SuspiciousLoginDataSim.py

# Generate Suspicious login - Login after consecutive failed logins
def generateSuspiciousLoginScenario1(df):
    global currentTime, usernames, ipAddressesForUsers, index
    username = usernames[random.randrange(NUMBER_OF_USERS)]
    contextID = uuid.uuid4()
    currentTime = currentTime + datetime.timedelta(seconds=random.randrange(3000))
    failureCount = random.randrange(4, 7)
    generateFailedLogin(df, failureCount, currentTime, username, contextID)
    index = index + failureCount
    currentTime = currentTime + datetime.timedelta(seconds=random.randrange(3))
    generateSuccessfulLogin(df, currentTime, username, contextID, isSuspicious=True)
    index = index + 1


# Generate Suspicious login 2 - Login from suspicious IP
def generateSuspiciousLoginScenario2(df):
    global currentTime, usernames, ipAddressesForUsers, index
    username = usernames[random.randrange(NUMBER_OF_USERS)]
    # contextID = uuid.uuid4()
    currentTime = currentTime + datetime.timedelta(seconds=random.randrange(3000))
    ip = generateRandomIPV4()
    geoLoc = None
    while geoLoc is None:
        while ip in geoLocationForIP:
            ip = generateRandomIPV4()
        geoLoc = geolocation.getGelocation(ip)
        if geoLoc.latitude == geoLocationForIP[ipAddressesForUsers[username]].latitude and geoLoc.longitude == \
                geoLocationForIP[ipAddressesForUsers[username]].longitude:
            geoLoc = None
            ip = generateRandomIPV4()
    geoLocationForIP[ip] = geoLoc
    generateSuccessfulLogin(df, currentTime, username)
    index = index + 1
    currentTime = currentTime + datetime.timedelta(seconds=random.randrange(60))
    generateSuccessfulLogin(df, currentTime, username, ip, isSuspicious=True)
    index = index + 1