Leveraging Artificial Intelligence for Data Networking and Cybersecurity in the United States
Journal Title: International Journal of Innovative Research in Computer Science and Technology - Year 2025, Vol 13, Issue 1
Abstract
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.
Authors and Affiliations
Sai Ratna Prasad Dandamudi , Jaideep Sajja , Amit Khanna
Keywords
Related Articles
- EP ID EP755759
- DOI 10.55524/ijircst.2025.13.1.5
- Views 35
- Downloads 0
Impact of Test Automation and Test Case Design Techniques - Challenges
Test Automation is more than a set of tests run to generate apparent results. It includes designing testware, implementing automated test cases, and monitoring and interpreting a broad range of results. Automation by sim...
Secure Big Data Access Control Policies for Cloud Computing Environment
As the term indicates the Big data it means we are work for the something big or can say something large in the Amount, Data the high volume is known as the big data.Now a Day for storing the data file in the Computer Sc...
Separating FECG from MECG and Analyzing Fetal Heart Rate
Figuring out fetal coronary heart can be essential for monitoring the situation of a fetus. While an ECG signal is recorded by way of putting electrodes on the maternal stomach, the fetal ECG is regularly masked by using...
An Overview of Openings in Concrete Deep Beams-A Comprehensive Analysis
The study of deep beams with openings in their webs and how to reinforce them is crucial for ensuring strong and effective structures. This collection of research examines various aspects of the topic, including the use...
A Study on Antimicrobial Finish on Textile Using Plant Extract
The use of plant-based biological colorants or other engaged biological extracts in textile coatings as antibacterial textiles finishes is gaining traction. Numerous plant-derived natural colors have potent antibacterial...