Machine Learning Enabled Techniques for Protecting Wireless Sensor Networks by Estimating Attack Prevalence and Device Deployment Strategy for 5G Networks

<table class="figure-group"><tr class="fig-image" id="a"><td><object data="https://static-preview.hindawi.com/articles/wcmc/volume-2022/5713092/figures/5713092.fig.008a.svgz" name="5713092.fig.008a" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(a) </b>Transmission control protocol</td></tr><tr class="fig-image" id="b"><td><object data="https://static-preview.hindawi.com/articles/wcmc/volume-2022/5713092/figures/5713092.fig.008b.svgz" name="5713092.fig.008b" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(b) </b>User defined structure</td></tr></table>

<div>Network layer predefined structure.</div>

Wireless Communications and Mobile Computing

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Figure 8

Figure 8: Machine Learning Enabled Techniques for Protecting Wireless Sensor Networks by Estimating Attack Prevalence and Device Deployment Strategy for 5G Networks 

Figure 8 | Machine Learning Enabled Techniques for Protecting Wireless Sensor Networks by Estimating Attack Prevalence and Device Deployment Strategy for 5G Networks 