def processMessage(self):
'''
Fetches a message from the queue and computes encrypted operations to get the generation / new grid state
and pushes new encrypted grid state in the queue to the client
:return:
'''
print("[SERVER SIMULATION] Start fetching message")
# fetch Message from queue, message is a dictionary with structure
# {"encrypted_old_grid": encrypted_old_grid, "encrypted_live_neighbours_grid": encrypted_live_neighbours_grid}
message_from_client = self.client_to_server_queue.get(0)
print("[SERVER SIMULATION] In Queue", message_from_client)
encrypted_old_grid = message_from_client["encrypted_old_grid"]
encrypted_live_neighbours_grid = message_from_client[
"encrypted_live_neighbours_grid"]
# Pyseal Evaluator
evaluator = Evaluator(self.encryptionContext)
# Computation of new grid
encrypted_new_grid = []
for i in range(self.N * self.N):
encrypted_result = Ciphertext()
evaluator.add(encrypted_old_grid[i],
encrypted_live_neighbours_grid[i], encrypted_result)
encrypted_new_grid.append(encrypted_result)
print("[SERVER SIMULATION] New Grid Computed")
print("[SERVER SIMULATION] Message to client ", encrypted_new_grid)
self.server_to_client_queue.put(encrypted_new_grid)
print(
"[SERVER SIMULATION] Put computed grid into server to client queue"
)
def initialize(self, use_old_keys=False):
# Initialize encryption params
self.init_encrypt_params()
# Check if the public & private key files exist
if os.path.isfile(defs.FN_FHE_PUBLIC_KEY) and \
os.path.isfile(defs.FN_FHE_PRIVATE_KEY) and \
use_old_keys == True:
self.log("Keys already exist. Reusing them instead.")
if not self.load_keys():
self.log("Failed to load keys")
return False
else:
# If not, then attempt to generate new ones
if not self.generate_keys():
self.log("Failed to generate keys")
return False
# Setup the rest of the crypto engine
self.encryptor = Encryptor(self.context, self.public_key)
self.evaluator = Evaluator(self.context)
self.decryptor = Decryptor(self.context, self.private_key)
# Set the initialized flag
self.initialized = True
return True
def test2():
img_path = '00001.jpg'
img = cv2.imread(img_path, cv2.IMREAD_GRAYSCALE)
print("Original image dimensions {}".format(img.shape))
sift = cv2.xfeatures2d.SIFT_create()
(kps, desc) = sift.detectAndCompute(img, None)
desc = preprocessing.normalize(np.array(
desc.flatten()[:DESC_SIZE]).reshape(1, DESC_SIZE),
norm='l2')
descriptor_vec1 = desc
descriptor_vec2 = descriptor_vec1
context = config()
public_key, secret_key = keygen(context)
encoder = IntegerEncoder(context.plain_modulus())
encryptor = Encryptor(context, public_key)
crtbuilder = PolyCRTBuilder(context)
evaluator = Evaluator(context)
decryptor = Decryptor(context, secret_key)
slot_count = (int)(crtbuilder.slot_count())
print("slot count {}".format(slot_count))
print("Plaintext shape", descriptor_vec1.shape)
plain_matrix = decompose_plain(slot_count, descriptor_vec1, crtbuilder)
for i in range(10000):
encrypted_matrix = Ciphertext()
print("Encrypting: ")
time_start = time.time()
encryptor.encrypt(plain_matrix, encrypted_matrix)
time_end = time.time()
print("Done in time {}".format((str)(1000 * (time_end - time_start))))
print("Square:")
time_start = time.time()
evaluator.square(encrypted_matrix)
time_end = time.time()
print("Square is done in {} miliseconds".format(
(str)(1000 * (time_end - time_start))))
plain_result = Plaintext()
print("Decryption plain: ")
time_start = time.time()
decryptor.decrypt(encrypted_matrix, plain_result)
time_end = time.time()
print("Decryption is done in {} miliseconds".format(
(str)(1000 * (time_end - time_start))))
# print("Plaintext polynomial: {}".format(plain_result.to_string()))
# print("Decoded integer: {}".format(encoder.decode_int32(plain_result)))
print("Noise budget {} bits".format(
decryptor.invariant_noise_budget(encrypted_matrix)))
def example_rotation_ckks():
print("Example: Rotation / Rotation in CKKS");
#Rotations in the CKKS scheme work very similarly to rotations in BFV.
parms = EncryptionParameters(scheme_type.CKKS)
poly_modulus_degree = 8192
parms.set_poly_modulus_degree(poly_modulus_degree)
parms.set_coeff_modulus(CoeffModulus.Create(
poly_modulus_degree, IntVector([40, 40, 40, 40, 40])))
context = SEALContext.Create(parms)
print_parameters(context)
keygen = KeyGenerator(context)
public_key = keygen.public_key()
secret_key = keygen.secret_key()
relin_keys = keygen.relin_keys()
gal_keys = keygen.galois_keys()
encryptor = Encryptor(context, public_key)
evaluator = Evaluator(context)
decryptor = Decryptor(context, secret_key)
ckks_encoder = CKKSEncoder(context)
slot_count = ckks_encoder.slot_count()
print("Number of slots: {}".format(slot_count))
step_size = 1.0 / (slot_count - 1)
input = DoubleVector(list(map(lambda x: x*step_size, range(0, slot_count))))
print_vector(input)
scale = 2.0**50
print("Encode and encrypt.")
plain = Plaintext()
ckks_encoder.encode(input, scale, plain)
encrypted = Ciphertext()
encryptor.encrypt(plain, encrypted)
rotated = Ciphertext()
print("Rotate 2 steps left.")
evaluator.rotate_vector(encrypted, 2, gal_keys, rotated)
print(" + Decrypt and decode ...... Correct.")
decryptor.decrypt(rotated, plain)
result = DoubleVector()
ckks_encoder.decode(plain, result)
print_vector(result)
def __init__(self,
poly_modulus="1x^1024 + 1",
coef_modulus_n_primes=20,
plain_modulus=1 << 32):
"""
Set up encryption context for encoder and decoder
:param poly_modulus:
:param coef_modulus_n_primes:
:param plain_modulus:
"""
self.params = EncryptionParameters()
self.params.set_poly_modulus(poly_modulus)
self.params.set_coeff_modulus([
seal.SmallModulus(p)
for p in FracContext.primes[:coef_modulus_n_primes]
])
self.params.set_plain_modulus(plain_modulus)
self.context = SEALContext(self.params)
self.print_parameters(self.context)
self.keygen = KeyGenerator(self.context)
self.public_key = self.keygen.public_key()
self.secret_key = self.keygen.secret_key()
self.evaluator = Evaluator(self.context)
class vec_plain_multiply(object):
"""Multiply componentwise cipher and plain along cipher's last dimension
cipher.shape[-1]= plain.shape
"""
def __init__(self, context):
self.evaluator = Evaluator(context)
def __call__(self, cipher, plain):
"""In order to not affect cipher for other calculations, make copy"""
cipher = dc(cipher)
if cipher.shape[-1] != plain.shape[0]:
raise ValueError("The cipher shape and plain shape don't match.")
for indices in np.ndindex(cipher.shape[:-1]):
for i in range(plain.shape[0]):
self.evaluator.multiply_plain(cipher[indices][i], plain[i])
return cipher
def seal_obj():
# params obj
params = EncryptionParameters()
# set params
params.set_poly_modulus("1x^4096 + 1")
params.set_coeff_modulus(seal.coeff_modulus_128(4096))
params.set_plain_modulus(1 << 16)
# get context
context = SEALContext(params)
# get evaluator
evaluator = Evaluator(context)
# gen keys
keygen = KeyGenerator(context)
public_key = keygen.public_key()
private_key = keygen.secret_key()
# evaluator keys
ev_keys = EvaluationKeys()
keygen.generate_evaluation_keys(30, ev_keys)
# get encryptor and decryptor
encryptor = Encryptor(context, public_key)
decryptor = Decryptor(context, private_key)
# float number encoder
encoder = FractionalEncoder(context.plain_modulus(),
context.poly_modulus(), 64, 32, 3)
return evaluator, encoder.encode, encoder.decode, encryptor.encrypt, decryptor.decrypt, ev_keys
def __init__(self,
context: SEALContext,
scale: float,
poly_modulus_degree: int,
public_key: PublicKey = None,
secret_key: SecretKey = None,
relin_keys: RelinKeys = None,
galois_keys: GaloisKeys = None):
self.scale = scale
self.context = context
self.encoder = CKKSEncoder(context)
self.evaluator = Evaluator(context)
self.encryptor = Encryptor(context, public_key)
self.decryptor = Decryptor(context, secret_key)
self.relin_keys = relin_keys
self.galois_keys = galois_keys
self.poly_modulus_degree_log = np.log2(poly_modulus_degree)
def set_parms(self, parms: EncryptionParameters, print_parms=False):
self._parms = parms
self._context = SEALContext.Create(self._parms)
self._encoder = IntegerEncoder(self._context)
self._evaluator = Evaluator(self._context)
if print_parms:
self.print_parameters(self._context)
def __init__(self, matrix=None):
"""
:param matrix: numpy.ndarray to be encrypted.
"""
self.parms = EncryptionParameters()
self.parms.set_poly_modulus("1x^2048 + 1")
self.parms.set_coeff_modulus(seal.coeff_modulus_128(2048))
self.parms.set_plain_modulus(1 << 8)
self.context = SEALContext(self.parms)
# self.encoder = IntegerEncoder(self.context.plain_modulus())
self.encoder = FractionalEncoder(self.context.plain_modulus(),
self.context.poly_modulus(), 64, 32,
3)
self.keygen = KeyGenerator(self.context)
self.public_key = self.keygen.public_key()
self.secret_key = self.keygen.secret_key()
self.encryptor = Encryptor(self.context, self.public_key)
self.decryptor = Decryptor(self.context, self.secret_key)
self.evaluator = Evaluator(self.context)
self._saved = False
self._encrypted = False
self._id = '{0:04d}'.format(np.random.randint(1000))
if matrix is not None:
assert len(
matrix.shape) == 2, "Only 2D numpy matrices accepted currently"
self.matrix = np.copy(matrix)
self.encrypted_matrix = np.empty(self.matrix.shape, dtype=object)
for i in range(self.matrix.shape[0]):
for j in range(self.matrix.shape[1]):
self.encrypted_matrix[i, j] = Ciphertext()
else:
self.matrix = None
self.encrypted_matrix = None
print(self._id, "Created")
def initialize_fractional(
poly_modulus_degree=4096,
security_level_bits=128,
plain_modulus_power_of_two=10,
plain_modulus=None,
encoder_integral_coefficients=1024,
encoder_fractional_coefficients=3072,
encoder_base=2
):
parameters = EncryptionParameters()
poly_modulus = "1x^" + str(poly_modulus_degree) + " + 1"
parameters.set_poly_modulus(poly_modulus)
if security_level_bits == 128:
parameters.set_coeff_modulus(seal.coeff_modulus_128(poly_modulus_degree))
elif security_level_bits == 192:
parameters.set_coeff_modulus(seal.coeff_modulus_192(poly_modulus_degree))
else:
parameters.set_coeff_modulus(seal.coeff_modulus_128(poly_modulus_degree))
print("Info: security_level_bits unknown - using default security_level_bits = 128")
if plain_modulus is None:
plain_modulus = 1 << plain_modulus_power_of_two
parameters.set_plain_modulus(plain_modulus)
context = SEALContext(parameters)
print_parameters(context)
global encoder
encoder = FractionalEncoder(
context.plain_modulus(),
context.poly_modulus(),
encoder_integral_coefficients,
encoder_fractional_coefficients,
encoder_base
)
keygen = KeyGenerator(context)
public_key = keygen.public_key()
secret_key = keygen.secret_key()
global encryptor
encryptor = Encryptor(context, public_key)
global evaluator
evaluator = Evaluator(context)
global decryptor
decryptor = Decryptor(context, secret_key)
global evaluation_keys
evaluation_keys = EvaluationKeys()
keygen.generate_evaluation_keys(16, evaluation_keys)
def _setup_members(self, context, config):
self._encoder = FractionalEncoder(context.plain_modulus(),
context.poly_modulus(),
config['int_coeff'],
config['fract_coeff'],
config['base'])
self._evaluator = Evaluator(context)
pk, sk, self._ev_key = self._create_keys(context)
self._encryptor = Encryptor(context, pk)
self._decryptor = Decryptor(context, sk)
def __init__(self, seal_server_params, cipher_save_path):
self.parms = EncryptionParameters(scheme_type.CKKS)
self.cipher_save_path = cipher_save_path
# Set Coeff modulus
coeff_modulus = [
SmallModulus(i) for i in seal_server_params["coeff_modulus"]
]
self.parms.set_coeff_modulus(coeff_modulus)
# Set Plain modulus
self.parms.set_plain_modulus(seal_server_params["plain_modulus"])
# Set Poly modulus degree
self.parms.set_poly_modulus_degree(
seal_server_params["poly_modulus_degree"])
self.context = SEALContext.Create(self.parms)
self.evaluator = Evaluator(self.context)
# Store the encrypted here
self._encrypts = []
def __init__(self, modulus, degree):
self.modulus = modulus
self.degree = degree
self.acceptable_degree = [1024, 2048, 4096, 8192, 16384]
if self.degree not in self.acceptable_degree:
raise Exception(f"Get {self.degree}, but expect degree {self.acceptable_degree}")
self.parms = EncryptionParameters(scheme_type.BFV)
self.parms.set_poly_modulus_degree(self.degree)
self.parms.set_coeff_modulus(CoeffModulus.BFVDefault(self.degree))
# self.parms.set_coeff_modulus(CoeffModulus.Create(self.degree, [60]))
self.parms.set_plain_modulus(self.modulus)
# print(self.parms.coeff_modulus()[0].value())
self.context = SEALContext.Create(self.parms)
self.keygen = KeyGenerator(self.context)
self.evaluator = Evaluator(self.context)
self.batch_encoder = BatchEncoder(self.context)
def inner_product(cypher1, cypher2):
# We also set up an Encryptor, Evaluator, and Decryptor here.
evaluator = Evaluator(context)
decryptor = Decryptor(context, secret_key)
for i in range(len(cypher1)):
evaluator.multiply(cypher1[i], cypher2[i])
encrypted_result = Ciphertext()
evaluator.add_many(cypher1, encrypted_result)
return encrypted_result
def initialize_encryption():
print_example_banner("Example: Basics I");
parms = EncryptionParameters()
parms.set_poly_modulus("1x^2048 + 1")
# factor: 0xfffffffff00001.
parms.set_coeff_modulus(seal.coeff_modulus_128(2048))
parms.set_plain_modulus(1 << 8)
context = SEALContext(parms)
print_parameters(context);
# Here we choose to create an IntegerEncoder with base b=2.
encoder = IntegerEncoder(context.plain_modulus())
keygen = KeyGenerator(context)
public_key = keygen.public_key()
secret_key = keygen.secret_key()
encryptor = Encryptor(context, public_key)
evaluator = Evaluator(context)
decryptor = Decryptor(context, secret_key)
return encryptor, evaluator, decryptor, encoder, context
def do_per_amount(amount, subtract_from=15):
"""
Called on every message in the stream
"""
print("Transaction amount ", amount)
parms = EncryptionParameters()
parms.set_poly_modulus("1x^2048 + 1")
parms.set_coeff_modulus(seal.coeff_modulus_128(2048))
parms.set_plain_modulus(1 << 8)
context = SEALContext(parms)
# Encode
encoder = FractionalEncoder(context.plain_modulus(),
context.poly_modulus(), 64, 32, 3)
# To create a fresh pair of keys one can call KeyGenerator::generate() at any time.
keygen = KeyGenerator(context)
public_key = keygen.public_key()
secret_key = keygen.secret_key()
encryptor = Encryptor(context, public_key)
plain1 = encoder.encode(amount)
encoded2 = encoder.encode(subtract_from)
# Encrypt
encrypted1 = Ciphertext(parms)
encryptor.encrypt(plain1, encrypted1)
# Evaluate
evaluator = Evaluator(context)
evaluated = evaluate_subtraction_from_plain(evaluator, encrypted1,
encoded2)
# Decrypt and decode
decryptor = Decryptor(context, secret_key)
plain_result = Plaintext()
decryptor.decrypt(evaluated, plain_result)
result = encoder.decode(plain_result)
str_result = "Amount left = " + str(result)
print(str_result)
return str_result
def configure_params(self):
with yaspin(
text=
'Initializing Encryptor, Eavaluator, Decryptor with generated parameters.....',
spinner='dots') as sp2:
self.frac_encoder = FractionalEncoder(self.context.plain_modulus(),
self.context.poly_modulus(),
64, 32, 3)
self.encryptor = Encryptor(self.context, self.public_key)
self.evaluator = Evaluator(self.context)
self.decryptor = Decryptor(self.context, self.secret_key)
if self.batching:
self.crtbuilder = PolyCRTBuilder(self.context)
sp2.hide()
print(HTML(
u'<b>></b> <msg> The system is ready to start encryption.</msg>'
),
style=style)
sp2.show()
sp2.ok("✔")
def encryption(value):
# IntegerEncoder with base 2
encoder = IntegerEncoder(context.plain_modulus())
# generate public/private keys
keygen = KeyGenerator(context)
public_key = keygen.public_key()
secret_key = keygen.secret_key()
# encrypts public key
encryptor = Encryptor(context, public_key)
# perform computations on ciphertexts
evaluator = Evaluator(context)
# decrypts secret key
decryptor = Decryptor(context, secret_key)
# perform encryptions
plaintext = encoder.encode(value)
# convert into encrypted ciphertext
encrypt = Ciphertext()
encryptor.encrypt(plaintext, encrypt)
print("Encryption successful!")
print("Encrypted ciphertext: " + (str)(value) + " as " +
plaintext.to_string())
# noise budget of fresh encryptions
print("Noise budget: " + (str)(decryptor.invariant_noise_budget(encrypt)) +
" bits")
# decrypts result
result = Plaintext()
decryptor.decrypt(encrypt, result)
print("Decryption successful!")
print("Plaintext: " + result.to_string())
# decode for original integer
print("Original node: " + (str)(encoder.decode_int32(result)) + "\n")
def __init__(self, poly_modulus = 2048 ,bit_strength = 128 ,plain_modulus = 1<<8, integral_coeffs = 64, fractional_coeffs = 32, fractional_base = 3):
parms = EncryptionParameters()
parms.set_poly_modulus("1x^{} + 1".format(poly_modulus))
if (bit_strength == 128):
parms.set_coeff_modulus(seal.coeff_modulus_128(poly_modulus))
else:
parms.set_coeff_modulus(seal.coeff_modulus_192(poly_modulus))
parms.set_plain_modulus(plain_modulus)
self.parms = parms
context = SEALContext(parms)
keygen = KeyGenerator(context)
public_key = keygen.public_key()
secret_key = keygen.secret_key()
self.encryptor = Encryptor(context, public_key)
self.evaluator = Evaluator(context)
self.decryptor = Decryptor(context, secret_key)
self.encoder = FractionalEncoder(context.plain_modulus(), context.poly_modulus(), integral_coeffs, fractional_coeffs, fractional_base)
def test1():
#TODO make the function taking dir name, iterating through all the descriptors, encrypting
#TODO add progress bar - the videos are decrypted
#TODO make a function taking a query and passing it to the sklearn function KNN with custom similarity funtion
#TODO add progress bar - the search is performed (calculate distance between encrypted vectors)
#TODO return results
#TODO Vlad Display. The results are true. The same as we would compute similarity between ncrypted vectors.
# In the same time we did not have to decrypt vectors stored in 3rd parity service to perform a search.
#TODO get the metrics
#TODO how to opimize
a = np.ones((1, DESC_SIZE))
b = np.ones((1, DESC_SIZE))
for i in range(a.shape[1]):
a[0, i] = random.uniform(0.0, 1.0)
b[0, i] = random.uniform(0.0, 1.0)
print("Descriptors for images a and b are: ")
print("a ", a)
print("b ", b)
context, params = config()
public_key, secret_key = keygen(context)
frac_encoder = FractionalEncoder(context.plain_modulus(),
context.poly_modulus(), 64, 32, 3)
encryptor = Encryptor(context, public_key)
evaluator = Evaluator(context)
decryptor = Decryptor(context, secret_key)
e1 = encrypt_vec(params, encryptor, frac_encoder, a)
e3 = encrypt_vec(params, encryptor, frac_encoder, b)
print("Calculate distance between plain a and b:")
sim = euclidean_dist(a, b)
print("Similarity between a and b: {}".format(sim))
print("Calculating distance between encrypted a and b:")
time_start = time.time()
enc_res = euclidean_dist_enc(evaluator, e1, e3)
time_end = time.time()
print("Done. Time: {} miliseconds".format(
(str)(1000 * (time_end - time_start))))
plain_result = Plaintext()
print("Decrypting result: ")
time_start = time.time()
decryptor.decrypt(enc_res, plain_result)
res = frac_encoder.encode(plain_result)
time_end = time.time()
print("Done. Time: {} miliseconds".format(
(str)(1000 * (time_end - time_start))))
print(
"........................................................................"
)
print("Noise budget {} bits".format(
decryptor.invariant_noise_budget(enc_res)))
print("Decrypted result {}, original result {}".format(res, sim))
print("Calculate distance between plain a and a:")
sim = euclidean_dist(a, a.copy())
print("Similarity between a and b: {}".format(sim))
print("Calculating distance between encrypted a and a:")
time_start = time.time()
enc_res = euclidean_dist_enc(evaluator, e1, e1)
time_end = time.time()
print("Done. Time: {} miliseconds".format(
(str)(1000 * (time_end - time_start))))
plain_result = Plaintext()
print("Decrypting result: ")
time_start = time.time()
decryptor.decrypt(enc_res, plain_result)
res = frac_encoder.encode(plain_result)
time_end = time.time()
print("Done. Time: {} miliseconds".format(
(str)(1000 * (time_end - time_start))))
print(
"........................................................................."
)
print("Noise budget {} bits".format(
decryptor.invariant_noise_budget(enc_res)))
print("Decrypted result {}, original result {}".format(res, sim))
def dot_product():
print("Example: Weighted Average")
# In this example we demonstrate the FractionalEncoder, and use it to compute
# a weighted average of 10 encrypted rational numbers. In this computation we
# perform homomorphic multiplications of ciphertexts by plaintexts, which is
# much faster than regular multiplications of ciphertexts by ciphertexts.
# Moreover, such `plain multiplications' never increase the ciphertext size,
# which is why we have no need for evaluation keys in this example.
# We start by creating encryption parameters, setting up the SEALContext, keys,
# and other relevant objects. Since our computation has multiplicative depth of
# only two, it suffices to use a small poly_modulus.
parms = EncryptionParameters()
parms.set_poly_modulus("1x^2048 + 1")
parms.set_coeff_modulus(seal.coeff_modulus_128(2048))
parms.set_plain_modulus(1 << 8)
context = SEALContext(parms)
print_parameters(context)
keygen = KeyGenerator(context)
keygen2 = KeyGenerator(context)
public_key = keygen.public_key()
secret_key = keygen.secret_key()
secret_key2 = keygen.secret_key()
# We also set up an Encryptor, Evaluator, and Decryptor here.
encryptor = Encryptor(context, public_key)
evaluator = Evaluator(context)
decryptor = Decryptor(context, secret_key2)
# Create a vector of 10 rational numbers (as doubles).
# rational_numbers = [3.1, 4.159, 2.65, 3.5897, 9.3, 2.3, 8.46, 2.64, 3.383, 2.795]
rational_numbers = np.random.rand(10)
# Create a vector of weights.
# coefficients = [0.1, 0.05, 0.05, 0.2, 0.05, 0.3, 0.1, 0.025, 0.075, 0.05]
coefficients = np.random.rand(10)
my_result = np.dot(rational_numbers, coefficients)
# We need a FractionalEncoder to encode the rational numbers into plaintext
# polynomials. In this case we decide to reserve 64 coefficients of the
# polynomial for the integral part (low-degree terms) and expand the fractional
# part to 32 digits of precision (in base 3) (high-degree terms). These numbers
# can be changed according to the precision that is needed; note that these
# choices leave a lot of unused space in the 2048-coefficient polynomials.
encoder = FractionalEncoder(context.plain_modulus(), context.poly_modulus(), 64, 32, 3)
# We create a vector of ciphertexts for encrypting the rational numbers.
encrypted_rationals = []
rational_numbers_string = "Encoding and encrypting: "
for i in range(10):
# We create our Ciphertext objects into the vector by passing the
# encryption parameters as an argument to the constructor. This ensures
# that enough memory is allocated for a size 2 ciphertext. In this example
# our ciphertexts never grow in size (plain multiplication does not cause
# ciphertext growth), so we can expect the ciphertexts to remain in the same
# location in memory throughout the computation. In more complicated examples
# one might want to call a constructor that reserves enough memory for the
# ciphertext to grow to a specified size to avoid costly memory moves when
# multiplications and relinearizations are performed.
encrypted_rationals.append(Ciphertext(parms))
encryptor.encrypt(encoder.encode(rational_numbers[i]), encrypted_rationals[i])
rational_numbers_string += (str)(rational_numbers[i])[:6]
if i < 9: rational_numbers_string += ", "
print(rational_numbers_string)
# Next we encode the coefficients. There is no reason to encrypt these since they
# are not private data.
encoded_coefficients = []
encoded_coefficients_string = "Encoding plaintext coefficients: "
encrypted_coefficients =[]
for i in range(10):
encoded_coefficients.append(encoder.encode(coefficients[i]))
encrypted_coefficients.append(Ciphertext(parms))
encryptor.encrypt(encoded_coefficients[i], encrypted_coefficients[i])
encoded_coefficients_string += (str)(coefficients[i])[:6]
if i < 9: encoded_coefficients_string += ", "
print(encoded_coefficients_string)
# We also need to encode 0.1. Multiplication by this plaintext will have the
# effect of dividing by 10. Note that in SEAL it is impossible to divide
# ciphertext by another ciphertext, but in this way division by a plaintext is
# possible.
div_by_ten = encoder.encode(0.1)
# Now compute each multiplication.
prod_result = [Ciphertext() for i in range(10)]
prod_result2 = [Ciphertext() for i in range(10)]
print("Computing products: ")
for i in range(10):
# Note how we use plain multiplication instead of usual multiplication. The
# result overwrites the first argument in the function call.
evaluator.multiply_plain(encrypted_rationals[i], encoded_coefficients[i], prod_result[i])
evaluator.multiply(encrypted_rationals[i], encrypted_coefficients[i], prod_result2[i])
print("Done")
# To obtain the linear sum we need to still compute the sum of the ciphertexts
# in encrypted_rationals. There is an easy way to add together a vector of
# Ciphertexts.
encrypted_result = Ciphertext()
encrypted_result2 = Ciphertext()
print("Adding up all 10 ciphertexts: ")
evaluator.add_many(prod_result, encrypted_result)
evaluator.add_many(prod_result2, encrypted_result2)
print("Done")
# Perform division by 10 by plain multiplication with div_by_ten.
# print("Dividing by 10: ")
# evaluator.multiply_plain(encrypted_result, div_by_ten)
# print("Done")
# How much noise budget do we have left?
print("Noise budget in result: " + (str)(decryptor.invariant_noise_budget(encrypted_result)) + " bits")
# Decrypt, decode, and print result.
plain_result = Plaintext()
plain_result2 = Plaintext()
print("Decrypting result: ")
decryptor.decrypt(encrypted_result, plain_result)
decryptor.decrypt(encrypted_result2, plain_result2)
print("Done")
result = encoder.decode(plain_result)
print("Weighted average: " + (str)(result)[:8])
result2 = encoder.decode(plain_result2)
print("Weighted average: " + (str)(result2)[:8])
print('\n\n', my_result)
def pickle_ciphertext():
parms = EncryptionParameters()
parms.set_poly_modulus("1x^2048 + 1")
parms.set_coeff_modulus(seal.coeff_modulus_128(2048))
parms.set_plain_modulus(1 << 8)
context = SEALContext(parms)
# Print the parameters that we have chosen
print_parameters(context);
encoder = IntegerEncoder(context.plain_modulus())
keygen = KeyGenerator(context)
public_key = keygen.public_key()
secret_key = keygen.secret_key()
# To be able to encrypt, we need to construct an instance of Encryptor. Note that
# the Encryptor only requires the public key.
encryptor = Encryptor(context, public_key)
# Computations on the ciphertexts are performed with the Evaluator class.
evaluator = Evaluator(context)
# We will of course want to decrypt our results to verify that everything worked,
# so we need to also construct an instance of Decryptor. Note that the Decryptor
# requires the secret key.
decryptor = Decryptor(context, secret_key)
# We start by encoding two integers as plaintext polynomials.
value1 = 5;
plain1 = encoder.encode(value1);
print("Encoded " + (str)(value1) + " as polynomial " + plain1.to_string() + " (plain1)")
value2 = -7;
plain2 = encoder.encode(value2);
print("Encoded " + (str)(value2) + " as polynomial " + plain2.to_string() + " (plain2)")
# Encrypting the values is easy.
encrypted1 = Ciphertext()
encrypted2 = Ciphertext()
print("Encrypting plain1: ", encrypted1)
encryptor.encrypt(plain1, encrypted1)
print("Done (encrypted1)", encrypted1)
print("Encrypting plain2: ")
encryptor.encrypt(plain2, encrypted2)
print("Done (encrypted2)")
# output = open('ciphertest.pkl', 'wb')
# dill.dumps(encrypted_save, output)
# output.close()
# encrypted1 = dill.load(open('ciphertest.pkl', 'rb'))
output = open('session.pkl', 'wb')
dill.dump_session('session.pkl')
del encrypted1
sill.load_session('session.pkl')
# To illustrate the concept of noise budget, we print the budgets in the fresh
# encryptions.
print("Noise budget in encrypted1: " + (str)(decryptor.invariant_noise_budget(encrypted1)) + " bits")
print("Noise budget in encrypted2: " + (str)(decryptor.invariant_noise_budget(encrypted2)) + " bits")
# As a simple example, we compute (-encrypted1 + encrypted2) * encrypted2.
# Negation is a unary operation.
evaluator.negate(encrypted1)
# Negation does not consume any noise budget.
print("Noise budget in -encrypted1: " + (str)(decryptor.invariant_noise_budget(encrypted1)) + " bits")
# Addition can be done in-place (overwriting the first argument with the result,
# or alternatively a three-argument overload with a separate destination variable
# can be used. The in-place variants are always more efficient. Here we overwrite
# encrypted1 with the sum.
evaluator.add(encrypted1, encrypted2)
# It is instructive to think that addition sets the noise budget to the minimum
# of the input noise budgets. In this case both inputs had roughly the same
# budget going on, and the output (in encrypted1) has just slightly lower budget.
# Depending on probabilistic effects, the noise growth consumption may or may
# not be visible when measured in whole bits.
print("Noise budget in -encrypted1 + encrypted2: " + (str)(decryptor.invariant_noise_budget(encrypted1)) + " bits")
# Finally multiply with encrypted2. Again, we use the in-place version of the
# function, overwriting encrypted1 with the product.
evaluator.multiply(encrypted1, encrypted2)
# Multiplication consumes a lot of noise budget. This is clearly seen in the
# print-out. The user can change the plain_modulus to see its effect on the
# rate of noise budget consumption.
print("Noise budget in (-encrypted1 + encrypted2) * encrypted2: " + (str)(
decryptor.invariant_noise_budget(encrypted1)) + " bits")
# Now we decrypt and decode our result.
plain_result = Plaintext()
print("Decrypting result: ")
decryptor.decrypt(encrypted1, plain_result)
print("Done")
# Print the result plaintext polynomial.
print("Plaintext polynomial: " + plain_result.to_string())
# Decode to obtain an integer result.
print("Decoded integer: " + (str)(encoder.decode_int32(plain_result)))
########################## paramaters required #################################
parms = EncryptionParameters()
parms.set_poly_modulus("1x^16384 + 1")
parms.set_coeff_modulus(seal.coeff_modulus_128(8192))
parms.set_plain_modulus(1 << 25)
context = SEALContext(parms)
encoderF = FractionalEncoder(context.plain_modulus(), context.poly_modulus(), 34, 30, 3)
keygen = KeyGenerator(context)
public_key = keygen.public_key()
secret_key = keygen.secret_key()
encryptor = Encryptor(context, public_key)
evaluator = Evaluator(context)
decryptor = Decryptor(context, secret_key)
num_cores = multiprocessing.cpu_count() -1
N=4
b = numpy.random.random_integers(1,10,size=(N,N))
X = (b + b.T)/2
print("\nX:")
print(X)
print(numpy.linalg.det(X))
print("Inverse by Numpy:")
print(numpy.linalg.inv(X))
print("\nMain program: \n")
X= encrypting_Matrix(X)
X_inv=inverseMatrix(X)
def example_rotation_bfv():
print("Example: Rotation / Rotation in BFV")
parms = EncryptionParameters(scheme_type.BFV)
poly_modulus_degree = 8192
parms.set_poly_modulus_degree(poly_modulus_degree)
parms.set_coeff_modulus(CoeffModulus.BFVDefault(poly_modulus_degree))
parms.set_plain_modulus(PlainModulus.Batching(poly_modulus_degree, 20))
context = SEALContext.Create(parms)
print_parameters(context)
keygen = KeyGenerator(context)
public_key = keygen.public_key()
secret_key = keygen.secret_key()
relin_keys = keygen.relin_keys()
encryptor = Encryptor(context, public_key)
evaluator = Evaluator(context)
decryptor = Decryptor(context, secret_key)
batch_encoder = BatchEncoder(context)
slot_count = batch_encoder.slot_count()
row_size = int(slot_count / 2)
print("Plaintext matrix row size: {}".format(row_size))
pod_matrix = UInt64Vector([0]*slot_count)
pod_matrix[0] = 0
pod_matrix[1] = 1
pod_matrix[2] = 2
pod_matrix[3] = 3
pod_matrix[row_size] = 4
pod_matrix[row_size + 1] = 5
pod_matrix[row_size + 2] = 6
pod_matrix[row_size + 3] = 7
print("Input plaintext matrix:")
print_matrix(pod_matrix, row_size)
#First we use BatchEncoder to encode the matrix into a plaintext. We encrypt
#the plaintext as usual.
plain_matrix = Plaintext()
print("Encode and encrypt.")
batch_encoder.encode(pod_matrix, plain_matrix)
encrypted_matrix = Ciphertext()
encryptor.encrypt(plain_matrix, encrypted_matrix)
print(" + Noise budget in fresh encryption: {} bits".format(
decryptor.invariant_noise_budget(encrypted_matrix)))
#Rotations require yet another type of special key called `Galois keys'. These
#are easily obtained from the KeyGenerator.
gal_keys = keygen.galois_keys()
#Now rotate both matrix rows 3 steps to the left, decrypt, decode, and print.
print("Rotate rows 3 steps left.")
evaluator.rotate_rows_inplace(encrypted_matrix, 3, gal_keys)
plain_result = Plaintext()
print(" + Noise budget after rotation: {} bits".format(
decryptor.invariant_noise_budget(encrypted_matrix)))
print(" + Decrypt and decode ...... Correct.")
decryptor.decrypt(encrypted_matrix, plain_result)
batch_encoder.decode(plain_result, pod_matrix)
print_matrix(pod_matrix, row_size)
#We can also rotate the columns, i.e., swap the rows.
print("Rotate columns.")
evaluator.rotate_columns_inplace(encrypted_matrix, gal_keys)
print(" + Noise budget after rotation: {} bits".format(
decryptor.invariant_noise_budget(encrypted_matrix)))
print(" + Decrypt and decode ...... Correct.")
decryptor.decrypt(encrypted_matrix, plain_result)
batch_encoder.decode(plain_result, pod_matrix)
print_matrix(pod_matrix, row_size)
#Finally, we rotate the rows 4 steps to the right, decrypt, decode, and print.
print("Rotate rows 4 steps right.")
evaluator.rotate_rows_inplace(encrypted_matrix, -4, gal_keys)
print(" + Noise budget after rotation: {} bits".format(
decryptor.invariant_noise_budget(encrypted_matrix)))
print(" + Decrypt and decode ...... Correct.")
decryptor.decrypt(encrypted_matrix, plain_result)
batch_encoder.decode(plain_result, pod_matrix)
print_matrix(pod_matrix, row_size)
def __init__(self, context):
self.evaluator = Evaluator(context)
def __init__(self, context, keygen):
self.relinear = Evaluator(context).relinearize
self.ev_keys = EvaluationKeys()
keygen.generate_evaluation_keys(10, self.ev_keys)
def encrypt(input_file):
X = np.load(input_file)
print("Starting the system....\n")
y, people_descriptors = search_for_centroids(X)
X, y = unison_shuffled_copies(X, y)
np.save(input_file, X)
np.save('./class_lables.npy', np.array(y))
np.save('./centroids.npy', np.array(people_descriptors))
print(
"All necessary dependencies are installed. Everything is up-to-date!")
print("The encryption mode is entered!")
time_start = time.time()
print('Configuring the encryption parameters')
context, params = config()
time_end = time.time()
#TODO time for the report. Put to the slides
#TODO Remove from logs
print("Parameters are configured. Time: {}\n".format(
(str)(1000 * (time_end - time_start))))
#print("Key generation .....")
time_start = time.time()
with yaspin(text='Generating public/private key pair',
spinner='dots') as sp1:
public_key, secret_key = keygen(context)
time.sleep(1)
sp1.hide()
print(HTML(
u'<b>></b> <msg>public/private key pair </msg> <sub-msg>is generated</sub-msg>'
),
style=style)
sp1.show()
sp1.ok("✔")
time_end = time.time()
print("Keys are generated! Time: {}".format(
(str)(1000 * (time_end - time_start))))
with yaspin(
text=
'Initializing Encryptor, Eavaluator, Decryptor with generated parameters.....',
spinner='dots') as sp2:
frac_encoder = FractionalEncoder(context.plain_modulus(),
context.poly_modulus(), 64, 32, 3)
encryptor = Encryptor(context, public_key)
evaluator = Evaluator(context)
decryptor = Decryptor(context, secret_key)
p = []
p.append(params)
p.append(context)
p.append(frac_encoder)
p.append(encryptor)
p.append(evaluator)
p.append(decryptor)
ENC_CONF = p
sp2.hide()
print(HTML(
u'<b>></b> <msg> The system is ready to start encryption.</msg>'),
style=style)
sp2.show()
sp2.ok("✔")
#enc_X = np.empty(X.shape, dtype=object)
with yaspin(text='Subscribing to the online-video stream.',
spinner='clock') as sp3:
time.sleep(5)
sp3.hide()
print(HTML(u'<b>></b> <msg> Success</msg>'), style=style)
sp3.show()
sp3.ok("✔")
print("Detecting people")
time_start = time.time()
with yaspin(
text='Encrypting the descriptor').white.bold.shark.on_blue as sp4:
for i, x in enumerate(X):
sp4.write("Got descriptor of 1x{} dimension for a person".format(
x.shape[0]))
time.sleep(1)
#enc_X[i, :] = encrypt_vec(params, encryptor, frac_encoder, x)
encrypt_vec(params, encryptor, frac_encoder, x)
dists = []
for j in range(people_descriptors.shape[0]):
dist1 = euclidean_dist(people_descriptors[j], x)
dists.append(dist1)
sp4.write(
"Distance between 'Current' person and Person #{}: {:.2f} - Person #{}: {:.2f} - Person #{}: {:.2f} - Person #{}: {:.2f}"
.format(0, dists[0], 1, dists[1], 2, dists[2], 3, dists[3]))
time.sleep(1)
dists = np.array(dists)
if (dists[dists < 0.6] is not None):
d = np.sort(dists)[0]
sp4.write(
"🔦FOUND descriptor similar to Person #{}".format(d))
time.sleep(1)
sp4.hide()
print(HTML(
u'<b>�</b> <msg>descriptor {}</msg> <sub-msg>encryption complete</sub-msg>'
.format(i)),
style=style)
sp4.show()
#sp.ok("All stream is encrypted")
sp4.ok("✔")
time_end = time.time()
print("Encryption is complete.")
print(
"ALL {} descriptors are successfully encrypted and sent to the CLOUD.".
format(X.shape[0]))
print("Time: {}".format((str)(1000 * (time_end - time_start))))
# coeff_modulus_128bit(int)
# coeff_modulus_192bit(int)
parms.set_coeff_modulus(seal.coeff_modulus_128(2048))
# The plaintext modulus can be any positive integer, even though here we take
# it to be a power of two.
parms.set_plain_modulus(1 << 8)
# 1 << 8 is bitwise operation which means 1 shifted eight times ie 2^8=256
context = SEALContext(parms)
encoder = IntegerEncoder(context.plain_modulus())
keygen = KeyGenerator(context)
public_key = keygen.public_key()
secret_key = keygen.secret_key()
encryptor = Encryptor(context, public_key)
evaluator = Evaluator(context)
decryptor = Decryptor(context, secret_key)
value=7
plain1 = encoder.encode(value1)
print("Encoded " + (str)(value) + " as polynomial " + plain1.to_string() + " (plain1)")
encrypted _data= Ciphertext()
encryptor.encrypt(plain, encrypted_data)
print("Noise budget in encrypted1: " + (str)(decryptor.invariant_noise_budget(encrypted_data)) + " bits")
# operations that can be performed --->
# result stored in encrypted1 data
evaluator.negate(encrypted1_data)
def __init__(self, context, keygen):
self.mult = Evaluator(context).multiply
self.keygen = keygen
if keygen:
self.relinear = vec_relinearize(context, keygen)
