Advertisement

Research of Botnet Situation Awareness Based on Big Data

  • Zhiqiang Luo
  • Jun Shen
  • Huamin Jin
  • Dongxin Liu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9461)

Abstract

With the rapid expansion of the botnet, a single network security system could not meet the requirement. Botnet situation awareness can dynamically reflect the overall botnet security and predict botnet security development trends. Characteristics of big data create opportunity for research breakthrough of large scale botnet situation awareness. This article discusses about botnet security situation awareness based on multi-source logs by utilizing big data analysis. It promotes detection accuracy and fast response of botnet events, and implements the early warning for DDoS attacks.

Keywords

Botnet Big data Situation awareness Network security 

Reference

  1. 1.
    Luo, Zhiqiang, Jun, Shen: Research and application of mobile e-commerce user provenance authentication technology. Telecommun. Sci. 6, 7–12 (2009)Google Scholar
  2. 2.
    Jian, C., Fan, M.: Signatures extraction method based on classification of malicious software. J. Comput. Appl. 31(1), 83–84 (2011)Google Scholar
  3. 3.
    Wang, Xinliang: Analysis and Detection of Botnet Anomaly Traffic[D]. Beijing University of Posts and Telecommunications, Beijing (2011)Google Scholar
  4. 4.
    Yu, Xiaocong, Dong, Xiaomei, Ge, Y., et al.: Online botnet detection techniques. Geomatics Inf. Sci. Wuhan Univ. 35(15), 578–581 (2010)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Zhiqiang Luo
    • 1
  • Jun Shen
    • 1
  • Huamin Jin
    • 1
  • Dongxin Liu
    • 1
  1. 1.Guangzhou Research Institute of China Telecom Co. Ltd.GuangzhouPeople’s Republic of China

Personalised recommendations