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Article Details

Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

Developing a Framework for Data Communication in a Wireless Network using Machine Learning Technique

Author 1: Somya Khidir Mohmmed Ataelmanan
Author 2: Mostafa Ahmed Hassan Ali

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Digital Object Identifier (DOI) : 10.14569/IJACSA.2021.0120341

Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 12 Issue 3, 2021.

  • Abstract and Keywords
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Abstract: The emergence of Internet of Things (IoT) has become a huge innovation for utilizing the enormous power of wireless media. The adaptation of smart devices, with intelligent networking, has greatly enhanced the traffic of the IoT environment. The present security mechanism is primarily focusing on specific areas such as content filtering, monitoring techniques, and anomaly detection. A vulnerability reflects the inability of a network that allows an attacker to detect the extent of existing mechanism of security. The existing techniques focused on specific attacks rather than monitoring the whole network. However, there is a demand for a framework to govern and protect data and services in IoT network. Anomaly detection framework is a resource intensive activity to protect data and services of IoT / Wireless Sensor Networks (WSN). It supports application layer of IoT network and traces it frequently to find the existence of malicious activities. In this study, researchers proposed an anomaly detection framework to safeguard against wireless attacks. The proposed framework has employed a machine learning technique to detect the traces of wireless attacks. It supports IoT based networks to monitor the functionalities of the resources. In addition, it discusses the open challenges in IoT networks with possible solutions. Researchers employed a test bed for evaluating the proposed framework. The outcome of the study shows that the proposed framework provides better services with more security.

Keywords: Anomaly detection; internet of things; wireless attacks; artificial intelligence; machine learning

Somya Khidir Mohmmed Ataelmanan and Mostafa Ahmed Hassan Ali, “Developing a Framework for Data Communication in a Wireless Network using Machine Learning Technique” International Journal of Advanced Computer Science and Applications(IJACSA), 12(3), 2021. http://dx.doi.org/10.14569/IJACSA.2021.0120341

@article{Ataelmanan2021,
title = {Developing a Framework for Data Communication in a Wireless Network using Machine Learning Technique},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2021.0120341},
url = {http://dx.doi.org/10.14569/IJACSA.2021.0120341},
year = {2021},
publisher = {The Science and Information Organization},
volume = {12},
number = {3},
author = {Somya Khidir Mohmmed Ataelmanan and Mostafa Ahmed Hassan Ali}
}


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