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              <text>Cybersecurity Threats Detection in Intelligent Networks using Predictive Analytics Approaches</text>
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              <text>AI (Artificial Intelligence); cyber security; cyber threats; threat detection</text>
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              <text>The modern scenario of network vulnerabilities necessitates the adoption of sophisticated detection and mitigation strategies. Predictive analytics is surfaced to be a powerful tool in the fight against cybercrime, offering unparalleled capabilities for automating tasks, analyzing vast amounts of data, and identifying complex patterns that might elude human analysts. This paper presents a comprehensive overview of how AI is transforming the field of cybersecurity. Machine intelligence can bring revolution to cybersecurity by providing advanced defense capabilities. Addressing ethical concerns, ensuring model explainability, and fostering collaboration between researchers and developers are crucial for maximizing the positive impact of AI in this critical domain.   2024 IEEE.</text>
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              <text>Duary S.; Choudhury P.; Mishra S.; Sharma V.; Rao D.D.; Paul Aderemi A.</text>
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              <text>4th International Conference on Innovative Practices in Technology and Management 2024, ICIPTM 2024</text>
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              <text>Institute of Electrical and Electronics Engineers Inc.</text>
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              <text>&lt;a href="https://doi.org/10.1109/ICIPTM59628.2024.10563348" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1109/ICIPTM59628.2024.10563348&lt;/a&gt;
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              <text>ISBN: 979-835030775-7</text>
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              <text>Duary S., Kalinga Institute of Industrial Technology, India; Choudhury P., Kalinga Institute of Industrial Technology, India; Mishra S., Kalinga Institute of Industrial Technology, India; Sharma V., Christ (Deemed to Be University), Department of Computational Sciences, Delhi NCR, India; Rao D.D., Infosys, Independent Researcher Consultant, United States; Paul Aderemi A., University of Bolton, School of Creative Technologies, United Kingdom</text>
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