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adaptive butterfly optimization algorithm(ABOA)Based Feature Selection and Deep Neural Network(DNN)for Detection of Distributed Denial-of-Service(DDoS)Attacks in Cloud

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Computer Systems Science & Engineering 2023年第10期47卷 1109-1123页

作者： S.Sureshkumar G.K.D.Prasanna Venkatesan R.Santhosh Department of Computer Science and Engineering Karpagam Academy of Higher EducationCoimbatore641021India Dean Engineering Faculty EngineeringKarpagam Academy of Higher EducationCoimbatore641021India Department of Computer Science and Engineering Faculty of EngineeringKarpagam Academy of Higher EducationCoimbatore641021India

Cloud computing technology provides flexible,on-demand,and completely controlled computing resources and services are highly *** this,with its distributed and dynamic nature and shortcomings in virtualization deployment,the cloud environment is exposed to a wide variety of cyber-attacks and security *** Intrusion Detection System(IDS)is a specialized security tool that network professionals use for the safety and security of the networks against attacks launched from various *** attacks are becoming more frequent and powerful,and their attack pathways are continually changing,which requiring the development of new detection *** the purpose of the study is to improve detection *** Selection(FS)is *** the same time,the IDS’s computational problem is limited by focusing on the most relevant elements,and its performance and accuracy *** this research work,the suggested adaptive butterfly optimization algorithm(ABOA)framework is used to assess the effectiveness of a reduced feature subset during the feature selection phase,that was motivated by this motive *** classification is not compromised by using an ABOA *** design of Deep Neural Networks(DNN)has simplified the categorization of network traffic into normal and DDoS threat ***’s parameters can be finetuned to detect DDoS attacks better using specially built *** reconstruction error,no exploding or vanishing gradients,and reduced network are all benefits of the changes outlined in this *** it comes to performance criteria like accuracy,precision,recall,and F1-Score are the performance measures that show the suggested architecture outperforms the other existing *** the proposed ABOA+DNN is an excellent method for obtaining accurate predictions,with an improved accuracy rate of 99.05%compared to other existing approaches.

关键词： Cloud computing distributed denial of service intrusion detection system adaptive butterfly optimization algorithm deep neural network

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