• DocumentCode
    2933006
  • Title

    BotCloud: Detecting botnets using MapReduce

  • Author

    Francois, Jerome ; Wang, Shaonan ; Bronzi, Walter ; State, Radu ; Engel, Thomas

  • Author_Institution
    Interdiscipl. Center for Security, Univ. of Luxembourg, Luxembourg City, Luxembourg
  • fYear
    2011
  • fDate
    Nov. 29 2011-Dec. 2 2011
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    Botnets are a major threat of the current Internet. Understanding the novel generation of botnets relying on peer-to-peer networks is crucial for mitigating this threat. Nowadays, botnet traffic is mixed with a huge volume of benign traffic due to almost ubiquitous high speed networks. Such networks can be monitored using IP flow records but their forensic analysis form the major computational bottleneck. We propose in this paper a distributed computing framework that leverages a host dependency model and an adapted PageRank [1] algorithm. We report experimental results from an open-source based Hadoop cluster [2] and highlight the performance benefits when using real network traces from an Internet operator.
  • Keywords
    IP networks; Internet; computer network security; distributed processing; peer-to-peer computing; telecommunication traffic; BotCloud; IP flow record; Internet; MapReduce; adapted PageRank algorithm; botnet traffic; botnets detection; distributed computing; forensic analysis; host dependency model; open-source based Hadoop cluster; peer-to-peer network; ubiquitous high speed network; Cloud computing; Clustering algorithms; Forensics; IP networks; Peer to peer computing; Topology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Forensics and Security (WIFS), 2011 IEEE International Workshop on
  • Conference_Location
    Iguacu Falls
  • Print_ISBN
    978-1-4577-1017-9
  • Electronic_ISBN
    978-1-4577-1018-6
  • Type

    conf

  • DOI
    10.1109/WIFS.2011.6123125
  • Filename
    6123125