Volume 18, No. 6, 2021

Performance Estimating And Optimizing Neural Network For Botnet Detection In Machine Learning

Dr. Nitya Nand Dwivedi , Dr. Shashiraj Teotia , Mr. Ankur Chaudhary


These days, botnets are being considered as the most vital security dangers in the web and it is vital to discover new routes for their recognition. Shared (P2P) botnets are the most imperative sorts of botnets that utilization P2P correspondence conventions to control their bots remotely. Along these lines, their recognition is more troublesome than different botnets. In this paper, we propose another way to deal with distinguish P2P botnets in the direction and control (C&C) period of life cycle dependent on the examination of activity conduct. The proposed methodology can distinguish C&C activity of P2P botnets by utilizing stream based highlights and order techniques. The execution of the proposed approach is assessed dependent on various parameters. The aftereffects of the assessment demonstrate that the proposed approach can recognize P2P botnet from ordinary system activity with high identification rate.

Pages: 3568-3584

Keywords: Botnet Detection, Machine Learning, Orange Data Mining Tool, Networks

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