AI-Powered Data Governance: Advancing Privacy and Compliance Through Data Masking and Sentiment Analysis

The integration of artificial intelligence in data governance has revolutionized how organizations protect and manage sensitive information while ensuring regulatory compliance. Advanced data masking techniques combined with sentiment analysis capabilities have established new standards in privacy protection and compliance monitoring. The implementation of comprehensive frameworks incorporating static and dynamic data masking, coupled with real-time sentiment analysis, has significantly enhanced organizations' ability to detect and prevent compliance violations. Modern architectural considerations focusing on scalability, security, and resource optimization have enabled robust implementation of AI-driven governance solutions. The emergence of enhanced privacy technologies, including homomorphic encryption and federated learning systems, alongside explainable AI frameworks and edge computing integration, has transformed traditional data protection approaches. These technological advancements have led to substantial improvements in data security, compliance monitoring efficiency, and overall governance effectiveness while reducing operational complexities and associated costs.

Authors

Institutions

Publication Details

Journal
Journal of Computer Science and Technology Studies
Published
2025-05-23
DOI
https://doi.org/10.32996/jcsts.2025.7.3.92
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

AI-Powered Data Governance: Advancing Privacy and Compliance Through Data Masking and Sentiment Analysis

Bujjibabu Katta
Journal of Computer Science and Technology Studies
Ethics and Social Impacts of AI
article

AI-Powered Data Governance: Advancing Privacy and Compliance Through Data Masking and Sentiment Analysis

Bujjibabu Katta
article en

Abstract

The integration of artificial intelligence in data governance has revolutionized how organizations protect and manage sensitive information while ensuring regulatory compliance. Advanced data masking techniques combined with sentiment analysis capabilities have established new standards in privacy protection and compliance monitoring. The implementation of comprehensive frameworks incorporating static and dynamic data masking, coupled with real-time sentiment analysis, has significantly enhanced organizations' ability to detect and prevent compliance violations. Modern architectural considerations focusing on scalability, security, and resource optimization have enabled robust implementation of AI-driven governance solutions. The emergence of enhanced privacy technologies, including homomorphic encryption and federated learning systems, alongside explainable AI frameworks and edge computing integration, has transformed traditional data protection approaches. These technological advancements have led to substantial improvements in data security, compliance monitoring efficiency, and overall governance effectiveness while reducing operational complexities and associated costs.

Journal of Computer Science and Technology StudiesVol. 7(3)
Fidelity Investments (United States) (US)
Openalex Percentile: Top 90%
Ethics and Social Impacts of AI
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.