Agunuru, Arun Kumar Reddy (2025) AI-powered data masking and safety: A technical perspective. World Journal of Advanced Engineering Technology and Sciences, 15 (3). pp. 607-613. ISSN 2582-8266
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Abstract
Artificial intelligence has fundamentally transformed data masking and safety practices, creating powerful new capabilities for organizations seeking to balance privacy protection with data utility. This technical article examines the multifaceted applications of AI across the data protection landscape, from intelligent sensitive data detection to contextual masking intelligence and adaptive anonymization frameworks. The integration of machine learning, natural language processing, computer vision, and knowledge graph techniques has enabled unprecedented protection for both structured and unstructured data while preserving analytical value. As regulatory requirements grow increasingly stringent and data volumes continue to expand, AI-driven approaches provide essential capabilities for maintaining compliance, enhancing privacy, and enabling secure data utilization across diverse organizational contexts.
Item Type: | Article |
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Official URL: | https://doi.org/10.30574/wjaets.2025.15.3.0860 |
Uncontrolled Keywords: | Data Masking; Artificial Intelligence; Privacy Preservation; Unstructured Data; Knowledge Graphs |
Depositing User: | Editor Engineering Section |
Date Deposited: | 16 Aug 2025 12:59 |
Related URLs: | |
URI: | https://eprint.scholarsrepository.com/id/eprint/4514 |