• DocumentCode
    189092
  • Title

    Based Sliding Window Cloud Computing Platform of Network Intrusion Detection Algorithm

  • Author

    He Xue Ni

  • Author_Institution
    Inf. Eng. Dept., Lanzhou Vocational Tech. Coll., Lanzhou, China
  • fYear
    2014
  • fDate
    11-13 Sept. 2014
  • Firstpage
    927
  • Lastpage
    930
  • Abstract
    In view of the existing cloud computing platform for network intrusion data set, serious problems, the network intrusion detection and prevention into cloud computing platform. With regard to various threats to carry out a full range of real-time active monitoring, detection and defense, the detection algorithm - CCPSWNIDA algorithm for intrusion platform network computing cloud based on sliding window. The advantage of CCPSWNIDA by using sliding window, with a size of K window, the binary exponential d from left to right (also from right to left) sliding, gets a valid set, the request message and the response message proportional law, and to monitor the abnormal situation, once found the percentage change beyond the normal range so, is that abnormal, alarm, to achieve the purpose of intrusion detection, results show that, the algorithm is advanced, a certain validity, can detect network intrusion defense solution.
  • Keywords
    cloud computing; computer network security; CCPSWNIDA algorithm; based sliding window cloud computing platform; binary exponential; intrusion platform network computing cloud based on sliding window; network intrusion data set; network intrusion defense solution; network intrusion detection algorithm; network intrusion detection and prevention; response message proportional law; Algorithm design and analysis; Cloud computing; Computer crime; Computers; Intrusion detection; Servers; Silicon; Cloud computing platform; DDoS detection algorithm; sliding window;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer and Information Technology (CIT), 2014 IEEE International Conference on
  • Conference_Location
    Xi´an
  • Type

    conf

  • DOI
    10.1109/CIT.2014.172
  • Filename
    6984781