Cloud Based DDOS Attack Detection Using Machine Learning Architectures: Understanding the Potential for Scientific Applications

Authors

  • Manjunath C R Associate Professor, Department of Compute Science and Engineering, Jain(Deemed-to-be University), Bangalore, India
  • Ketan Rathor GyanSys Inc Carmel
  • Nandini Kulkarni Symbiosis School of Planning Architecture and Design, Symbiosis International Deemed University. Symbiosis School of Planning Architecture and Design, Nagpur
  • Prashant Pandurang Patil Associate Professor, Bharati Vidyapeeth (Deemed to be University), Y. M. Institute of Management Karad.
  • Manoj S. Patil Research Consultant, Research and Development, Jawaharlal Nehru Medical College, Datta Meghe Institute of Medical Sciences, Wardha, Maharashtra, India.
  • Jasdeep Singh Assistant Professor, Department of CSE, RIMT University, Mandi, Gobind garh, Punjab, India.

Keywords:

cloud computing, DDoS attack, machine learning, dimensionality reduction, data delivery ratio

Abstract

Cloud computing technology has become a crucial component of IT services utilized in daily living in this era of technology. Website hosting services are gradually migrating to cloud in this regard. This increases the value of cloud-based websites while also creating new risks for those services. A severe threat of this nature is DDoS attack. This research propose novel technique in cloud based DDOS attacks using machine learning architectures. here the input has been collected based on cloud module and it has been processed for dimensionality reduction and noise removal. Then this data feature has been extracted and classified using ResNet-101 based KELM. The experimental analysis has been carried out in terms of data delivery ratio, transmission rate, validation accuracy, training accuracy, end-end delay. the proposed technique attained data delivery ratio of 92%, transaction rate of 82%, validation accuracy of 89%, training accuracy of 96%, end-end delay of 56%

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References

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Overall proposed architecture

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Published

19.12.2022

How to Cite

Manjunath C R, Ketan Rathor, Nandini Kulkarni, Prashant Pandurang Patil, Manoj S. Patil, & Jasdeep Singh. (2022). Cloud Based DDOS Attack Detection Using Machine Learning Architectures: Understanding the Potential for Scientific Applications. International Journal of Intelligent Systems and Applications in Engineering, 10(2s), 268 –. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/2398

Issue

Vol. 10 No. 2s (2022)

Section

Research Article

License

Copyright (c) 2022 Manjunath C R , Ketan Rathor , Nandini Kulkarni, Prashant Pandurang Patil, Manoj S. Patil , Jasdeep Singh

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