AI-Powered Cybersecurity for the Financial Public Sector: A Microsoft Sentinel and Low-Code Power Automate Framework

DOI

10.2991/978-94-6239-678-4_3How to use a DOI?

Keywords

Cybersecurity; Microsoft Sentinel; AI; Finance; Low-Code; Public sector; Automation

Abstract

The social sphere of the financial world is becoming increasingly exposed to cyber threats, and therefore defense systems must be developed to work independently and be intelligent and capable of expanding automatically. This research paper considers how the artificial intelligence-powered runs of Microsoft Sentinel SIEM scopes can be combined with low-code automation and recent technology in Power Automate to improve cyber resilience. It was a qualitative test on around 50,000 actual and simulated security violations within the financial industry that focused on phishing, privilege escalation, abnormal logins, and fraudulent access. Some of the most important measures of performance included Mean Time to Detect (MTTD), Mean Time to Respond (MTTR), accuracy of detection, false positive rate (FPR) and false negative rate (FNR). The results were pretty impressive: MTTD, MTTR and accuracy were improved 64 percent, 69 percent and 88.5 percent to 96.2 percent, respectively. This was confirmed through comparisons and benchmarking to Splunk and IBM QRadar, and activities performed to determine that the load and the cost/incident to the analysts was minimized. At least at the 95 percent level, statistical tests revealed that such changes were significant. The article demonstrates how artificial intelligence could be used to monitor and track cryptocurrencies with the help of automated processes in order to base decisions taken by the financial security operations on statistical information. The findings show that the Sentinel Power Automate system appears as an affordable, viable and scalable solution to guard financial institutions against growing cyber threats, and it meets the requirements of the regulations.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Srinivas Kamineni
AU  - Sarat Piridi
AU  - Satyanarayana Asundi
AU  - Nataraja Kumar Koduri
PY  - 2026
DA  - 2026/05/28
TI  - AI-Powered Cybersecurity for the Financial Public Sector: A Microsoft Sentinel and Low-Code Power Automate Framework
BT  - Proceedings of the 2nd International Conference on Recent Advancement and Modernization in Sustainable Intelligent Technologies & Applications (RAMSITA-2026)
PB  - Atlantis Press
SP  - 20
EP  - 32
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6239-678-4_3
DO  - 10.2991/978-94-6239-678-4_3
ID  - Kamineni2026
ER  -