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              <text>Insights of Evolving Methods Towards Screening of AI-Enhanced Malware in IoT Environment</text>
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              <text>Artificial Intelligence; detection; Internet of Things; Malware; prevention; Security; Threats</text>
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              <text>Internet-of-Things (IoT) has been encountering a series of potential form of threats since past half decades. Artificial Intelligence (AI), which is frequently seen to be adopted to solve various challenges in IoT operation, has now been adopted even by attackers for their malicious purposes. Of all forms of threats, AI-enhanced malwares are one of the most potential forms of threats which has its extensive effectiveness towards the complete operation of the entire IoT environment. Hence, this manuscript discusses existing detection and prevention approaches evolved in current literatures to understand various taxonomies of solution-based methodologies for circumventing such threats. The paper also contributes towards highlighting the potential open-ended issues that are yet to be addressed.  The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.</text>
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              <text>Shahabadkar R.; Nandeeswar S.B.; Soman R.; Sangeetha G.</text>
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              <text>Lecture Notes in Networks and Systems, Vol-1120 LNNS, pp. 694-704.</text>
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              <text>Springer Science and Business Media Deutschland GmbH</text>
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              <text>&lt;a href="https://doi.org/10.1007/978-3-031-70518-2_57" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1007/978-3-031-70518-2_57&lt;/a&gt;
&lt;br /&gt;&lt;br /&gt;&lt;a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85210812213&amp;amp;doi=10.1007%2F978-3-031-70518-2_57&amp;amp;partnerID=40&amp;amp;md5=9ad21107c217298867738a5644654d34" target="_blank" rel="noreferrer noopener"&gt;https://www.scopus.com/inward/record.uri?eid=2-s2.0-85210812213&amp;amp;doi=10.1007%2f978-3-031-70518-2_57&amp;amp;partnerID=40&amp;amp;md5=9ad21107c217298867738a5644654d34&lt;/a&gt;</text>
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              <text>ISSN: 23673370; ISBN: 978-303170517-5</text>
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              <text>Shahabadkar R., Department of CSE, AMC Engineering College, Karnataka, Bangaluru, 560083, India; Nandeeswar S.B., Department of CSE (AIML), AMC Engineering College, Karnataka, Bengaluru, India; Soman R., Department of CSE, BNM Institute of Technology, Banashankari Stage II, Karnataka, Bangaluru, 560070, India; Sangeetha G., Department of Computer Science, Christ University, Karnataka, Bengaluru, India</text>
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