DocumentCode
2561196
Title
Role-based collaborative information collection model for botnet detection
Author
Wang, Hailong ; Gong, Zhenghu
Author_Institution
Sch. of Comput., Nat. Univ. of Defense Technol., Changsha, China
fYear
2010
fDate
17-21 May 2010
Firstpage
473
Lastpage
480
Abstract
With the growing number of botnet attacks, the botnet detection is becoming increasingly important for the network security. To enhance the existing botnet detection systems which are short of efficient information collection functions, this paper presents a collaborative information collection model with a new 5-tuple structural mode. In the model, we introduce the static and dynamic roles to meet the requirements of information collection and collaboration respectively. Moreover, we give an efficient design for the collection agent and its communication mechanism, which are the core components in the model. Finally, a representative example is given to show that our design for the collection agent can effectively collect the information about the widespread botnet activities, which can help to improve the detection performance and accuracy for a botnet detection system.
Keywords
data acquisition; invasive software; 5-tuple structural mode; botnet detection; network security; role based collaborative information collection model; Collaboration; Collaborative work; Computer networks; Computer security; Information analysis; Information security; Intrusion detection; Local area networks; National security; Performance analysis; Botnet; Collaborative; Information Collection; Network Security; Role;
fLanguage
English
Publisher
ieee
Conference_Titel
Collaborative Technologies and Systems (CTS), 2010 International Symposium on
Conference_Location
Chicago, IL
Print_ISBN
978-1-4244-6619-1
Type
conf
DOI
10.1109/CTS.2010.5478475
Filename
5478475
Link To Document