def read_rows_cols_n_reps_threshold_indent(sbb_dict, db):
""" Read setup:server-array to extract rows/cols/n_reps into db. """
sbbd = sbb_dict['setup:server-array']
rows = sbbd['rows']
cols = sbbd['cols']
n_reps = sbbd['n_reps']
threshold = sbbd['threshold']
json_indent = sbbd['json_indent']
assert isinstance(rows, int) and rows > 0
assert isinstance(cols, int) and cols > 0
assert isinstance(n_reps, int) and n_reps > 0
assert isinstance(threshold, int) and threshold > 0
db['rows'] = rows
assert rows < 27
db['row_list'] = sv.row_list(rows)
db['cols'] = cols
db['n_reps'] = n_reps
db['threshold'] = threshold
assert n_reps < 27
db['k_list'] = sv.k_list(n_reps)
assert json_indent is None or isinstance(json_indent, int)
assert json_indent is None or json_indent >= 0
db['json_indent'] = json_indent
sv.set_json_indent(json_indent)
print('read_rows_cols_n_reps_threshold: successful.')
def read_rows_cols_n_reps_threshold_indent(sbb_dict, db):
""" Read setup:server-array to extract rows/cols/n_reps into db. """
sbbd = sbb_dict['setup:server-array']
rows = sbbd['rows']
cols = sbbd['cols']
n_reps = sbbd['n_reps']
threshold = sbbd['threshold']
json_indent = sbbd['json_indent']
assert isinstance(rows, int) and rows > 0
assert isinstance(cols, int) and cols > 0
assert isinstance(n_reps, int) and n_reps > 0
assert isinstance(threshold, int) and threshold > 0
db['rows'] = rows
assert rows < 27
db['row_list'] = sv.row_list(rows)
db['cols'] = cols
db['n_reps'] = n_reps
db['threshold'] = threshold
assert n_reps < 27
db['k_list'] = sv.k_list(n_reps)
assert json_indent is None or isinstance(json_indent, int)
assert json_indent is None or json_indent >= 0
db['json_indent'] = json_indent
sv.set_json_indent(json_indent)
print('read_rows_cols_n_reps_threshold: successful.')
def __init__(self, election, n_fail, n_leak):
""" Initialize server. This is one for the whole election.
The server array has the given number of rows and columns
as parts or sub-servers. Here we simulate the actions of
these sub-servers.
n_fail = number of servers that could fail
n_leak = number of servers that my leak information
"""
assert isinstance(n_fail, int) and n_fail >= 0
assert isinstance(n_leak, int) and n_leak >= 0
self.election = election
self.n_fail = n_fail
self.n_leak = n_leak
if self.n_fail > 0:
self.cols = 1 + n_leak
self.rows = 2 + n_fail + n_leak
self.threshold = 2 + n_leak # number of rows needed to reconstruct
else:
self.cols = 1 + n_leak
self.rows = 1 + n_leak
self.threshold = 1 + n_leak
rows = self.rows
cols = self.cols
threshold = self.threshold
# each row has an identifier in "abcd..."
assert rows <= 26
self.row_list = sv.row_list(rows)
self.challenges = dict()
# The state of the server in row i, col j is represented
# here in the dictionary P[race_id][i][j] for the given race
# where i in row_list and 0 <= j < cols.
# create one top-level dict sdb as database for this main server
self.sdb = dict()
# within the top level dict sdb, create a three-dimensional array of
# sub-dicts for data storage, each addressed as sdb[race_id][i][j]
for race in election.races:
race_id = race.race_id
self.sdb[race_id] = dict()
for i in self.row_list:
self.sdb[race_id][i] = dict()
for j in range(cols):
self.sdb[race_id][i][j] = dict()
# each server has its own random-number source for each race
# in practice, these could be derived from true random seeds input
# independently to each server
for race_id in election.race_ids:
for i in self.row_list:
for j in range(cols):
rand_name = "server:" + race_id + ":" + \
str(i) + ":" + str(j)
self.sdb[race_id][i][j]['rand_name'] = rand_name
sv.init_randomness_source(rand_name)
# within each sub-dict sdb[race_id][i][j] create a variety of lists for
# storage of cast votes and associated data, including 2m-way replicated
# lists needed for the 2m mixes (passes) needed.
for race_id in election.race_ids:
for i in self.row_list:
# first-column lists for storing cast votes and secrets
sdbp = self.sdb[race_id][i][0]
sdbp['ballot_id'] = dict() # ballot_id (indices from p_list)
sdbp['cu'] = dict() # commitments to u
sdbp['cv'] = dict() # commitments to v
sdbp['x'] = dict() # choice x, where x = u+v mod M
sdbp['u'] = dict() # u
sdbp['v'] = dict() # v
sdbp['ru'] = dict() # randomness to open com(u)
sdbp['rv'] = dict() # randomness to open com(v)
# for all columns, have 2m-way replicated data structures
for j in range(cols):
sdbp = self.sdb[race_id][i][j]
for k in election.k_list:
sdbp[k] = dict()
sdbp[k]['x'] = dict() # inputs on pass k
sdbp[k]['y'] = dict() # outputs on pass k
# last-column lists for storing published lists of commitments
for k in election.k_list:
sdbp = self.sdb[race_id][i][self.cols-1][k]
sdbp['y'] = dict()
sdbp['u'] = dict()
sdbp['v'] = dict()
sdbp['ru'] = dict()
sdbp['rv'] = dict()
sdbp['cu'] = dict()
sdbp['cv'] = dict()
# create one top-level dict sdb as database for this main server (a unshared copy of sbd)
self.sdb = deepcopy(self.sdb) # TODO remove
def __init__(self, election, n_fail, n_leak):
""" Initialize server. This is one for the whole election.
The server array has the given number of rows and columns
as parts or sub-servers. Here we simulate the actions of
these sub-servers.
n_fail = number of servers that could fail
n_leak = number of servers that my leak information
"""
assert isinstance(n_fail, int) and n_fail >= 0
assert isinstance(n_leak, int) and n_leak >= 0
self.election = election
self.n_fail = n_fail
self.n_leak = n_leak
if self.n_fail > 0:
self.cols = 1 + n_leak
self.rows = 2 + n_fail + n_leak
self.threshold = 2 + n_leak # number of rows needed to reconstruct
else:
self.cols = 1 + n_leak
self.rows = 1 + n_leak
self.threshold = 1 + n_leak
rows = self.rows
cols = self.cols
threshold = self.threshold
# each row has an identifier in "abcd..."
assert rows <= 26
self.row_list = sv.row_list(rows)
# The state of the server in row i, col j is represented
# here in the dictionary P[race_id][i][j] for the given race
# where i in row_list and 0 <= j < cols.
# create one top-level dict sdb as database for this main server
self.sdb = dict()
# within the top level dict sdb, create a three-dimensional array of
# sub-dicts for data storage, each addressed as sdb[race_id][i][j]
for race in election.races:
race_id = race.race_id
self.sdb[race_id] = dict()
for i in self.row_list:
self.sdb[race_id][i] = dict()
for j in range(cols):
self.sdb[race_id][i][j] = dict()
# each server has its own random-number source for each race
# in practice, these could be derived from true random seeds input
# independently to each server
for race_id in election.race_ids:
for i in self.row_list:
for j in range(cols):
rand_name = "server:" + race_id + ":" + \
str(i) + ":" + str(j)
self.sdb[race_id][i][j]['rand_name'] = rand_name
sv.init_randomness_source(rand_name)
# within each sub-dict sdb[race_id][i][j] create a variety of lists for
# storage of cast votes and associated data, including 2m-way replicated
# lists needed for the 2m mixes (passes) needed.
for race_id in election.race_ids:
for i in self.row_list:
# first-column lists for storing cast votes and secrets
sdbp = self.sdb[race_id][i][0]
sdbp['ballot_id'] = dict() # ballot_id (indices from p_list)
sdbp['cu'] = dict() # commitments to u
sdbp['cv'] = dict() # commitments to v
sdbp['x'] = dict() # choice x, where x = u+v mod M
sdbp['u'] = dict() # u
sdbp['v'] = dict() # v
sdbp['ru'] = dict() # randomness to open com(u)
sdbp['rv'] = dict() # randomness to open com(v)
# for all columns, have 2m-way replicated data structures
for j in range(cols):
sdbp = self.sdb[race_id][i][j]
for k in election.k_list:
sdbp[k] = dict()
sdbp[k]['x'] = dict() # inputs on pass k
sdbp[k]['y'] = dict() # outputs on pass k
# last-column lists for storing published lists of commitments
for k in election.k_list:
sdbp = self.sdb[race_id][i][self.cols-1][k]
sdbp['y'] = dict()
sdbp['u'] = dict()
sdbp['v'] = dict()
sdbp['ru'] = dict()
sdbp['rv'] = dict()
sdbp['cu'] = dict()
sdbp['cv'] = dict()
# post on log that server array is set up
election.sbb.post("setup:server-array",
{"rows": rows, "cols": cols,
"n_reps": election.n_reps,
"threshold": threshold,
'json_indent': election.json_indent},
time_stamp=False)
