def test_fingerprinted_data_type(self):
scheme = AKScheme(gamma=2)
secret_key = 123
recipient = 0
data = BreastCancerWisconsin()
fingerprinted = scheme.insertion(data, recipient, secret_key)
self.assertIsInstance(fingerprinted, Dataset)
def test_base_fingerprint_creation(self):
scheme = AKScheme(gamma=2)
secret_key = 123
recipient = 0
fingerprint = scheme.create_fingerprint(recipient_id=recipient,
secret_key=secret_key)
self.assertIsNotNone(fingerprint)
def test_no_target_datapath(self):
scheme = AKScheme(gamma=1)
secret_key = 123
recipient = 0
data = '../../datasets/breast_cancer_wisconsin.csv'
fingerprinted_data = scheme.insertion(data, recipient, secret_key)
suspect = scheme.detection(fingerprinted_data, secret_key)
self.assertEqual(recipient, suspect)
def test_detection_all_numerical(self):
scheme = AKScheme(gamma=2)
secret_key = 123
recipient = 0
data = BreastCancerWisconsin()
fingerprinted_data = scheme.insertion(data, recipient, secret_key)
suspect = scheme.detection(fingerprinted_data, secret_key)
self.assertEqual(recipient, suspect)
def test_insertion_all_numerical(self):
scheme = AKScheme(gamma=2)
secret_key = 123
recipient = 0
data = BreastCancerWisconsin()
fingerprinted = scheme.insertion(data, recipient, secret_key)
self.assertListEqual(data.dataframe.columns.tolist(),
fingerprinted.dataframe.columns.tolist())
def test_base_no_suspect(self):
scheme = AKScheme(gamma=2)
secret_key = 123
recipient = 0
fingerprint = scheme.create_fingerprint(recipient_id=recipient,
secret_key=secret_key)
suspect = scheme.detect_potential_traitor(fingerprint=fingerprint,
secret_key=secret_key + 1)
self.assertEqual(suspect, -1)
def test_exclude_datapath(self):
scheme = AKScheme(gamma=1)
secret_key = 123
recipient = 0
data = '../../datasets/breast_cancer_wisconsin.csv'
dataframe = pd.read_csv(data)
fingerprinted_data = scheme.insertion(data,
recipient,
secret_key,
exclude=['clump-thickness'])
# suspect = scheme.detection(fingerprinted_data, secret_key, exclude=['clump-thickness'])
self.assertTrue(fingerprinted_data.dataframe['clump-thickness'].equals(
dataframe['clump-thickness']))
def test_include_fail(self):
scheme = AKScheme(gamma=1)
secret_key = 123
recipient = 0
data = '../../datasets/breast_cancer_wisconsin.csv'
dataframe = pd.read_csv(data)
include = ['clump-thickness', 'mitoses']
fingerprinted_data = scheme.insertion(dataset=dataframe,
recipient_id=recipient,
secret_key=secret_key,
include=include)
suspect = scheme.detection(fingerprinted_data, secret_key)
self.assertNotEqual(recipient, suspect)
def test_include(self):
scheme = AKScheme(gamma=1)
secret_key = 123
recipient = 0
data = '../../datasets/breast_cancer_wisconsin.csv'
dataframe = pd.read_csv(data)
fingerprinted_data = scheme.insertion(dataset=dataframe,
recipient_id=recipient,
secret_key=secret_key,
include=['clump-thickness'])
suspect = scheme.detection(fingerprinted_data,
secret_key,
include=['clump-thickness'])
self.assertTrue(
fingerprinted_data.dataframe['uniformity-of-cell-size'].equals(
dataframe['uniformity-of-cell-size']))
def test_exclude_multi_3(self):
scheme = AKScheme(gamma=1)
secret_key = 123
recipient = 0
data = '../../datasets/breast_cancer_wisconsin.csv'
dataframe = pd.read_csv(data)
exclude = [
'clump-thickness', 'uniformity-of-cell-shape', 'marginal-adhesion',
'single-epithelial-cell-size', 'bare-nuclei', 'bland-chromatin',
'sample-code-number', 'normal-nucleoli'
]
fingerprinted_data = scheme.insertion(dataframe,
recipient,
secret_key,
exclude=exclude)
# suspect = scheme.detection(fingerprinted_data, secret_key, exclude=exclude)
self.assertFalse(dataframe['mitoses'].equals(
fingerprinted_data.dataframe['mitoses']))