This page documents the Helios v4 data structures and specs.
Contrary to previous ideas, Helios v4 will *not* support mixnets, but its data structures will be ready to eventually support them.
NOT FINAL. THIS DOCUMENT IS IN PROGRESS AS OF August 29th 2012.
Helios is a truly verifiable voting system, which means that:
This document specifies all data formats and the exact verification protocols and algorithms. Using this document, it should be possible for an able programmer to build a complete verification program in any modern programming language. For the sake of concreteness, instead of pseudo-code, we use Python (2.3 or above.)
This document covers Helios 4.0, due out for release in Fall 2012. The biggest changes from v3.0 are:
All data for an election is easily accessible using simple HTTP GET requests. The HTTP interface for accessing all data from a given election is built so as to enable static storage of this data in a simple filesystem made available over the web, to simplify long-term robustness. Consider an election with election id <ELECTION_ID>. Assuming a host and prefix that we denote {HELIOS_HOST}, the election data structure, including the election public key, questions, etc., can be obtained by requesting the following URL:
{HELIOS_HOST}/elections/<ELECTION_ID>
The list of voters, denoted <VOTER_LIST>, is available at:
{HELIOS_HOST}/elections/<ELECTION_ID>/voters/
Given this list, it is possible to extract individual voter identifiers, denoted <VOTER_ID>
The list of cast ballots is available at, with each ballot including the <VOTER_ID> that it corresponds to:
{HELIOS_HOST}/elections/<ELECTION_ID>/ballots/
This call will return ballots in chronological (oldest to newest) order, and takes optional parameters limit and after.
The list of all ballots cast by a voter is:
{HELIOS_HOST}/elections/<ELECTION_ID>/ballots/<VOTER_ID>/all
For convenience, the last cast ballot is:
{HELIOS_HOST}/elections/<ELECTION_ID>/ballots/<VOTER_ID>/last
The result of an election is available at:
{HELIOS_HOST}/elections/<ELECTION_ID>/result
Every election has trustees (sometimes just one), and the list of trustees, including each trustee's public key and PoK, decryption factor and proof is at:
{HELIOS_HOST}/elections/<ELECTION_ID>/trustees/
NOT YET IMPLEMENTED:
While the trustee's robustness information (e.g. Lagrange coeff) is at:
{HELIOS_HOST}/elections/<ELECTION_ID>/trustees/<TRUSTEE_ID>/robustness_factor
Data Formats
We begin with a description of the data types and their representations. All data made available by Helios is in JavaScript Object Notation (JSON) format, with keys in alphabetical order and no extraneous whitespace other than that specified by JSON. These two conditions are particularly important, as hashing data structures will only yield the same hash if the conditions are respected. An example of a JSON data structure with these two conditions is:
Example (not an actual Helios data structure)
{"email": ["ben@adida.net", "ben@mit.edu"], "first_name": "Ben", "last_name": "Adida"}
All large integers are represented as base64 strings. An El-Gamal public-key is then a dictionary including the prime p, the primer-order q of its intended subgroup, the generator g, and the public-key value y (with keys in alphabetical order):
<ELGAMAL_PUBLIC_KEY>
{"g": "Hbb3mx34sd", "p": "mN3xc34", "q": "J3sRtxcwqlert", "y": "U8cnsvn45234wsdf"}
An El-Gamal ciphertext is a JSON structure containing properties alpha and beta, the two components modulo p.
<ELGAMAL_CIPHERTEXT>
{"alpha": "6BtdxuEwbcs+dfs3", "beta": "nC345Xbadw3235SD" }
In Helios, all ciphertexts are Exponential ElGamal, so alpha = g^r mod p, and beta = g^m y^r mod p.
In Helios, all hash values are base-64 encoded, and the hashing algorithm is always SHA256:
Hash value example
{"election_hash": "c0D1TVR7vcIvQxuwfLXJHa5EtTHZGHpDKdulKdE1oxw"}
A single voter in Helios is represented using a few fields that identify the voter. This data structure has changed from prior versions of Helios in order to accommodate multiple types of users, not just users identified by email address.
<VOTER>
{"name": "Ben Adida", "uuid": "60435862-65e3-11de-8c90-001b63948875", "voter_id": "benadida@gmail.com", "voter_type": "email"}
Together, the type and id identify the voter via some external authentication mechanism. In the example above, this is a user whose email address is benadida@gmail.com. Another example might be:
<VOTER>
{"name": "Ben Adida", "uuid": "4e8674e2-65e3-11de-8c90-001b63948875", "voter_id": "ben@adida.net", "voter_type": "email"}
where this is a voter identified by the email address ben@adida.net.
The uuid field is used as a reference key within Helios.
Voters may be identified by OpenID URL rather than email address, in which case their JSON representation is:
<VOTER>
{"name": "Ben Adida", "uuid": "4e8674e2-65e3-11de-8c90-001b63948875",
"voter_id": "http://benadida.myopenid.com", "voter_type": "openid"}
Other fields may be present in a <VOTER> data structure, e.g. category. These do not affect the cryptographic processing, but if present, they become part of the hash of the voter list.
In order to protect voter privacy, Helios can obfuscate the voter_id, especially when that voter_id is an email address. This protection is not meant to resist a powerful attacker with other knowledge about the voter, but mostly to prevent activities such as email-address crawlers for the purpose of spamming. In this case, a voter can be represented with the field voter_id_hash replacing voter_id. The hash is SHA256 by default, or specified as a prefix when it is a different hash:
<VOTER>
{"name": "Ben Adida", "uuid": "60435862-65e3-11de-8c90-001b63948875", "voter_id_hash": "47DEQpj8HBSa+/TImW+5JCeuQeRkm5NMpJWZG3hSuFU", "voter_type": "email"}
Voter Aliases
In some elections, it may be preferable to never reveal the identity of the voters. This is particularly applicable when organizers are worried about votes being decryptable in 30+ years, when cryptographic advances make today's algorithms weaker. An election may thus publish only an ALIASED_VOTER:
<ALIASED_VOTER>
{"alias": "voter_123", "uuid": "b7dbd90a-65e3-11de-8c90-001b63948875"}
An aliased voter still has a UUID, so it can still be referred appropriately in the rest of the system.
Casting a Vote
Once a voter has cast a ballot, the encrypted vote representation is then:
<CAST_VOTE>
{"cast_at": "2009-07-15 12:23:46", "vote": <VOTE>, "vote_hash": "8bncn23nsfsdk234234",
"voter_hash": "2bxksdlkxnsdf", "voter_uuid": "b7dbd90a-65e3-11de-8c90-001b63948875"}
cast_at is the timestamp of the cast vote in UTC.
We describe the details of the <VOTE> data structure later in this document, once we have described all of the required components.
vote_hash is available to enable a shorter version of this data structure:
<SHORT_CAST_VOTE>
{"cast_at": "2009-07-15 12:23:46", "vote_hash": "c0D1TVR7vcIvQxuwfLXJHa5EtTHZGHpDKdulKdE1oxw",
"voter_hash": "2bxksdlkxnsdf", "voter_uuid": "b7dbd90a-65e3-11de-8c90-001b63948875"}
where only the hash and not the full vote is listed.
An election is represented as:
<ELECTION>
{"cast_url": "https://heliosvoting.org/cast/",
"description": "... blah blah blah ... info about the election",
"frozen_at": null,
"name": "Student President Election at Foo University 2010",
"openreg": false, "public_key": <ELGAMAL_PUBLIC_KEY>,
"questions": <QUESTION_LIST>,
"short_name": "fooprez2010",
"use_voter_aliases": false,
"uuid": "1882f79c-65e5-11de-8c90-001b63948875",
"voters_hash": "G6yS/dAZm5hKnCn5cRgBGdw3yGo"}
short_name, name, and description describe the election. The short name must be a few characters without a space (almost like a database key), the name can be a long string, and the description is an even longer description of the election.
cast_url indicates the URL where ballots for this election should be cast.
frozen_at indicates the timestamp at which this election was frozen. It remains null until the election is frozen.
openreg indicates whether voters can be added to the list after the election has started.
use_voter_aliases indicates whether this election aliases its voters.
uuid is a unique identifier for the election, and name is the election's name.
<ELGAMAL_PUBLIC_KEY> is, as detailed earlier, the JSON data structure that represents an El-Gamal public key.
<QUESTION_LIST> is a data structure that represents the list of questions and available answers to those questions.
<QUESTION_LIST>
[<QUESTION>, <QUESTION>, ...]
and a single question is a JSON object:
<QUESTION>
{"answer_urls": ["http://example.com/alice", null], "answers": ["alice", "bob"], "choice_type": "approval", "max": 1, "min": 0,
"result_type": "absolute", "question": "Who Should be President?", "short_name": "President", "tally_type": "homomorphic"}
which, in this case, contains two possible answers (alice and bob), URLs that describe these answers in greater detail, the text of the question, and a short name for the question. The parameter max indicates the maximum number of options that a voter can select, most often 1. The parameter min indicates the minimum number of options that a voter must select, most often 0. Note how, given that max and min should be small integers, they are in fact serialized as integers, not as strings. choice_type indicates the kind of question, for now just approval (possibly with a maximum number of choices). If max is null, then it's approval voting for as many candidates as desired. tally_type indicates how the question is tallied, e.g. homomorphic or mixnet.
voters_hash is the hash of the list of voters for the election. The list of voters is a JSON array of <VOTER> data structures. For example, a list of voters might be:
<VOTER_LIST> (example)
[{"id": "benadida@gmail.com", "name": "Ben Adida", "type": "email", "uuid": "60435862-65e3-11de-8c90-001b63948875"}, {"id": "ben@adida.net", "name": "Ben2 Adida", "type": "email", "uuid": "4e8674e2-65e3-11de-8c90-001b63948875"}]
Open Registration
Helios supports "open registration elections", when the election administrator so desires. In those elections, the voter list is not set ahead of time. In that case, an election data structure contains a null voters_hash, and sets openreg to true.
Once an election is ready to be used for voting, the administrator freezes the election, at which point Helios prevents changing any of the question parameters and voter registration settings: an open election remains an open election, and a closed election remains closed with a fixed voter list. The frozen_at field then indicates the timestamp at which the election was frozen.
Such a frozen election can be designated by its Helios Election Fingerprint, which is the hash of the JSON election data structure (with properly alphabetized field names, as always). Note how this fingerprint depends on the list of voters if the election registration status is closed, but not if it is open. In any case, this fingerprint does not depend on any cast vote or cast-vote hash.
A vote contains a list of encrypted answers, and a reference to the election, both by ID (for convenience) and by hash (for integrity.) The hash is the election fingerprint just described.
<VOTE>
{"answers": [<ENCRYPTED_ANSWER>, <ENCRYPTED_ANSWER>, ...], "election_hash": "Nz1fWLvVLH3eY3Ox7u5hxfLZPdw", "election_uuid": "1882f79c-65e5-11de-8c90-001b63948875"}
Each "encrypted answer" corresponds to one election question: it contains a list of ciphertexts (one for each possible choice for that question), a list of corresponding proofs that the ciphertext is correctly formed, and an overall proof that all of the ciphertexts for that election question, taken together, are correctly formed.
<ENCRYPTED_ANSWER>
{"choices": [<ELGAMAL_CIPHERTEXT>, <ELGAMAL_CIPHERTEXT>, ...], "individual_proofs": [<ZK_PROOF_0..1>, <ZK_PROOF_0..1>, ...], "overall_proof": <ZK_PROOF_0..max>}
The value of max in overall_proof matches the value of max in the election's question definition.
For approval voting questions, the overall_proof is absent.
When a voter generates a ballot, Helios provides the ballot fingerprint, which is the base64-encoding of the SHA256 hash of the <VOTE> data structure defined above.
A zero-knowledge proof, denoted <ZK_PROOF_0..max>, is a transcript of a non-interactive proof that the corresponding ciphertext encodes an integer value between 0 and max. For the overall proof, the ciphertext whose value is being proven to be between 0 and max is the homomorphic sum (element-wise product) of the choices ciphertexts.
In Helios, all 0..max proofs are disjunctive proofs (CDS & CP), meaning that the transcript includes max+1 proofs, one for each possible value of the plaintext, 0 through max. The max+1 individual challenges must sum up to the single actual protocol challenge, which ensures that one of the proofs is real (while the others are simulated.)
<ZK_PROOF_0..max>
[<ZK_PROOF(0)>, <ZK_PROOF(1)>, ..., <ZK_PROOF(max)>]
A single ZK proof is then composed of three messages: the commitment, the challenge, and the response. Since the proof is a Chaum-Pedersen proof of a DDH tuple, the commitment is composed of two values, A and B. Thus, a ZK proof is:
<ZK_PROOF(plaintext)>
{"challenge": "2342342", "commitment": {"A": "28838", "B": "9823723"}, "response": "970234234"}
In Helios v4, the commitment is optional, since these types of proofs can be checked with just the challenge and response, which cuts down the size of a proof significantly. This is doable because the commitment values A and B should be recoverable as:
A = g^response / alpha^challenge
B = y^response / (beta/g^m)^challenge
at which point those values can be used in the proof verification. Effectively, we do more computation in exchange for a much smaller proof, since A and B are in the full group, while challenge and response are in the subgroup.
Proof Robustness
In prior versions of Helios, the proofs were generated using Fiat-Shamir with very little context, which makes an individual proof easily exchangeable with another. This is bad for security proofs (and for actual security, not coincidentally). So, to generate a challenge in a Fiat-Shamir'ized proof, we now include a lot more context.
First, to generate a challenge in general, we now create a JSON data structure, with the same strictness as our other JSON data structures (alphabetized keys, no extra spaces), that contains all the fields we want for context.
In the Proof of Knowledge of a Secret Key, we include: election_uuid, trustee_email.
In the single-choice proof inside a valid ballot, we include: election_hash, question_num, choice_num, ciphertext (in JSON format).
In the overall proof inside a valid ballot, we include: election_hash, question_num, ciphertext, where the ciphertext is the homomorphic combination of all the choice ciphertexts.
In the proof of decryption, we include: ciphertext, election_hash, trustee_email.
For example, in a single-choice proof, this is the string we hash (extra spacing for readability only):
{"A": "3bZcd35GAS",
"B": "7bXcd352sd",
"choice_num": 0,
"ciphertext": {"alpha": "6BtdxuEwbcs+dfs3", "beta": "nC345Xbadw3235SD"},
"election_hash": "Nz1fWLvVLH3eY3Ox7u5hxfLZPdw",
"question_num": 2}
to generate the challenge that the prover must respond to.
When a voter chooses to audit their ballot, each encrypted answer contains additional information concerning the actual selected choice and the randomness used to encrypt each choice's ciphertext. Specifically, the JSON structure for <VOTE_WITH_PLAINTEXTS> is as follows.
<VOTE_WITH_PLAINTEXTS>
{"answers": [<ENCRYPTED_ANSWER_WITH_PLAINTEXT>, <ENCRYPTED_ANSWER_WITH_PLAINTEXT>, ...], "election_hash": <B64_HASH>, "election_uuid": <ELECTION_UUID>}
And the contained <ENCRYPTED_ANSWER_WITH_PLAINTEXT> is as follows.
<ENCRYPTED_ANSWER_WITH_PLAINTEXT>
{"answer": 1, "choices": [<ELGAMAL_CIPHERTEXT>, <ELGAMAL_CIPHERTEXT>, ...], "individual_proofs": [<ZK_PROOF_0..1>, <ZK_PROOF_0..1>, ...], "overall_proof": <ZK_PROOF_0..max>, "randomness": [<BIGINT_B64>, <BIGINT_B64>, <BIGINT_B64>]}
The result of an election is represented using the <RESULT> data structure. The proofs of the decryption are done at the Trustee level. The result simply displays the count of votes for each candidate within each question, in an array of arrays format.
<RESULT>
[[<QUESTION_1_CANDIDATE_1_COUNT>, <QUESTION_1_CANDIDATE_2_COUNT>, <QUESTION_1_CANDIDATE_3_COUNT>], [<QUESTION_2_CANDIDATE_1_COUNT>, <QUESTION_2_CANDIDATE_2_COUNT>]]
Even if there is only one keypair in the case of a simple election, Helios v3 (in a departure from previous versions), represents every election as having trustees. If there is only one trustee, that's fine, but the data structure remains the same:
<TRUSTEE>
{"decryption_factors": <LIST_OF_LISTS_OF_DEC_FACTORS>,
"decryption_proofs": <LIST_OF_LISTS_OF_DEC_PROOFS>,
"pok": <POK_OF_SECRET_KEY>,
"public_key": <PUBLIC_KEY>,
"public_key_hash": <PUBLIC_KEY_HASH>,
"uuid": <UUID_OF_TRUSTEE>}
In the rest of this document, we show how to verify various aspects of a Helios election using Python code for concreteness and legibility. We assume that certain data structures have been defined: election, vote, proof, disjunctive_proof, and a few others, all of which correspond to collections of fields that directly map to the JSON data structures described above. However, we note that a verification program need not necessarily parse these JSON strings into custom Python objects. It is perfectly acceptable to extract individual fields when necessary.
In particular, in a number of cases, our sample code will call election.toJSON(), or vote.toJSON() in order to re-convert the data structure to JSON so that it can be hashed and checked for integrity. A verification program that handles JSON strings directly without de-serializing them to Python objects would obviously not need to re-serialize to JSON, either. The original JSON provided by the Helios server hashes appropriately to the intended values.
Recall the Chaum-Pedersen proof that a ciphertext (alpha,beta) under public key (y, (g,p,q)) is proven to encode the value m by proving knowledge of r, the randomness used to create the ciphertext, specifically that g, y, alpha, beta/g^m is a DDH tuple, noting that alpha = g^r and beta/g^m = y^r.
verify_proof(ciphertext, plaintext, proof, public_key):
if pow(public_key.g, proof.response, public_key.p) !=
((proof.commitment.A * pow(ciphertext.alpha, proof.challenge, public_key.p)) % public_key.p):
return False
beta_over_m = modinverse(pow(public_key.g, plaintext, public_key.p), public_key.p) * ciphertext.beta
beta_over_m_mod_p = beta_over_m % public_key.p
if pow(public_key.y, proof.response, public_key.p) !=
((proof.commitment.B * pow(beta_over_m_mod_p, proof.challenge, public_key.p)) % public_key.p):
return False
return True
In a disjunctive proof that the ciphertext is the encryption of one value between 0 and max, all max+1 proof transcripts are checked, and the sum of the challenges is checked against the expected challenge value. Since we use this proof in non-interactive Fiat-Shamir form, we generate the expected challenge value as SHA1(A0 + "," + B0 + "," + A1 + "," + B1 + ... + "Amax" + "," + Bmax) with A0, B0, A1, B1, ... ,Amax, Bmax in decimal form. (Ai and Bi are the components of the commitment for the i'th proof.)
Thus, to verify a <ZK_PROOF_0..max> on a <ELGAMAL_CIPHERTEXT>, the following steps are taken.
verify_disjunctive_0..max_proof(ciphertext, max, disjunctive_proof, public_key):
for i in range(max+1):
# the proof for plaintext "i"
if not verify_proof(ciphertext, i, disjunctive_proof[i], public_key):
return False
# the overall challenge
computed_challenge = sum([proof.challenge for proof in disjunctive_proof]) % public_key.q
# concatenate the arrays of A,B values
list_of_values_to_hash = sum([[p.commitment.A, p.commitment.B] for p in disjunctive_proof], [])
# concatenate as strings
str_to_hash = ",".join(list_of_values_to_hash)
# hash
expected_challenge = int_sha(str_to_hash)
# last check
return computed_challenge == expected_challenge
Thus, given <ELECTION> and a <VOTE>, the verification steps are as follows:
verify_vote(election, vote):
# check hash (remove the last character which is a useless '=')
computed_hash = base64.b64encode(hash.new(election.toJSON()).digest())[:-1]
if computed_hash != vote.election_hash:
return False
# go through each encrypted answer by index, because we need the index
# into the question array, too for figuring out election information
for question_num in range(len(vote.answers)):
encrypted_answer = vote.answers[question_num]
question = election.questions[question_num]
# initialize homomorphic sum (assume operator overload on __add__ with 0 special case.)
homomorphic_sum = 0
# go through each choice for the question (loop by integer because two arrays)
for choice_num in range(len(encrypted_answer.choices)):
ciphertext = encrypted_answer.choices[choice_num]
disjunctive_proof = encrypted_answer.individual_proofs[choice_num]
# check the individual proof (disjunctive max is 1)
if not verify_disjunctive_0..max_proof(ciphertext, 1, disjunctive_proof, election.public_key):
return False
# keep track of homomorphic sum
homomorphic_sum = ciphertext + homomorphic_sum
# check the overall proof
if not verify_disjunctive_0..max_proof(homomorphic_sum, question.max,
encrypted_answer.overall_proof,
election.public_key):
return False
# done, we succeeded
return True
Given a <VOTE_WITH_PLAINTEXTS> and a claimed vote fingerprint, verification entails checking the fingerprint, checking all of the proofs to make sure the ballot is well-formed, and finally ensuring that the ballot actually encodes the claimed choices.
verify_ballot_audit(vote_with_plaintexts, election, vote_fingerprint)
# check the proofs
if not verify_vote(election, vote_with_plaintexts):
return False
# check the proper encryption of each choice within each question
# go through each encrypted answer
for encrypted_answer in vote_with_plaintexts.answers:
# loop through each choice by integer (multiple arrays)
for choice_num in range(len(encrypted_answer.choices)):
# the ciphertext and randomness used to encrypt it
ciphertext = encrypted_answer.choices[choice_num]
randomness = encrypted_answer.randomness[choice_num]
# the plaintext we expect, g^1 if selected, or g^0 if not selected
if choice_num == encrypted_answer.answer:
plaintext = public_key.g
else:
plaintext = 1
# check alpha
if pow(public_key.g, randomness, public_key.p) != ciphertext.alpha:
return False
# check beta
expected_beta = (pow(public_key.y, randomness, public_key.p) * plaintext) % public_key.p
if expected_beta != ciphertext.beta:
return False
# check the fingerprint
vote_without_plaintexts = vote_with_plaintexts.remove_plaintexts()
computed_fingerprint = base64.b64encode(hash.new(vote_without_plaintexts.toJSON()).digest())[:-1]
return computed_fingerprint == vote_fingerprint
To verify a complete election tally, one should:
In other words, the complete results of a verified election includes: the election fingerprint, the list of ballot fingerprints, the trustee decryption factors and proofs, and the final plaintext counts. Any party who verifies the election should re-publish all of these items, as they are meaningless without one another. This is effectively a "re-tally".
Part of this re-tally requires checking a partial decryption proof, which is almost the same, but not quite the same, as checking an encryption proof with given randomness.
Given a ciphertext denoted (alpha,beta), and a trustee's private key x corresponding to his public key y, a partial decryption is:
dec_factor = alpha^x mod p.
The trustee then provides a proof that (g, y, alpha, dec_factor) is a proper DDH tuple, which yields a Chaum Pedersen proof of discrete log equality. Verification proceeds as follows:
verify_partial_decryption_proof(ciphertext, decryption_factor, proof, public_key):
# Here, we prove that (g, y, ciphertext.alpha, decryption_factor) is a DDH tuple, proving knowledge of secret key x.
# Before we were working with (g, alpha, y, beta/g^m), proving knowledge of the random factor r.
if pow(public_key.g, proof.response, public_key.p) !=
((proof.commitment.A * pow(public_key.y, proof.challenge, public_key.p)) % public_key.p):
return False
if pow(ciphertext.alpha, proof.response, public_key.p) !=
((proof.commitment.B * pow(decryption_factor, proof.challenge, public_key.p)) % public_key.p):
return False
# compute the challenge generation, Fiat-Shamir style
str_to_hash = str(proof.commitment.A) + "," + str(proof.commitment.B)
computed_challenge = int_sha(str_to_hash)
# check that the challenge matches
return computed_challenge == proof.challenge
Then, the decryption factors must be combined, and we check that:
dec_factor_1 * dec_factor_2 * ... * dec_factor_k * m = beta (mod p)
Then, the re-tally proceeds as follows.
retally_election(election, voters, result, result_proof):
# compute the election fingerprint
election_fingerprint = b64_sha(election.toJSON())
# keep track of voter fingerprints
vote_fingerprints = []
# keep track of running tallies, initialize at 0
# again, assuming operator overloading for homomorphic addition
tallies = [[0 for a in question.answers] for question in election.questions]
# go through each voter, check it
for voter in voters:
if not verify_vote(election, voter.vote):
return False
# compute fingerprint
vote_fingerprints.append(b64_sha(voter.vote.toJSON()))
# update tallies, looping through questions and answers within them
for question_num in range(len(election.questions)):
for choice_num in range(len(election.questions[question_num].answers)):
tallies[question_num][choice_num] = voter.vote.answers[question_num].choices[choice_num] +
tallies[question_num][choice_num]
# now we have tallied everything in ciphertexts, we must verify proofs
for question_num in range(len(election.questions)):
for choice_num in range(len(election.questions[question_num].answers)):
decryption_factor_combination = 1
for trustee_num in range(len(election.trustees)):
trustee = election.trustees[trustee_num]
# verify the tally for that choice within that question
# check that it decrypts to the claimed result with the claimed proof
if not verify_partial_decryption_proof(tallies[question_num][choice_num],
trustee.decryption_factors[question_num][choice_num],
trustee.decryption_proof[question_num][choice_num],
trustee.public_key):
return False
# combine the decryption factors progressively
decryption_factor_combination *= trustee.decryption_factors[question_num][choice_num]
if (decryption_factor_combination * election.result[question_num][choice_num]) % election.public_key.p
!= tallies[question_num][choice_num].beta % election.public_key.p:
return False
# return the complete tally, now that it is confirmed
return {
'election_fingerprint': election_fingerprint,
'vote_fingerprints' : vote_fingerprints,
'verified_tally' : result
}