A deep learning approach to predict the number of k-barriers

MATLAB code for "A deep learning approach to predict the number of k-barriers for intrusion detection over a circular region using WSNs."
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Updated 26 Aug 2022
This file contains the MATLAB code for "A deep learning approach to predict the number of k-barriers for intrusion detection over a circular region using WSNs, 2022, Expert Systems with Applications."
For more information please refer to the following link;
If you need a full-text of this manuscript then please email to me (abhilash.iiserb@gmail.com) or you can request it through ResearchGate.
If you are using this code then please cite the following paper;
Singh, A., Amutha, J., Nagar, J., & Sharma, S. (2022). A deep learning approach to predict the number of k-barriers for intrusion detection over a circular region using wireless sensor networks. Expert Systems with Applications, 118588.
Additional references for further reading;
  1. Singh, A., Nagar, J., Sharma, S., & Kotiyal, V. (2021). A Gaussian process regression approach to predict the k-barrier coverage probability for intrusion detection in wireless sensor networks. Expert Systems with Applications, 172, 114603. https://doi.org/10.1016/j.eswa.2021.114603
  2. Singh, A., Amutha, J., Nagar, J., Sharma, S., & Lee, C. C. (2022). Lt-fs-id: Log-transformed feature learning and feature-scaling-based machine learning algorithms to predict the k-barriers for intrusion detection using wireless sensor network. Sensors, 22(3), 1070. https://doi.org/10.3390/s22031070
  3. Singh, A., Amutha, J., Nagar, J., Sharma, S., & Lee, C. C. (2022). AutoML-ID: automated machine learning model for intrusion detection using wireless sensor network. Scientific Reports, 12(1), 1-14. https://www.nature.com/articles/s41598-022-13061-z

Cite As

ABHILASH SINGH (2024). A deep learning approach to predict the number of k-barriers (https://github.com/abhilash12iec002/intrusion_detection/releases/tag/v1.0.2), GitHub. Retrieved .

Singh, A., Amutha, J., Nagar, J., & Sharma, S. (2022). A deep learning approach to predict the number of k-barriers for intrusion detection over a circular region using wireless sensor networks. Expert Systems with Applications, 118588.

MATLAB Release Compatibility
Created with R2022a
Compatible with any release
Platform Compatibility
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Version Published Release Notes
1.0.2

See release notes for this release on GitHub: https://github.com/abhilash12iec002/intrusion_detection/releases/tag/v1.0.2

1.0.0

To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.