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Data Detection in Wireless Sensor Network Based on Convex Hull and Naïve Bayes Algorithm

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Role of Data-Intensive Distributed Computing Systems in Designing Data Solutions

Part of the book series: EAI/Springer Innovations in Communication and Computing ((EAISICC))

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Abstract

Wireless sensor networks (WSNs) have been affected by data due to their placement in random and risky atmospheres. Sensitive data in computer systems are increasing drastically and, thus, there is an utmost need to provide efficient cybersecurity. While detecting security bugs, software engineers discuss these bugs privately and they are not made public until security patches are available. This leads to many failures such as communication failure and hardware or software failure. This work aims to assist software developers in classifying bug reports in a better way by identifying security vulnerabilities as security bugs reports (SBRs) through the tuning of learners and data preprocessors. Practically, machine learning (ML) techniques are used to detect intrusions based on data and to learn by what means secure and nonsecure bugs can be differentiated. This work proposes a rudimentary classification model for bug prediction by involving Adaptive Ensemble Learning with Hyper Optimization (AEL-HO) technique. Classifier performance is analyzed based on the F1-score, detection accuracy (DA), Matthew’s correlation coefficients (MCC), and true positive rate (TPR) parameters. Comparisons are made among different already-existing classifiers.

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Author information

Authors and Affiliations

  1. Santiago Antúnez de Mayolo National University, Huaraz, Peru

    Edwin Hernan Ramirez-Asis & Miguel Angel Silva Zapata

  2. Information Technology, Malla Reddy Engineering College for Women, Secunderabad, India

    A. R. Sivakumaran

  3. School of Agricultural and Food Engineering, Faculty of Food and Agricultural Technology, Pibulsongkram Rajabhat University, Phitsanulok, Thailand

    Khongdet Phasinam

  4. Department of Electronics & Communication Engineering, GLA University, Mathura, UttarPradesh, India

    Abhay Chaturvedi

  5. Department of Information Technology, Adhiyamaan College of Engineering, Hosur, TamilNadu, India

    R. Regin

Authors
  1. Edwin Hernan Ramirez-Asis
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  2. Miguel Angel Silva Zapata
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  3. A. R. Sivakumaran
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  4. Khongdet Phasinam
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  5. Abhay Chaturvedi
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  6. R. Regin
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Editor information

Editors and Affiliations

  1. Computer Science, Banaras Hindu University, Varanasi, India

    Sarvesh Pandey

  2. Madan Mohan Malaviya University of Technology, Gorakhpur, Uttar Pradesh, India

    Udai Shanker

  3. University of South Dakota, South Dakota, SD, USA

    Vijayalakshmi Saravanan

  4. Deutsches Elektronen-Synchrotron DESY, Hamburg, Germany

    Ra**ikumar Ramalingam

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Ramirez-Asis, E.H., Zapata, M.A.S., Sivakumaran, A.R., Phasinam, K., Chaturvedi, A., Regin, R. (2023). Data Detection in Wireless Sensor Network Based on Convex Hull and Naïve Bayes Algorithm. In: Pandey, S., Shanker, U., Saravanan, V., Ramalingam, R. (eds) Role of Data-Intensive Distributed Computing Systems in Designing Data Solutions. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-031-15542-0_3

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  • DOI: https://doi.org/10.1007/978-3-031-15542-0_3

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  • Online ISBN: 978-3-031-15542-0

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