International Journal of Innovative Research in Engineering and Management
Year: 2025, Volume: 13, Issue: 1
First page : ( 34) Last page : ( 41)
Online ISSN : 2350-0557.
DOI: 10.55524/ijircst.2025.13.1.5 | DOI URL: https://doi.org/10.55524/ijircst.2025.13.1.5
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This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)
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Sai Ratna Prasad Dandamudi , Jaideep Sajja, Amit Khanna
The United States has rapidly advanced in data networking infrastructure, driven by the widespread adoption of 5G networks, Internet of Things (IoT) devices, and cloud computing technologies. This rapid technological expansion has fueled economic growth and enhanced connectivity but has also introduced vulnerabilities to increasingly sophisticated cyber threats. As cyberattacks grow more advanced, organizations face significant challenges in maintaining network security and ensuring data integrity. This paper examines the role of artificial intelligence (AI) in addressing these challenges by improving data networking and bolstering cybersecurity efforts across the U.S.
Through the analysis of empirical data from major network providers, leading cybersecurity firms, and government agencies, the study focuses on three critical areas: predictive threat detection, real-time anomaly response, and network optimization. AI has demonstrated unparalleled capabilities in these domains, enabling organizations to proactively identify and mitigate threats while optimizing network performance. Results reveal that AI-driven systems achieve an impressive 92% accuracy in cyber threat detection, reduce average response times to under 1.5 minutes, and improve bandwidth allocation efficiency by 35% during peak traffic hours.
The findings underscore the transformative potential of AI in enhancing both network efficiency and cybersecurity measures, resulting in substantial economic benefits. Organizations adopting AI solutions report a reduction in data breach costs by up to $18 billion annually and a marked improvement in operational efficiency. Despite these advancements, challenges such as high implementation costs, skill shortages, and ethical concerns must be addressed to maximize AI’s potential. This study provides actionable insights for stakeholders, emphasizing the necessity of AI in safeguarding U.S. digital infrastructure in an evolving technological landscape.
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S. Lodhi, A. Hussain, and A. Gill, “Renewable energy technologies: Present patterns and upcoming paths in ecological power production,” Global Journal of Universal Studies, vol. 1, no. 1, pp. 108–131, 2024. Available From: http://dx.doi.org/10.70445/gjus.1.1.10
S. Lodhi, A. Hussain, and A. Gill, “Green innovations: Artificial intelligence and sustainable materials in production,” BULLET: Jurnal Multidisiplin Ilmu, vol. 3, no. 4, pp. 492–507, 2024. Available From: https://journal.mediapublikasi.id/index.php/bullet/article/view /4474
S. Lodhi, A. Hussain, and A. Gill, “Artificial intelligence: Pioneering the future of sustainable cutting tools in smart manufacturing,” BIN: Bulletin of Informatics, vol. 2, no. 1, pp. 147–162, 2024. Available From: https://ojs.jurnalmahasiswa.com/ojs/index.php/bin/article/vie w/355
A. Tariq, M. Hayat, A. Hussain, A. Tariq, and S. Rasool, “Maximizing efficiency in telemedicine: An IoT-based artificial intelligence optimization framework for health analysis,” European Journal of Science, Innovation and Technology, vol. 3, no. 6, pp. 48–61, 2023. Available From: https://shorturl.at/2IVfp
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MS Scholar, Department of Computer Science, American National University, Virginia, USA
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Anjum Ahsan, Parvez Rauf, Mohd Haroon.
January 2025 - Vol 13, Issue 1
Sai Ratna Prasad Dandamudi, Jaideep Sajja, Amit Khanna.
January 2025 - Vol 13, Issue 1
Sai Ratna Prasad Dandamudi, Jaideep Sajja, Amit Khanna.
January 2025 - Vol 13, Issue 1
