|
|
 |
to
content of issue |
|
Title |
DATA MINING IN THE PROBLEM
OF DETECTING BOTNETS |
|
Authors |
KOSENKO Maxim Yu.
Lecturer, Department of
Information Technology Institute of Information
Technologies Chelyabinsk State University. Bld. 129,
Br. Kashirinih Str., Chelyabinsk, 454001. E-mail:
kosenko@csu.ru |
|
Section |
COMPUTER SECURITY |
|
Issue |
19 |
Page |
22-29 |
index UDC |
65.012.810, 004.056, 004.7 |
index LBC |
|
|
Abstract |
This paper presents multi-agent system for detecting
botnets “NET.BOTNET” based on data mining. This
system contributes to the problem of detecting
botnets in a global network and is designed to
detect group behavior of bots. The proposed system
allows to detect botnets regardless
of their Protocol or organizational structure using
a clustering analysis of network traffic.
This paper describes the architecture of multi-agent
system using agent-oriented techniques for the
representation of models, object-oriented and
agent-based methodology for the design and
development of software systems. Also discusses a
method of detecting traffic of botnets based on data
mining. |
|
Keywords |
botnet, detection of botnet, multi-agent
system. |
|
 |
You can access full text version of
the article |
|
|
to
content of issue |
|
