Data leakage analysis in wireless networks using Super-vised and Unsupervised Testing

Shahzad Ashraf; Zeeshan Aslam

doi:10.48168/innosoft.s12.a108

Shahzad Ashraf National Fertilizer Corporation Institute of Engineering and Technology Multan https://orcid.org/0000-0002-7637-7870
Zeeshan Aslam Alfanar Global Development Saudi Arabia

DOI: 10.48168/innosoft.s12.a108

PURL: 42411/s12/a108

ARK: ark:/42411/s12/a108

Keywords: Supervised testing, unsupervised testing, neural network, wireless networks

Abstract

Due to an increasing number of wireless spectrums, the multiple frequencies are tangling resource management process that results hindrance in operation. In addition, the previous data become vulnerable when reports are received for data leakage enigma. In this situation, it is indispensable to secure the data in the dataset and detect the actual amount of data during resource transformation mechanism in wireless networks. A system as been developed to detect the leaked data using supervised and unsupervised testing technique by conducting simulation in Python. The targeted and actual outcome is obtained which deduced through supervised and undersized testing, the outcome remained 96.03%, and 94.53% respectively.

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