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Secure cloud computing: leveraging GNN and leader K-means for intrusion detection optimization.

Raman Dugyala1, Premkumar Chithaluru2, M Ramchander3

  • 1Department of Computer Science and Engineering, Chaitanya Bharathi Institute of Technology, Hyderabad, 500075, India.

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Summary

This study introduces an optimized Intrusion Detection System (IDS) for cloud computing, enhancing security with Graph Neural Networks and Leader K-means clustering. The new system significantly improves intrusion detection accuracy and processing efficiency.

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Area of Science:

  • Computer Science
  • Cybersecurity
  • Artificial Intelligence

Background:

  • Cloud computing's rapid growth presents significant security challenges, particularly in intrusion detection.
  • Traditional intrusion detection systems (IDS) in cloud environments often suffer from low accuracy and high processing times.
  • There is a critical need for advanced IDS solutions to address the evolving threat landscape in cloud infrastructure.

Purpose of the Study:

  • To develop an optimized Intrusion Detection System (IDS) for cloud environments.
  • To enhance the accuracy and efficiency of intrusion detection in cloud computing.
  • To provide a robust security solution for sensitive data within cloud platforms.

Main Methods:

  • Integration of Graph Neural Networks (GNNs) and Leader K-means clustering for improved data analysis and threat identification.
  • Utilization of an optimized Grasshopper Optimization algorithm to enhance the performance of an Optimal Neural Network (NN).
  • Implementation of Advanced Encryption Standard (AES) encryption and steganography for comprehensive data security.

Main Results:

  • The proposed IDS demonstrates significant improvements in both detection accuracy and processing efficiency compared to existing methods.
  • Leader K-means clustering effectively enhances the IDS's ability to distinguish between normal and malicious network activities.
  • The optimized NN, boosted by the Grasshopper Optimization algorithm, achieves superior performance in identifying complex threats.

Conclusions:

  • The developed IDS offers a comprehensive and effective solution to the security challenges in cloud computing.
  • The synergistic combination of GNNs, Leader K-means, and optimized NN provides a powerful framework for advanced intrusion detection.
  • This research contributes a valuable, efficient, and accurate security system for protecting cloud environments and sensitive data.