Dynamic Suppression Algorithm of Semi-distributed Zombie Network Based on Big Data

doi:10.3969/j.issn.1006-2475.2020.08.018

Abstract

Abstract: In order to improve the security of semi-distributed botnet, a dynamic suppression algorithm of semi-distributed botnet based on big data is proposed. The method of baud interval equalization control is used to compensate the dynamic characteristics of the semi-distributed botnet. The sampling model of the dynamic characteristics of the semi-distributed botnet is constructed. The decision equalization method is used to analyze the collected dynamic characteristics quantitatively and recursively and extract the statistical characteristics of the semi-distributed botnet. On this basis, the big data optimization calculation method is used to achieve the true optimal suppression of the semi-distributed botnet. Under the embedded environment, the optimal inhibition parameters of the semi-distributed botnet are combined with the results of load response to realize the dynamic inhibition of the semi-distributed botnet. The simulation results show that the semi-distributed botnet dynamic suppression method has a good effect, it improves the suppression precision, shortens the suppression time, and reduces the bit error rate of network output.

Key words: big data, semi-distributed, botnet, dynamic suppression

CLC Number:

TP391

LIU Zhang-rong. Dynamic Suppression Algorithm of Semi-distributed Zombie Network Based on Big Data[J]. Computer and Modernization, 2020, 0(08): 109-113.

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