def do_POST(self):
# Parse the form data posted
form = cgi.FieldStorage(
fp=self.rfile,
headers=self.headers,
environ={'REQUEST_METHOD': 'POST',
'CONTENT_TYPE': self.headers['Content-Type'],
})
# Begin the response
self.send_response(200)
self.end_headers()
self.wfile.write('\n')
message = threading.currentThread().getName()
self.wfile.write(message)
self.wfile.write('\n')
self.wfile.write('Client: %s\n' % str(self.client_address))
self.wfile.write('Path: %s\n' % self.path)
user = form['user'].value
if 'switch' in form:
switch = form['switch'].value
DIM.setLearningMode(user, switch)
else:
vectortype = form['datatype'].value
data = json.loads(form['json'].value)
Runner.Run(data, user, vectortype)
return
def detectNetworkAnomalies(passedData, username):
# Get the trained data set
trainedData = DatabaseInteractionClass.getNetworkLearnedData(username)
npTrainedData = np.array(trainedData)
# Generate the model, and fit the trained data to it
clf = svm.OneClassSVM(nu=0.1, kernel="rbf", gamma=0.00005)
clf.fit(npTrainedData)
# This should return an array of 1's and -1's (in float64 form), the -1's corresponding to failures
return clf.predict(passedData)
def detectProcessAnomalies(passedData, username):
# Get the trained data set
trainedData = DatabaseInteractionClass.getProcessLearnedData(username)
#scaledTrainingData = []
#scaledPassedData = []
#for point in trainedData:
# scaledTrainingData.append(AnomalyDetectionClass.scalePoint(point))
#for point in passedData:
# scaledPassedData.append(AnomalyDetectionClass.scalePoint(point))
print "in detect process anomalies"
print "training data:"
print trainedData
print "input data:"
print passedData
npTrainedData = np.array(trainedData)
#npTrainedData = np.array(scaledTrainingData)
# Generate the model, and fit the trained data to it
clf = svm.OneClassSVM(nu=0.1, kernel="rbf", gamma=0.00005)
clf.fit(npTrainedData)
# This should return an array of 1's and -1's (in float64 form), the -1's corresponding to failures
return clf.predict(passedData)
def getLatLong(ipAddress):
latitude, longitude = DatabaseInteractionClass.getLatLongFromIP(ipAddress)
return latitude, longitude
from DatabaseInteractionModule import DatabaseInteractionClass as DIM
print DIM.getScore("zlbales")
print DIM.getScore("cbcullen")
print DIM.getPointsProcessed("zlbales")
print DIM.getPointsProcessed("cbcullen")
print DIM.isLearningMode("zlbales")
print DIM.isLearningMode("cbcullen")
#integer version of Zach's IP (129.186.251.4) at time of writing test
print DIM.getLatLongFromIP(2176514820)
#integer version of Google's IP address for DNS server (8.8.8.8)
print DIM.getLatLongFromIP((8 * 256 * 256 * 256) + (8 * 256 * 256) + (8 * 256) + 8)
print DIM.setScore("zlbales", 99, 10)
print DIM.setScore("zlbales", 98, 20)
print DIM.setScore("zlbales", 97, 30)
print DIM.setScore("zlbales", 100, 0)
print DIM.getProcessLearnedData("zlbales")
print DIM.getProcessLearnedData("cbcullen")
print DIM.getProcessLearnedData("unknown")
print DIM.getFileLearnedData("zlbales")
print DIM.getFileLearnedData("cbcullen")
print DIM.getFileLearnedData("unknown")
print DIM.getNetworkLearnedData("zlbales")