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    <name>Conference Paper</name>
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          <name>Title</name>
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              <text>Multi-Layer Ensemble Deep Reinforcement Learning based DDoS Attack Detection and Mitigation in Cloud-SDN Environment</text>
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              <text>Cloud environment; DDoS attacks; Deep learning; Reinforcement learning; Software defined network</text>
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              <text>Cloud computing (CC) remains as a promising environment which offers scalable and cost effectual computing facilities. The combination of the SDN technique with the CC platform simplifies the complexities of cloud networking and considerably enhances the scalability, manageability, programmability, and dynamism of the cloud. This study introduces a novel Multi-Layer Ensemble Deep Reinforcement Learning based DDoS Attack Detection and Mitigation (MEDR-DDoSAD) technique in Cloud-SDN Environment. The major aim of the presented technique lies in the recognition of DDoS attacks from the cloud-SDN platform. The MEDR-DDoSAD technique transforms the input data into images and the features are derived via deep convolutional neural network based Xception model.   2022 IEEE.</text>
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          <name>Creator</name>
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              <text>Christila S.A.; Sivakumar R.</text>
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              <text>4th International Conference on Circuits, Control, Communication and Computing, I4C 2022, pp. 451-455.</text>
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          <name>Publisher</name>
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              <text>Institute of Electrical and Electronics Engineers Inc.</text>
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          <name>Date</name>
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              <text>2022-01-01</text>
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              <text>&lt;a href="https://doi.org/10.1109/I4C57141.2022.10057641" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1109/I4C57141.2022.10057641&lt;/a&gt;
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              <text>Restricted Access</text>
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              <text>ISBN: 979-835039747-5</text>
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              <text>Online</text>
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              <text>English</text>
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              <text>Christila S.A., CHRIST (Deemed to Be University), Dept. of Computer Science, Karnataka, Bengaluru, India; Sivakumar R., CHRIST (Deemed to Be University), Dept. of Computer Science, Karnataka, Bengaluru, India</text>
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