DocumentCode :
188210
Title :
A Collaborative Traceback against P2P Botnet Using Information Sharing and Correlation Analysis
Author :
Xiaolei Wang ; Jie He ; Yuexiang Yang
Author_Institution :
Coll. of Comput., Nat. Univ. of Defense Technol., Changsha, China
fYear :
2014
fDate :
13-15 Oct. 2014
Firstpage :
132
Lastpage :
138
Abstract :
Botnets are a serious threat to Internet-based services and end users. The recent paradigms shift from centralized to more sophisticated Peer-to-Peer (P2P) botnets introduces new challenges for security researchers. Centralized botnets are easy to be taken down by computer security researchers and law enforcement. Thus, botnet operators have sought new ways to harden the infrastructures of their botnets and some botnets operators have (re) designed their botnets to use P2P infrastructures because of the excellent properties of P2P technology. Many P2P botnets are far more resilient to current takedown attempts than centralized botnets due to the lack of single points of failure and stealthy Command and Control (C&C) servers. In order to combat and eradicate a P2P botnet better, we have to track a P2P botnet and find its main C&C servers. However, research on tracking for C&C servers in current P2P botnets is still lacking to the best of our knowledge, which is urgently required. In this paper, an overview of current P2P botnets is firstly presented, including architecture characteristics and traffic models. Based on the architecture characteristics of P2P botnets and traffic models, a collaborative trace back framework is proposed to find the main C&C servers in P2P botnets.
Keywords :
groupware; invasive software; peer-to-peer computing; Internet-based services; P2P botnet; P2P infrastructure; P2P technology; botnet operators; collaborative traceback framework; command and control servers; correlation analysis; information sharing; peer-to-peer botnet; Distributed computing; Knowledge discovery; C&Cservers; P2P botnet; architecture characteristics; collaborative framework; traceback; traffic model;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC), 2014 International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4799-6235-8
Type :
conf
DOI :
10.1109/CyberC.2014.31
Filename :
6984294
Link To Document :
بازگشت