Fuzzy Integrated Latent Dirichlet Allocation Algorithm for Intrusion Detection in Cloud Environments

Authors

  • Vinayak Kishan Nirmale Lecturer in Mathematics, Department of Polytechnic, MIT World Peace University, Paud Road, Kothrud, Pune, Maharashtra, India, Pincode: 411038
  • C. Madhusudhana Rao Professor and Head, Department of CSE, Institute of Aeronautical Engineering, Hyderabad. Telangana, India, Pincode: 500043
  • Mylapalli Ramesh Assistant Professor, Department of CSE, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur Dist., Andhra Pradesh, India, Pincode: 522302
  • M. Nirmala Professor, Department of Mathematics, Sathyabama Institute of Science and Technology, Chennai, Tamilnadu, India, Pincode: 600119
  • S. Girinath Assistant Professor, Department of Computer Applications, Mohan Babu University, A. Rangampeta, Tirupati, Andhra Pradesh, India, Pincode: 517 102
  • Nellore Manoj Kumar Department of Mathematics, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences (SIMATS), Thandalam, Chennai, Tamilnadu, India

Keywords:

Intrusion, Cloud, Fuzzy, Latent Dirichlet, NIDS, DoS, R2L, FI-LDA

Abstract

This research presents an in-depth exploration of the FI-LDA model, showcasing its efficacy in anticipating and preventing intrusions, thereby bolstering security measures within cloud environments. The study introduces a novel approach to intrusion prevention, fostering a robust predictive model that significantly enhances the system's capability to discern evolving attack patterns. Leveraging fuzzy modeling, the research demonstrates the utilization of vast amounts of unlabeled data, resulting in heightened accuracy and reliability of the system. The evaluation of diverse elements crucial for cybersecurity underscores the comprehensive approach adopted to achieve the research objectives. While the FI-LDA model exhibited a favorable trade-off, addressing a pervasive flaw, there remains a call for further refinement to detect assault patterns more effectively. The research concludes by highlighting the commendable effectiveness of the FI-LDA model in identifying and detecting malicious activities within the cloud environment, affirming its strong overall performance and contribution to advancing intrusion detection systems.

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Published

23.02.2024

How to Cite

Nirmale, V. K. ., Rao, C. M. ., Ramesh, M. ., Nirmala, M. ., Girinath, S. ., & Kumar, N. M. . (2024). Fuzzy Integrated Latent Dirichlet Allocation Algorithm for Intrusion Detection in Cloud Environments. International Journal of Intelligent Systems and Applications in Engineering, 12(17s), 249–259. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/4870

Issue

Vol. 12 No. 17s (2024)

Section

Research Article

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