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Journal of Information and Optimization Sciences cover
Hybrid ·Peer-reviewed·ISSN (Online): 2169-0103·ISSN (Print): 0252-2667

WoS  JIF 2026 : 0.4 (Q4)

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Monthly Journal: Publishes theoretical and applied research on topics in information and optimization sciences.

Issues up to 2022 co-published with and available at:Taylor & Francis
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Open Access Research Article

Generic row filtering and column masking for fine-grained data access control through secure JDBC drivers

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pp. 1955–1964Vol. 47Issue 5-BMay 2026DOI: 10.47974/JIOS-2287XML
Received:
01 Apr 2025
Published Online:
23 Apr 2026
Article type:
Research Article
Language:
EN
Article no.:
JIOS-2287
Pages:
1955–1964

Abstract

In today’s data-centric world, safeguarding confidentiality and staying compliant with strict privacy laws is no longer optionality – it is essential. However, traditional database security often lacks the precision needed for truly fine-grained access control. This paper presents a specialized JDBC driver designed to bridge that gap. By acting as a transparent middleware, our approach enforces universal row-level filtering and column-level masking that integrates effortlessly with existing applications. Working with RDBMS like Oracle/MySQL or data warehouses such as Hive, this driver offers a unified security layer. We detail the architecture and implementation of the driver, demonstrating through performance evaluations that it effectively secures data without compromising system speed.

Keywords

Subject Classifications

Primary 68P27Secondary 68M25

References

[1] S. K. Mandal, R. Singh, N. Chandu, D. Mehta, S. K. Henge, D. Kothapeta, C. K. Hinge, A. Sharma, and T. Hussain, “Evolutionary multi-authentication cryptographic key implications for secure data access control,” Journal of Discrete Mathematical Sciences and Cryptography, vol. 28, no. 5-B, pp. 1865–1874 (2025), doi : 10.47974/JDMSC-2363.
[2] M. Yaramadhi, K. S. Reddy, K. R. Prasad, M. Kavya, E. Muniyandy, S. Rajeswari, and R. Thouheed, “Preventing insider attacks: Leveraging Identity and Access Management (IAM) solutions over traditional password-based authentication,” Journal of Information and Optimization Sciences, vol. 46, no. 2, pp. 509–519 (2025), doi : 10.47974/JIOS-1931.
[3] C. Cotner and R. L. Miller, “Row level security in database management system,” U.S. Patent, 9, 870, 483 B2 (2018).
[4] A. Gosain and A. Arora, “Security Issues in Data Warehouse: A Systematic Review,” in International Conference on Intelligent Computing, Communication & Convergence, Bhubneshwar (2015).
[5] R. K. Sharma and V. Kapoor, “A Generic Data Privacy Approach for Relational Databases and Data Warehouse,” International Journal of Intelligent Systems and Applications in Engineering (IJISAE), vol. 11, no. 3, pp. 1286–1289 (2023)
[6] K. Shirudkar and D. Motwani, “Big Data Security,” International Journal of Advance Research in Computer Science and Software En­gineering, vol. 5, no. 3, pp. 1102-1105 (2015).
[7] D. S. Terzi, R. Terzi, and S. Sagiroglu, “A Survey on Security and Privacy Issues in Big Data,” in 10th International Conference for Inter­net Technology and Secured Transactions  (2015). 
[8] Y. Tian, “Towards the Development of Best Data Security for Big Data,” in Communications and Networks, vol. 9, pp. 291-301 (2017).  
[9] V. N. Inukollu, S. Arsi, and S. R. Ravuri, “Security Issues associated with Big Data in cloud computing,” in International Journal of Network Security & Its Applications (IJNSA) vol. 6, no. 3, pp. 51-55 (2014). 
[10]  R. K. Sharma and V. Kapoor, “Implementing Row and Column Level Security in Hive,” in International Journal of Advanced Research in Computer Engineering & Technology (IJARCET), vol. 6, no. 9, pp. 1329-1332 (2017)
[11] K. Tran, S. Vasudevan, P. Desai, A. Gorelik, M. Ahuja, A. Y. Venkateshababu, M. Verma, D. Hu, W. E. Moustafa, V. Rajamani, A. Gupta, I. Buenrostro, and K. Raina, “Data Guard: A Fine-grained Purpose-based Access Control System for Large Data Warehouses,” in arXiv preprint, arXiv:2502.01998 (2025).
[12] Johannes Koppenwallner and Erich Schikuta, “DiCE - A Data Encryption Proxy for the Cloud,” arXiv preprint, arXiv:2310.05710 (2023).
[13] Oracle Corporation, “Using Oracle Virtual Private Database to Control Data Access,” Oracle Documentation, Oracle (2018). 
[14] Carson Smith, “Proxy-Based Dynamic Data Masking in FieldShield,” IRI Blog (2023). Available: https://beta.iri.com

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