arrow
Return

DDoS attack detection method using cluster analysis

delete2008-04-01
delete182
PRE
AI
J
Juhyun Kim
K
Ki Hoon Kwon
K
Kim, Sehun
DOI:10.1016/j.eswa.2007.01.040delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
Distributed Denial of Service (DDoS) attacks generate enormous packets by a large number of agents and can easily exhaust the computing and communication resources of a victim within a short period of time. In this paper, we propose a method for proactive detection of DDoS attack by exploiting its architecture which consists of the selection of handlers and agents, the communication and compromise, and attack. We look into the procedures of DDoS attack and then select variables based on these features. After that, we perform cluster analysis for proactive detection of the attack. We experiment with 2000 DARPA Intrusion Detection Scenario Specific Data Set in order to evaluate our method. The results show that each phase of the attack scenario is partitioned well and we can detect precursors of DDoS attack as well as the attack itself. (C) 2007 Elsevier Ltd. All rights reserved.
Keywords:
DDoS
proactive detection
security
cluster analysis
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Expert Systems with Applications cover
Expert Systems with Applications
IF:
7.5
Papers:
2.9W
Citations:
10.2W

Organization

No organization information available