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    ARTICLE

    A Novel DDoS Attack Detection Method Using Optimized Generalized Multiple Kernel Learning

    Jieren Cheng1, 2, Junqi Li2, *, Xiangyan Tang2, Victor S. Sheng3, Chen Zhang2, Mengyang Li2

    CMC-Computers, Materials & Continua, Vol.62, No.3, pp. 1423-1443, 2020, DOI:10.32604/cmc.2020.06176

    Abstract Distributed Denial of Service (DDoS) attack has become one of the most destructive network attacks which can pose a mortal threat to Internet security. Existing detection methods cannot effectively detect early attacks. In this paper, we propose a detection method of DDoS attacks based on generalized multiple kernel learning (GMKL) combining with the constructed parameter R. The super-fusion feature value (SFV) and comprehensive degree of feature (CDF) are defined to describe the characteristic of attack flow and normal flow. A method for calculating R based on SFV and CDF is proposed to select the combination More >

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