Mitigating Data Leakage Risks: A Comprehensive Approach to Data Governance in Age of AI

The use of Large Language Models (LLMs) is in-creasing in various industries, leading to growing concerns about data governance. Although LLMs can handle natural language processing and generation exceptionally well, there are important issues to consider regarding data privacy, security, and compliance. This paper examines the hurdles that LLMs present in data governance in different industries and suggests a solution using microservice architecture customized to each department's require-ments. By incorporating fine-tuned language models specific to each domain within a microservice structure, companies can reduce the chances of data breaches and improve their data governance processes.

Authors

Publication Details

Journal
International Journal of Science and Research (IJSR)
Published
2025-04-25
DOI
https://doi.org/10.21275/sr25421041811
Primary Topic
Digital and Cyber Forensics
Type
article
Field-Weighted Citation Impact
0.00
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article

Mitigating Data Leakage Risks: A Comprehensive Approach to Data Governance in Age of AI

Atharva Rajiv Weginwar, Raghunandan Nuggehalli Ramesha, Jayaprakash Ramsaran, Suyash Bhogawar
International Journal of Science and Research (IJSR)
Digital and Cyber Forensics
article

Mitigating Data Leakage Risks: A Comprehensive Approach to Data Governance in Age of AI

Atharva Rajiv Weginwar, Raghunandan Nuggehalli Ramesha, Jayaprakash Ramsaran, Suyash Bhogawar
article en

Abstract

The use of Large Language Models (LLMs) is in-creasing in various industries, leading to growing concerns about data governance. Although LLMs can handle natural language processing and generation exceptionally well, there are important issues to consider regarding data privacy, security, and compliance. This paper examines the hurdles that LLMs present in data governance in different industries and suggests a solution using microservice architecture customized to each department's require-ments. By incorporating fine-tuned language models specific to each domain within a microservice structure, companies can reduce the chances of data breaches and improve their data governance processes.

International Journal of Science and Research (IJSR)Vol. 14(4)
Climate action
Openalex Percentile: Top 89%
Digital and Cyber Forensics
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