|
ABSTRACT
Title |
: |
Signature Analysis of UDP Streams for Intrusion
Detection using Data Mining Algorithms |
Authors |
: |
R.Sridevi, Dr.K.Lakshmi |
Keywords |
: |
UDP, Intrusion detection, KDD Cup dataset, Random
tree, Naïve Bayes |
Issue Date |
: |
October 2010 |
Abstract |
: |
with the increased use of internet for a wide range of
activity from simple data search to online commercial
transactions, securing the network is extremely important for any
organization. Intrusion detection becomes extremely important to
secure the network. Conventional techniques for intrusion
detection have been successfully deployed, but predictive action
can help in protecting the system in the long run. Data mining
techniques are being increasingly used to study the data streams
and good results have been achieved over time.
In this paper we propose to extract unique signatures from UDP
data stream, apply existing mining techniques and compare
results. We have used the KDD cup 1999 dataset which contains a
wide variety of intrusion attacks simulated in a military
environment.
|
Page(s) |
: |
2461-2465 |
ISSN |
: |
0975–3397 |
Source |
: |
Vol. 2, Issue.7 |
|