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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM64717

Advanced Administrator Intrusion Prevention Mechanizer: A Secure Policy-Based Administration Framework for Database and Application Security

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM64717

Volume:

10 |

6 |

Jun 2026

Pages:

1-5

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM64717

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

Dinesh Kumar V

Dinesh Kumar V

Department of Cyber Security

DR.M.G.R. Educational and Research Institute

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Magna Y

Department of Cyber Security

DR.M.G.R. Educational and Research Institute

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Abstract

Escalating reliance on large-scale distributed applications has placed unprecedented demands on secure, policy-driven access control mechanisms within enterprise environments. Conventional administrative architectures are hampered by weak policy governance, vulnerability to insider exploitation, and inadequate intrusion deterrence, collectively exposing organizations to significant data-security risks. This paper presents the Advanced Administrator Intrusion Prevention Mechanizer (AAIPM), a novel framework that integrates text-mining-driven policy synthesis, multi-tier privilege stratification, and a Joint Threshold Administration Mechanism (JTAM) to achieve comprehensive protection of application and database assets. The JTAM enforces a distributed consensus requirement, mandating approval from a quorum of administrators prior to committing any high-impact database operation. Privilege classification into aggressive, fine-grained, and conservative tiers further enables granular, role-calibrated access governance. Evaluation results confirm that the AAIPM substantially reduces unauthorized-access incidents while enabling automated, context-aware policy generation without exposure of sensitive system internals. The proposed architecture constitutes a scalable and interoperable solution for modern enterprise security administration.

KEYWORDS

Intrusion Prevention System Policy-Based Access Control Text Mining Joint Threshold Administration Mechanism (JTAM) Multi-Level Authentication Database Security Insider Threat Detection Privilege Stratification.

Cite This Article

Dinesh Kumar V, Magna Y, "Advanced Administrator Intrusion Prevention Mechanizer: A Secure Policy-Based Administration Framework for Database and Application Security," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 6, pp. 1-5, Jun 2026. https://doi.org/10.55041/IJSREM64717

Full Article/Conclusion

The Advanced Administrator Intrusion Prevention Mechanizer (AAIPM) represents a substantive contribution to enterprise database security administration. By unifying automated text-mining-driven policy synthesis, JTAM-enforced distributed approval, and a tri-tier privilege stratification model, the system addresses critical security gaps that conventional platforms leave unresolved. The AAIPM's practical deployability—implemented on widely available enterprise technologies with no specialized hardware requirements—positions it as an economically viable and operationally realistic security enhancement for organizations of varying scale. Future research will investigate deep learning-based anomaly detection for real-time threat identification, blockchain-anchored policy storage for tamper-proof governance records, and federated deployment architectures for distributed enterprise environments.

References

[1] Mustafa, I., Salimi, A., and Scriney, M., "Secure Communication and Edge-Blind Policy Enforcement Framework (SCOPE) for Distributed Architectures," Distributed Systems Security Conference, 2025. [2] Saqib Ali et al., "A Systematic Review on Blockchain-Based Access Control Systems in Cloud Environment," IEEE Access, vol. 12, pp. 45231–45245, 2024. [3] Ayman Abdelhamid et al., "The Survey on the Dual Nature of XAI Challenges in Intrusion Detection and Their Potential for AI Innovation," Computers & Security Journal, vol. 138, 2024. [4] Jinpeng Wei et al., "ABAC Policy Mining through Affiliation Networks and Biclique Analysis," ACM Digital Library, 2024. [5] Mohamed Hamdy et al., "Advancing Cybersecurity: A Comprehensive Review of AI-Driven Detection Techniques," International Journal of Information Security, vol. 23, no. 4, 2024. [6] Xiaofei Zhang et al., "Current Status, Challenges, and Future Trends of Deep Learning-Based Intrusion Detection Models," IEEE Transactions on Network Security, 2024. [7] Abdulrahman Alharbi et al., "Insider Threat Mitigation: Systematic Literature Review," Journal of Network and Computer Applications, vol. 240, 2024. [8] Sahoo, S., Halder, R., and Mondal, S., "Anomaly-Free Federated Access Control Policy Enforcement Framework for Decentralized Systems," Decentralized Systems Proceedings, 2025. [9] Anderson, K., and Lee, J. S., "Natural Language Processing and Text-Mining for Security Policy Harmonization in Multi-Tenant Environments," Journal of Cloud Security, 2023. [10] Grichenko, V., and European Security Alliance, "Adaptive Authentication and Risk-Based Access Control in High-Security Corporate Infrastructures," European Cybersecurity Symposium, 2025.

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Publication Date

6/9/2026

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Double-Blind Peer Review

Review Rounds: 2

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