def enroll():
db = DBConnection()
success, dbId = db.addUserCredentials()
if success != True:
return False, None
dbUsername, dbPassword = db.getUserCredentials(dbId)
print('Starting the Enrollment process')
counter = 0
while counter < 2:
print('Sample => {}'.format(counter + 1))
username = input('Enter username:\n').strip()
if username != dbUsername:
print('Removed the sample as username did not match')
continue
print('Enter password:')
user = linuxGetTimelog.User(dbId, dbUsername, dbPassword)
success, date = user.startLogging()
if success == True:
extractFeatures(dbId, date)
addToCSV(dbId, date)
counter += 1
sys.stdout.flush();
tcflush(sys.stdin, TCIOFLUSH)
db.closeConnection()
global userId
userId = dbId
print("Enrollment Process over")
return True, userId
def testModel(userId):
print('Let us test the created model')
db = DBConnection()
dbUsername, dbPassword = db.getUserCredentials(userId)
username = input('Enter username:\n').strip()
if username != dbUsername:
print('Removed the sample as username did not match')
return
print('Enter password:'******'data/user_input/{}/userData.csv'.format(userId),
header=0).tail(1)
X = userData[[
'release_codes', 'pp', 'pr', 'rp', 'rr', 'ppavg', 'pravg', 'rpavg',
'rravg', 'total'
]]
X = get_hashed_matrix(X)
names = [
"Isolation Forest Ensemble",
]
classifiers = [
IsolationForest(random_state=np.random.RandomState(42)),
]
for name, clf in zip(names, classifiers):
# print("\nLoading classifier : {}".format(name))
clf = joblib.load('data/user_input/{}/userModel-{}.pkl'.format(
userId, name))
result = clf.predict(X)
if result[0] == 1:
print('Welcome')
else:
print('Stay away impostor!')
# testModel(114)
