusing random secret

If the same value k used to sign different messages then the secret key x can be easily recovered.

s₁ = (H(m₁) + x·r)·k⁻¹ mod n
s₂ = (H(m₂) + x·r)·k⁻¹ mod n
s₁ - s₂ = (H(m₁) - H(m₂))·k⁻¹ mod n
→  k = (H(m₁) - H(m₂))·(s₁ - s₂)⁻¹ mod n
→  x = (s₁·k - m₁)·r⁻¹ mod n

Schnorr Scheme

Interactive Schnorr Protocol

A kind of interactive zero-knowledge proof used to prove knowledge of some secret without revealing it.

In particular, in this context, it is used to prove knowledge of the discrete logarithm of a value with respect to a public generator.


  • G: cyclic group with prime order n
  • g ∈ G: a generator for G
  • x ∈ Zₙ*: secret scalar
  • y ∈ G: public group element such that y = gˣ

P wants to prove to V the knowledge of the discrete logarithm of y.


  1. Commitment: P chooses a random secret scalar k ∈ Zₙ*, computes r = gᵏ, and sends it to V.
  2. Challenge: V chooses a random value c and sends it to P.
  3. Response: P computes s = k + c·x mod n and sends it to V.
  4. Verification: V checks whether gˢ = r·yᶜ.

Verification Proof:

gˢ = g^(k + c·x) = gᵏ·gˣᶜ = r·yᶜ


  • To extract the secret x, V must compute x = (s - k)·c⁻¹ mod n. To do so, he must know the value of k, discrete log of r.
  • P can’t cheat as well. The only way to cheat is if he’s able to know the value of c before committing the value k. In that case he can compute r = gˢ·x⁻ᶜ for an arbitrary value s.

Non-Interactive Schnorr Protocol

The protocol can be made non-interactive by modifying the challenge step.

The challenge value is obtained from a technique known as Fiat-Shamir Heuristic. In practice, is computed as the output of a cryptographic hash function.

c = H(y || r)

Schnorr Signature

If we also bind a message m to the challenge then we obtain a Signature Scheme:

c = H(y || r || m)

Reusing random secret

If the same value k used with two different challenges then the secret key x can be easily recovered.

s₁ = k + c₁·x mod n
s₂ = k + c₂·x mod n
s₁ - s₂ = (c₁ - c₂)·x
→  x = (s₁ - s₂)·(c₁ - c₂)⁻¹ mod n

Chaum-Pedersen DLEQ Scheme

P wants to prove to V that two public values y₁ = gˣ and y₂ = hˣ have the same discrete logarithm with respect to the two generators g and h.


  • G₁ and G₂: two cyclic groups with same prime order n
  • g ∈ G₁ and h ∈ G₂: generators of G₁ and G₂ respectively
  • x ∈ Zₙ*: secret scalar
  • y₁, y₂ ∈ G: public group element such that y₁ = gˣ and y₂ = hˣ


  • Commitment: P chooses a random secret scalar k and sends to V the couple r₁ = gᵏ and r₂ = hᵏ.
  • Challenge: V chooses a random scalar c and sends it to P.
  • Response: P computes s = k + c·x mod n and sends it to V.
  • Verification: V checks if gˢ = r₁·y₁ᶜ and hˢ = r₂·y₂ᶜ.

Note that the verification for the individual values is equal to the Schnorr protocol, as a consequence P also prove knowledge of the secret and not just equality.

The verification and security proofs are quite similar to the Schnorr protocol.

Non-Interactive Chaum-Pedersen DLEQ Protocol

The idea is basically the same used for the Schnorr signature.

The challenge c is computed as:

c = H(y₁ || y₂ || r₁ || r₂).

Diffie-Hellman Key Exchange Protocol

The protocol is used to generate a shared secret between two parties A and B.


  • G: cyclic group with order n
  • g ∈ G: a generator for G
  • a ∈ Zₙ*: A secret key
  • yₐ ∈ G: A’s public key yₐ = gᵃ
  • b ∈ Zₙ*: B secret key
  • yᵦ ∈ G: B’s public key yᵦ = gᵇ


  • A generates a ∈ Zₙ and sends to B the public yₐ = gᵃ
  • B generates b ∈ Zₙ* and sends to A the public yᵦ = gᵇ
  • A computes k = yᵦᵃ
  • B computes k = yₐᵇ

The proof that the two parties gets the same k trivially follow the commutativity of the exponent in exponentiation.

Man in The Middle Attack

In a public network there can be a third actor C that performs a DH protocol instance with both A and B. When communicates with A he impersonates B and when it communicates with B he impersonates A.

The popular defense is to introduce some form of data-origin authentication. For example by signing the public keys with a key trusted by both the entities (i.e. some form of authority as done by PKI).

Attacks to DLP

Attacks against DLP can be divided in two classes:

  • generic: they work in any cyclic group, using only the group operation;
  • specialized: exploit special properties of a particular cyclic group.

Attacks can be further divided into two more classes:

  • running time dependent on the size of the cyclic group;
  • running time dependent on the size of the prime factors of the group order.

In the attacks’ analysis each step corresponds to a group operation.

Given the cyclic group G with order n and a generator g, let’s assume we want to compute the discrete logarithm of y = gˣ.

Generic algorithm where we simply repeat the group operation for the generator g until the result is equal to y.

On average, for a random value x, we expect to find the correct solution after checking half of all the possibilities.

This gives a complexity of O(n) steps.

To make brute-force infeasible is thus sufficient to choose a group G with a large enough order.

Shanks’ Algorithm

Also known as Baby-Step Giant-Step method, is a generic algorithm which trades time for memory.

The discrete logarithm is rewritten as:

m = ⌈√n⌉
x = m·x₁ + x₂  , for 0 ≤ x₁, x₂ < m

We rewrite y as:

y = gˣ = g^(m·x₁ + x₂) = g^(m·x₁) · g^x₂

→ y·g^(-m·x₁) = g^x₂

The value of g⁻ᵐ is known. The algorithm tries to find the solution (x₁, x₂).

The idea is to search for x₁ and x₂ separately.

In the first phase all the possible values for g^x₂ are computed and stored in a lookup table.

This phase requires O(√n) steps and needs to store O(√n) group elements.

The computed values for g^x₂ can be computed offline once (per group generator) and are independent on the exact value of y.

In the second phase we check for all x₁ until we don’t find the value which satisfies the equation (using the pre-computed x₂ values).

y·g^(-m·x₁) ≟ g^x₂

The second phase requires O(√n) computational steps.

The implication of this attack is a reduction of complexity for the general DLP. For example, to achieve at least 128 bits of security we require n ≥ 2²⁵⁶.

Pollard’s Rho Algorithm

This algorithm is currently the best known algorithm for computing the discrete logarithm for elliptic curve groups.

Is based on the birthday paradox, which asserts that to achieve a probability p of finding a collision while randomly extracting items from a set of d elements we need to extract: n(p) ≈ √(2·d·ln(1/(1-p))). For example, with p = 1/2 we have n = √(2·d·ln(2)).

Pseudo-randomly generate group elements of the form gⁱ·yʲ.

For each element keep track of the values i and j.

Continue until a collision is found: g^i₁·y^j₁ = g^i₂·y^j₂.

Which leads to the relation:

i₁ + x·j₁ ≡ i₂ + x·j₂ (mod n)
i₁ - i₂ ≡ x·(j₂ - j₁) (mod n)

If gcd(j₂ - j₁, n) = 1, then:

x = (i₁ - i₂)·(j₂ - j₁)⁻¹ mod n

A clever pseudo-random function for i and j generation is presented by Stinson1.

Pohlig-Hellman Algorithm

The algorithm reduces the discrete logarithm problem in a group with a composite order n to separate instances of the problem in subgroups of prime order pᵢ.

For each prime-order subgroup, another algorithm is applied, like Pollard’s rho, to solve the discrete log problem. Thus, this is essentially a pre-processing phase that optimizes the problem for these more efficient algorithms when the group order has small prime factors.

Given y = gˣ and n = ∏ pᵢ^eᵢ, the algorithm tries to compute the smaller discrete logarithms xᵢ = x mod pᵢ^eᵢ.

Once the values xᵢ = x mod pᵢ^eᵢ for all the prime factors pᵢ are found, the solution for n is trivially found by direct application of CRT.

Let p be a prime such that pᵉ is a factor of n. We want to compute the value r = x mod pᵉ (without knowing x obviously).

Because r < pᵉ, then we can express r in base p as:

r = ∑ rⱼ·pʲ , with 0 ≤ rⱼ < p  and for 0 ≤ j < e

Also, because r = x mod pᵉ, we can express x as:

x = pᵉ·q + r = pᵉ·q + ∑ rⱼ·pʲ

For some integer q.

The first step is to compute r₀ by observing that y^(n/p) = g^(r₀·n/p).


y^(n/p) = g^(x·n/p)

→  x·n/p = (pᵉ·q + ∑ rⱼ·pʲ)·n/p
         = (τ·p + r₀)·n/p
         = τ·n + r₀·n/p
         ≡ r₀·n/p (mod n)

Using this fact we proceed by trying to find the r₀ which satisfies the equation in O(p) steps.

If e = 1 then x ≡ r₀ (mod p) and thus we’re done. Otherwise, we proceed determining rⱼ for all the other exponents j < e.

Define y₀ = y and yⱼ = y·g^[-(r₀ + r₁·p + .. + rⱼ₋₁·pʲ⁻¹)] =

This time we’ll use the generalized equation yⱼ^(n/pʲ⁺¹) = g^(rⱼ·n/p).


yⱼ^(n/pʲ⁺¹) = g^[(x - r₀ - r₁·p - .. - rⱼ₋₁·pʲ⁻¹)·n/pʲ⁺¹]

→ (x - r₀ - r₁·p - .. - rⱼ₋₁·pʲ⁻¹)·n/pʲ⁺¹
  = (pᵉ·q + ∑ rⱼ·pʲ - r₀ - r₁·p - .. - rⱼ₋₁·pʲ⁻¹)·n/pʲ⁺¹
  = (τⱼ·pʲ⁺¹ + rⱼ·pʲ)·n/pʲ⁺¹
  = τⱼ·n + rⱼ·n/p
  ≡ rⱼ·n/p (mod n)

We proceed computing each rⱼ in O(p) steps.

This can be improved by noting that finding rᵢ for σ = g^(rᵢ·n/p) is equivalent to find rᵢ = log_[g^(n/p)](σ) and that g^(n/p) has order p.

We can try to find each rᵢ using any other DLP attack method, thus reducing the complexity to find each rᵢ to O(√p).

To contrast this attack the group order must have its largest prime factor in a range that is considered safe (e.g. today something like 2¹⁶⁰).

In practice, some popular cryptographic schemes defined over the DLP work in a prime order group.

Index Calculus Algorithm

Efficient method for cyclic groups Zₚ* and the multiplicative group of nonzero elements in GF(pᵐ), m > 1 (extension fields).

The idea comes from the fact that a significant number of elements of G can be expressed as the product of elements of a small subset of G.

The attack is so powerful that to provide 80 bit security the prime of a DLP in Zₚ* should be at least 1024 bit long!


Let B = { pᵢ } be a subset of small primes in Zₚ*.

In the first phase we find the logarithm of the |B| primes for base g.

Let C be the set of congruences defined using pseudo random values xⱼ and such that g^xⱼ has all its factors in B (we can use trial division):

C = { g^xⱼ ≡ ∏ pᵢ^aᵢⱼ (mod p) },  for some exponents set {aᵢⱼ}

Define |C| to be slightly bigger that |B|.

The elements of C can be rewritten as:

xⱼ ≡ ∑ aᵢⱼ·log_g(pᵢ) (mod p-1)

We end up with |C| congruences in |B| unknowns ({log_g(pᵢ)}) which hopefully have a unique solution modulo p-1.

This phase is carried out offline and an attacked can generate a big set of tuples L = { (pᵢ, log_g(pᵢ)) } for a generator g.


We want to recover the discrete logarithm for a generic y = gˣ.

Choose a random integer s (0 < s < p - 1) such that σ = y·gˢ mod p can be factored using just elements in B:

y·gˢ ≡ ∏ pᵢ^zᵢ (mod p)

Which can be rewritten as:

log_g(y) + s ≡ ∑ zᵢ·log_g(pᵢ) (mod p-1)

The only unknown in this equation is log_g(y), which gives us x.

Asymptotic run times:

  • pre-computation: e^[(1 + o(1))·√(ln(p)·ln(ln(p)))]
  • attack: e^[(1/2 + o(1))·√(ln(p)·ln(ln(p)))]


  • Cyclic groups notes
  • Shanks algorithm Rust PoC here
  • Reusing the ephemeral secret failure PoC here
  • Merlin - Rust implementation which automates the Fiat-Shamir transform.

  1. Cryptography Theory and Practice - Douglas Stinson ↩︎