AI Governance and Cybersecurity Policy in the Public Sector: Balancing National Security, Data Privacy, and Ethical Risk
Abstract
The increasing deployment of artificial intelligence (AI) in public-sector environments creates a complex governance challenge in which cybersecurity, national security, data privacy, and ethical accountability must be addressed simultaneously. Government agencies increasingly depend on data-intensive decision systems, making policy frameworks essential for controlling security exposure and maintaining public trust. This research and review paper examines AI governance and cybersecurity policy from a public-sector perspective, with particular emphasis on the balance between national-security objectives, privacy protection, organizational knowledge, stakeholder attitudes, and ethical risk. The study adopts a structured qualitative review and conceptual synthesis of the references supplied for this research. Ahmed (2024) provides the principal conceptual foundation for examining cybersecurity policy frameworks for AI in government, while the remaining studies are critically interpreted for their evidence concerning knowledge, attitudes, stakeholder support, counseling, perception, and technology acceptance. Although several supplied references originate from healthcare and contraceptive-service research rather than AI governance, their findings provide transferable insights into how knowledge, communication, stakeholder perceptions, and institutional support can influence policy implementation. The analysis indicates that effective public-sector AI governance requires more than technical security controls. It requires coordinated policy mechanisms, transparent decision processes, privacy-conscious data management, stakeholder education, accountability structures, and continuous risk assessment. The paper proposes an integrated conceptual governance model linking AI cybersecurity controls with privacy safeguards, ethical oversight, stakeholder capacity, and institutional accountability. The findings further indicate that policy effectiveness depends on the ability of public institutions to reconcile security imperatives with individual rights rather than treating them as independent objectives.
Keywords
References
Similar Articles
- Dr. Lin K. Chen, A Novel Energy-Efficient and Secure Opportunistic Routing Protocol for Data Transmission in Wireless Sensor Networks , International Journal of Cyber Threat Intelligence and Secure Networking: Vol. 3 No. 06 (2026): Volume 03 Issue 06
- Dr. Arjun Pratap Singh, Dr. Neha Verma, Research on Unusual Transmission Pattern Recognition in Telecommunication Infrastructure Using Fuzzy Equation Approach , International Journal of Cyber Threat Intelligence and Secure Networking: Vol. 3 No. 04 (2026): Volume 03 Issue 04
- Mr. Deepak Mehta, A Review of Explainable Machine Learning Methods for Malware Detection and Classification , International Journal of Cyber Threat Intelligence and Secure Networking: Vol. 3 No. 07 (2026): Volume 03 Issue 07
- Dr. Nguyen Van Minh, Dr. Tran Thi Lan, Cross-Layer Protocol Design and Integration Strategies for IoT and IoRT Convergence: An Analytical Review of Enabling Technologies, Challenges, and Emerging Solutions , International Journal of Cyber Threat Intelligence and Secure Networking: Vol. 3 No. 08 (2026): Volume 03 Issue 08
- Muhammad Rizki Pratama, Siti Nurhaliza Putri, Deep Graph Learning Architecture for Real-Time Cyber Threat Identification and Detection in Cloud Platforms , International Journal of Cyber Threat Intelligence and Secure Networking: Vol. 3 No. 08 (2026): Volume 03 Issue 08
- Dr. Thomas Becker, Kevin Brooks, STRENGTHENING CYBER RESILIENCE: A COMPREHENSIVE EVALUATION OF SOCIAL ENGINEERING AWARENESS PROGRAMS , International Journal of Cyber Threat Intelligence and Secure Networking: Vol. 1 No. 01 (2024): Volume 01 Issue 01
- Dr. Arjun Mehta, Dr. Priya Nair, Comprehensive Review of Modern Health Monitoring Technologies and Digital Healthcare Services , International Journal of Cyber Threat Intelligence and Secure Networking: Vol. 3 No. 07 (2026): Volume 03 Issue 07
- Ms. Shivani Jain, A Survey on Deep Learning Approaches for Malware Detection and Classification , International Journal of Cyber Threat Intelligence and Secure Networking: Vol. 3 No. 08 (2026): Volume 03 Issue 08
- Dr. Tanvi Das, James D. Walker, A FEDERATED MULTI-MODAL SYSTEM FOR INSIDER THREAT DETECTION IN ENERGY INFRASTRUCTURE USING BIOMETRIC AND CYBER DATA , International Journal of Cyber Threat Intelligence and Secure Networking: Vol. 2 No. 01 (2025): Volume 02 Issue 01
- Dr. Wei-Lin Cheng, COLLATERAL EFFECTS AND UNINTENDED REPERCUSSIONS IN OFFENSIVE CYBER OPERATIONS: A SYSTEMATIC LITERATURE REVIEW , International Journal of Cyber Threat Intelligence and Secure Networking: Vol. 2 No. 03 (2025): Volume 02 Issue 03
You may also start an advanced similarity search for this article.