research/dkg: Add more comments and complaint challenge handling.

This commit is contained in:
parazyd
2023-08-12 15:55:15 +02:00
parent ee0cc25107
commit 6c5dbf4f92

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@@ -1,8 +1,8 @@
# Distributed Key Generation
# A naive approach.
# Distributed Key Generation scheme
t = 4 # Threshold
t = 4 # Threshold
n = 10 # Participants
assert t <= n
# Pallas
p = 0x40000000000000000000000000000000224698fc094cf91b992d30ed00000001
@@ -24,49 +24,70 @@ shares = {}
public_values = []
broadcast_values = {}
# The participants create their random polynomials and broadcast shares.
for i in range(n):
# Pick a random secret
coeffs = [Fq.random_element()]
# Generate random polynomial of degree t
coeffs = [Fq.random_element() for _ in range(t+1)]
# Set a_0 as a random secret
coeffs[0] = Fq.random_element()
for _ in range(t):
coeffs.append(Fq.random_element())
polynomials.append(coeffs)
# Compute and send secret shares
shares[i+1] = [sum([coeffs[j] * (i+1)**j for j in range(t+1)]) for i in range(n)]
shares[i+1] = [sum([coeffs[j] * (k**j) for j in range(t+1)]) for k in range(1, n+1)]
# Compute public value
public_values.append(coeffs[0] * G)
# Broadcast f_i(1)*G, f_i(2)*G, ..., f_i(n)*G
broadcast_values[i+1] = [sum([coeffs[j] * k**j for j in range(t+1)]) * G for k in range(1, n+1)]
# Broadcast evaluations of the polynomial at public points
broadcast_values[i+1] = [sum([coeffs[j] * (k**j) for j in range(t+1)]) * G for k in range(1, n+1)]
# ====================
# Step 2: Verification
# ====================
# In real-world, it is important to ensure that malicious participants
# cannot raise false complaints to disqualify honest participants.
# Having a robust mechanism to protect against Sybil attacks or malicious
# complaint flodding is essential.
complaints = {}
for j in range(1, n+1): # For each participant P_j
complaints[j] = []
for i in range(1, n+1): # From each participant P_i
# Initial check against broadcasted values
for i in range(1, n+1):
for j in range(1, n+1):
if shares[i][j-1] * G != broadcast_values[i][j-1]:
complaints[j].append(i) # P_j complains against P_i
if j not in complaints:
complaints[j] = []
complaints[j].append(i)
# Handle complaints
for complainant, offenders in complaints.items():
for offender in list(offenders): # Using list() to avoid runtime modification issues
# The offender proves they sent a correct share to the complainant
revealed_share = sum([polynomials[offender-1][k] * complainant**k for k in range(t+1)])
if revealed_share * G == broadcast_values[offender][complainant-1]:
complaints[complainant].remove(offender)
# Disqualification step
disqualified = {i for i, comp in complaints.items() if len(comp) > 0}
# ===================================
# Step 3: Secret Share Reconstruction
# ===================================
disqualified = {i for i, comp in complaints.items() if len(comp) > t}
# Sum the shares of qualified participants to get the group's secret share
# This is assuming a single party holds enough shares.
qualified_shares = [shares[i][i-1] for i in range(1, n+1) if i not in disqualified]
# Sum the secrets of qualified participants to get the group's secret share
# In a real-world application, this isn't safe and measures should be in
# place to prevent this scenario.
qualified_shares = [polynomials[i][0] for i in range(n) if i+1 not in disqualified]
if len(qualified_shares) < t+1:
raise Exception("Too many disqualifications. DKG failed.")
raise ValueError("Too many disqualifications. DKG failed.")
group_secret = sum(qualified_shares)
group_public_0 = group_secret * G
# However we can also do this without ever giving a single party enough
# shares to reconstruct the secret:
participant_pubkeys = [shares[i][i-1] * G for i in range(1, n+1) if i not in disqualified]
participant_pubkeys = [polynomials[i][0] * G for i in range(n) if i+1 not in disqualified]
if len(participant_pubkeys) < t+1:
raise Exception("Too many disqualifications. DKG failed.")
raise ValueError("Too many disqualifications. DKG failed.")
group_public_1 = sum(participant_pubkeys)
assert group_public_0 == group_public_1