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                <text>Conference Papers</text>
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    <name>Conference Paper</name>
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              <text>Trust Model for Cloud Using Weighted KNN Classification for Better User Access Control</text>
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          <name>Subject</name>
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              <text>Access control; Cloud environment and trust value; Nearest neighbor</text>
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              <text>The majority of the time, cloud computing is a service-based technology that provides Internet-based technological services. Cloud computing has had explosive growth since its debut, and it is now integrated into a wide variety of online services. These have the primary benefit of allowing thin clients to access the resources and services. Even while it could appear favorable, there are a lot of potential weak points for various types of assaults and cyber threats. Access control is one of the several protection layers that are available as part of cloud security solutions. In order to improve cloud security, this research introduces a unique access control mechanism. For granting users access to various resources, the suggested approach applies the trust concept. For the purpose of predicting trust, the KNN model was recently proposed, however the current approach for categorizing options is sensitive and unstable, particularly when an unbalanced data scenario occurs. Furthermore, it has been discovered that using the exponent distance as a weighting system improves classification performance and lowers variance. The prediction of the users trust levels using weighted K-means closest neighbors is presented in this research. According to the findings, the suggested approach is more effective in terms of throughput, cost, and delay.  2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.</text>
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              <text>Rajagopal M.; Ramkumar S.; Gobinath R.; Thimmiraja J.</text>
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              <text>Lecture Notes in Networks and Systems, Vol-673 LNNS, pp. 237-248.</text>
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          <name>Publisher</name>
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              <text>Springer Science and Business Media Deutschland GmbH</text>
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              <text>2023-01-01</text>
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              <text>&lt;a href="https://doi.org/10.1007/978-981-99-1745-7_17" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1007/978-981-99-1745-7_17&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85168767621&amp;amp;doi=10.1007%2F978-981-99-1745-7_17&amp;amp;partnerID=40&amp;amp;md5=5eeb3fdbc7f12440b65573090decbbf9" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85168767621&amp;amp;doi=10.1007%2f978-981-99-1745-7_17&amp;amp;partnerID=40&amp;amp;md5=5eeb3fdbc7f12440b65573090decbbf9&lt;/a&gt;</text>
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              <text>Restricted Access</text>
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              <text>ISSN: 23673370; ISBN: 978-981991744-0</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>Rajagopal M., Lean Operations and Systems, School of Business and Management, CHRIST (Deemed to be University), Bangalore, India; Ramkumar S., Department of Computer Science, School of Sciences, CHRIST (Deemed to be University), Bangalore, India; Gobinath R., Department of Computer Science, School of Sciences, CHRIST (Deemed to be University), Bangalore, India; Thimmiraja J., Department of Information Technology, Dr. Mahalingam College of Engineering and Technology, Tamil Nadu, Pollachi, India</text>
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