• DocumentCode
    642911
  • Title

    Botnet detection technique for corporate area network

  • Author

    Savenko, Oleg ; Lysenko, Sergii ; Kryshchuk, Andrii ; Klots, Yuriy

  • Author_Institution
    Dept. of Syst. Program., Khmelnitsky Nat. Univ., Khmelnitsky, Ukraine
  • Volume
    01
  • fYear
    2013
  • fDate
    12-14 Sept. 2013
  • Firstpage
    363
  • Lastpage
    368
  • Abstract
    A new approach for the botnet detection based on multi-agent system is proposed. For increasing of the efficiency of botnet detection the multi-agent system was involved that allowed to make botnet detection via agents´ communication within corporate network. A new technique with the usage of fuzzy and neural-fuzzy systems that makes the conclusion about botnet presence degree in computer systems is developed. The analysis of the botnets´ actions demonstrations in the situation of the intentionally computer system reconnection is performed. It takes into account the botnet demonstrations in the several computer systems which are available in the network.
  • Keywords
    computer network security; computer viruses; fuzzy neural nets; intranets; multi-agent systems; Trojans; agents communication; botnet detection; botnet presence degree; botnets actions demonstrations; computer system reconnection; corporate area network; multiagent system; neural-fuzzy systems; worm viruses; Computational modeling; Computers; Fuzzy logic; Malware; Monitoring; Multi-agent systems; Software; Trojan; adaptive neuro-fuzzy inference system; agent; antivirus detection; botnet; fuzzy logic; multi-agent system; sensor; worm-virus;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Data Acquisition and Advanced Computing Systems (IDAACS), 2013 IEEE 7th International Conference on
  • Conference_Location
    Berlin
  • Print_ISBN
    978-1-4799-1426-5
  • Type

    conf

  • DOI
    10.1109/IDAACS.2013.6662707
  • Filename
    6662707