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                <text>Conference Papers</text>
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    <name>Conference Paper</name>
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          <name>Title</name>
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              <text>Detection of Malicious Nodes in Flying Ad-hoc Network with Supervised Machine Learning</text>
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              <text>Linear Regression; Logistic Regression; Node Existence Matrix; Node Reputation Matrix; Path Reputation Matrix</text>
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              <text>An Ad-hoc network (FANET) is a new upcoming technology which has been used in several sectors. Ad-hoc networks are mostly wireless local area networks (LANs). The devices communicate with each other directly instead of relying on a base station or access points as in wireless LANs for data transfer. In an Ad-hoc network the communication between one node to another in a FANET is not secured and there isn't any authorized protocol for secured communication. Therefore, we suggest an algorithm to detect the malicious node in a network. This algorithm uses Linear regression to calculate the reputation or trust value of a node in the network. Then the above found trust value is used to classify the node as normal node or malicious node based on the Logistic Regression Classification. Thus, allowing a secure communication of data and avoiding attacks.  2022 IEEE.</text>
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          <name>Creator</name>
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              <text>Tangade S.; Kumaar R.A.; Malavika S.; Monisha S.; Azam F.</text>
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              <text>Proceedings of the 3rd International Conference on Smart Technologies in Computing, Electrical and Electronics, ICSTCEE 2022</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/ICSTCEE56972.2022.10099989" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1109/ICSTCEE56972.2022.10099989&lt;/a&gt;
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          <name>Rights</name>
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              <text>Restricted Access</text>
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              <text>ISBN: 978-166545664-7</text>
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          <name>Format</name>
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              <text>Online</text>
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              <text>English</text>
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              <text>Conference paper</text>
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              <text>Tangade S., CHRIST University, Dept. of CSE., Bengaluru, India; Kumaar R.A., School of ECE, REVA University, Bengaluru, India; Malavika S., School of ECE, REVA University, Bengaluru, India; Monisha S., School of ECE, REVA University, Bengaluru, India; Azam F., School of Comp. Science and Engineering, REVA University, Bengaluru, India</text>
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