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논문검색

Botnet Detection Based on Correlation of Malicious Behaviors

초록

영어

Botnet has become the most serious security threats on the current Internet infrastructure. Botnet is a group of compromised computers (Bots) which are remotely controlled by its originator (BotMaster) under a common Command and Control (C&C) infrastructure. Botnets can not only be implemented by using existing well known bot tools, but can also be constructed from scratch and developed in own way, which makes the botnet detection a challenging problem. Because the P2P (peer to peer) botnet is a distributed malicious software network, it is more difficult to detect this bot. In this paper, we proposed a new general Botnet detection correlation algorithm, which is based on the correlation of host behaviors and classification method for network behaviors. The experimental results show the proposed approach not only can successfully detect known botnet with a high detection rate but it can also detect some unknown malware.

목차

Abstract
 1. Introduction
 2. System Vulnerability
 3. Bot Propagation
 4. Related Work
 5. Host-based Detection
 6. Experiment for Host-based Detection
 7. Network-based Detection
 Acknowledgements
 References

저자정보

  • Chunyong Yin School of Computer & Software, Nanjing University of Information Science & Technology, Jiangsu Key Laboratory of Meteorological Observation and Information Processing, Nanjing University of Information Science & Technology, Nanjing 210044, China
  • Mian Zou School of Computer & Software, Nanjing University of Information Science & Technology, Nanjing 210044, China
  • Darius Iko School of Computer & Software, Nanjing University of Information Science & Technology, Nanjing 210044, China
  • Jin Wang School of Computer & Software, Nanjing University of Information Science & Technology, Nanjing 210044, China

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