Earticle

초록

영어

Presently P2P-controlled bots has become an increasing threat to our network security due to the fact that P2P bots do not have a centralized point to shutdown or trace back, thus making the detection of P2P bots is very difficult. To enhance the detection rate, a new model to detect P2P bots on an individual host is proposed by improving the dendritic cells algorithm (IDCA). In the proposed approach, the raw data for P2P bot detection is obtained via APITrace tool. The processes ID are mapped into the antigens, and the behavioral data created by the processes are mapped into the signals, which are the time series input data of IDCA, are used to implement data fusion and correlation. The test experimental results show that the proposed method is effective to detect P2P-controlled bots on the host with low false positives.

목차

Abstract
 1. Introduction
 2. Dendritic Cell Algorithm (DCA)
 3. Improved DCA for Detection of P2P Bots
  3.1 Data Collection
  3.2 Signal and Antigen Mapping
  3.3 Data Fusion
  3.4 Correlation and Analysis
 4. Experiments and Analysis
  4.1 Experimental Setup
  4.2 Experimental Results
 5. Conclusions
 References

키워드

저자

• Shoubao Su [ School of Computer, Jinling Institute of Technology, Nanjing 211169, China ]
• Yu Su [ School of Software, Nanjing University, Nanjing 210093, China ]
• Mingjuan Xu [ School of Information Engineering, West Anhui University, Lu’an 237012, China ] Corresponding author
• Xianjin Fang [ School of Computer Science & Engineering, Anhui University of Science and Technology, Huainan 232001, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Grid and Distributed Computing

• 간기

  격월간

• pISSN

  2005-4262

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605