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 :
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