Article Per Year (5 Year)
p-Index From 2021 - 2026
0.408
P-Index
This Author published in this journals
All Journal International Journal of Applied Mathematics, Sciences, and Technology for National Defense
Kotilingala, Sudheer
Unknown Affiliation
Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Mathematics Physics

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Zero trust framework for protecting federal networks and cloud services Kotilingala, Sudheer
International Journal of Applied Mathematics, Sciences, and Technology for National Defense Vol. 3 No. 1 (2025): International Journal of Applied Mathematics, Sciences, and Technology for Nati
Publisher : FoundAE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58524/app.sci.def.v3i1.669

Abstract

There has been a rapid uptake of cloud technologies in public sectors due to increased efficiency across operations while increasing the complexity of cyber threats. This paper analyses the original Zero Trust Architecture (ZTA) concept as a security concept applicable to federal networks and cloud services protection. It mainly involves linking ZTA principles with FedRAMP regulations and insists on constant validation, minimisation of rights, and breach presumption. The study outlines guidelines for ZTA implementations for compliance and readiness in the cloud environments.
Next-Gen SOC: Leveraging generative AI for scalable threat detection and AI-powered alert classification Kotilingala, Sudheer
International Journal of Applied Mathematics, Sciences, and Technology for National Defense Vol. 3 No. 3 (2025): International Journal of Applied Mathematics, Sciences, and Technology for Nati
Publisher : FoundAE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58524/app.sci.def.v3i3.670

Abstract

The volume of alerts produced by the SIEM system causes SOC analysts to experience alert fatigue, with actual security incidents obscured by more than fifty percent of notifications being considered false positives. This inefficiency causes delays in response times and puts organisations at risk due to insufficient resource allocation. We have, therefore, introduced a new framework in this paper, which incorporates LLMs into SOC initiatives. Overall, with the help of contextual understanding elements of LLMs, our framework concludes with 95,5% accuracy to classify the alerts as false positives or actual threats. The study’s results, therefore, validate less alert fatigue, improved systems functioning, and shorter time to critical security events using the proposed methodology. As a result, this paper outlines the proposed system’s description, development, and evaluation to determine its potential for future SOC operations.
Co-Authors