Jieren Cheng1, 2, Yifu Liu1, *, Xiangyan Tang1, Victor S. Sheng3, Mengyang Li1, Junqi Li1
CMC-Computers, Materials & Continua, Vol.62, No.3, pp. 1317-1333, 2020, DOI:10.32604/cmc.2020.06177
Abstract Distributed Denial-of-Service (DDoS) has caused great damage to the network
in the big data environment. Existing methods are characterized by low computational
efficiency, high false alarm rate and high false alarm rate. In this paper, we propose a
DDoS attack detection method based on network flow grayscale matrix feature via multiscale convolutional neural network (CNN). According to the different characteristics of
the attack flow and the normal flow in the IP protocol, the seven-tuple is defined to
describe the network flow characteristics and converted into a grayscale feature by binary.
Based on the network flow More >
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