FAPRP: A Machine Learning Approach to Flooding Attacks Prevention Routing Protocol in Mobile Ad Hoc Networks

<table class="figure-group"><tr class="fig-image" id="a"><td><object data="https://static-preview.hindawi.com/articles/wcmc/volume-2019/6869307/figures/6869307.fig.0013a.svgz" name="6869307.fig.0013a" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(a) </b>Packet delivery ratio</td></tr><tr class="fig-image" id="b"><td><object data="https://static-preview.hindawi.com/articles/wcmc/volume-2019/6869307/figures/6869307.fig.0013b.svgz" name="6869307.fig.0013b" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(b) </b>End-to-end delay</td></tr><tr class="fig-image" id="c"><td><object data="https://static-preview.hindawi.com/articles/wcmc/volume-2019/6869307/figures/6869307.fig.0013c.svgz" name="6869307.fig.0013c" type="image/svg+xml"></object></td></tr><tr class="fig-caption"><td><b>(c) </b>Routing load</td></tr></table>

<div>AODV, B-AODV, and FAPRP performances under RREQ flooding attacks.</div>

Wireless Communications and Mobile Computing

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Figure 13

Figure 13: FAPRP: A Machine Learning Approach to Flooding Attacks Prevention Routing Protocol in Mobile Ad Hoc Networks 