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                <text>Conference Papers</text>
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    <name>Conference Paper</name>
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              <text>FADA: Flooding Attack Defense AODV Protocol to counter Flooding Attack in MANET</text>
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              <text>Denial of Service (DoS); FADA Protocol; Flooding attack; MANET; Throughput</text>
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              <text>The intrinsic nature of a Mobile Ad hoc Network (MANET) makes it difficult to provide security and it is more vulnerable to network attacks. Denial of Service (DoS) attack can be executed using Flooding attack, that has the potential to bring down the entire network. This attack works by delivering an excessive number of unwanted packets that consumes too much battery life, storage space, and bandwidth, that eventually lowers the system's performance. In order to flood the network, the attacker injects fake packets into it. Both Control Packet flooding and Data flooding attacks are taken into account in this study. FADA (Flooding Attack Defense AODV) protocol is proposed to counter flooding attack that promotes greater utilization of existing resources. This research identifies the attack-causing node, isolates it and protects the network against flooding attack. Attack Detection Rate, Attack Detection Accuracy, End-to-end delay and Throughput are few metrics used for evaluation of the proposed model. NS-2.35 is used to demonstrate the efficiency of the suggested protocol and the results prove that the proposed model increases system's throughput while decreasing attack. The simulation results have shown that the proposed FADA protocol performs better than the existing models taken into consideration.   2023 IEEE.</text>
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              <text>Kiruthika M.; Krishnasamy L.; Samuel P.; Kanagaraj K.</text>
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              <text>Proceedings of IEEE 2023 5th International Conference on Advances in Electronics, Computers and Communications, ICAECC 2023</text>
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              <text>Institute of Electrical and Electronics Engineers Inc.</text>
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              <text>2023-01-01</text>
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              <text>&lt;a href="https://doi.org/10.1109/ICAECC59324.2023.10560115" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1109/ICAECC59324.2023.10560115&lt;/a&gt;
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              <text>ISBN: 979-835030544-9</text>
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              <text>Online</text>
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              <text>English</text>
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              <text>Kiruthika M., School of Computing, SRM Institute of Science and Technology, Department of Computational Intelligence, Tamilnadu, Kattankulathur, India; Krishnasamy L., School of Engineering and Technology, Christ University, Department of Computer Science and Engineering, Karnataka, Bengaluru, India; Samuel P., School of Computing, SRM Institute of Science and Technology, Department of Computational Intelligence, Tamilnadu, Kattankulathur, India; Kanagaraj K., School of Computing, SRM Institute of Science and Technology, Department of Computational Intelligence, Tamilnadu, Kattankulathur, India</text>
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