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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM64270
Volume:
10 |
5 |
May 2026
Pages:
1-5
Publication Frequency:
Monthly (12 issues per year)
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.
Department of Computer science
R.V college of Engineering
Department of Computer science
R.V college of Engineering
Department of Computer science
R.V college of Engineering
Department of Computer science
R.V college of Engineering
Artificial Intelligence (AI) is increasingly used in national security for surveillance, cyber defense, threat prediction, and intelligence analysis. However, the rapid growth of AI in defense systems has created major concerns related to privacy violations, biased decision-making, misuse of surveillance, lack of transparency, and theft of sensitive AI models. Existing research focuses on improving AI efficiency, while limited attention is given to governance, ethical accountability, explainability, and intellectual property protection of national-security AI systems. This paper proposes a Secure and Explainable AI Governance Framework that integrates human oversight, explainable AI, anti-manipulation security measures, and IPR protection to ensure responsible, transparent, and secure use of AI in national security operations.
KEYWORDS
Artificial Intelligence (AI) has improved national security and intelligence analysis, through things like surveillance, cyber defense, predictive threat detection, and automated monitoring systems, but you know it is not only smooth sailing. When dependence on AI increases it also brings serious problems tied to privacy violations, biased decisions, little to no transparency, adversarial attacks, and even unauthorized access to sensitive defense technologies. In this paper we propose a Secure and Explainable AI Governance Framework that kind of ties together explainable AI, human oversight, anti-manipulation security mechanisms, ethical governance, and intellectual property protection for AI-based national-security systems. The idea is that this framework helps enable transparent, accountable, and secure deployment of AI technologies, while at the same time lowering risks that come from uncontrolled or unethical AI usage in defense and intelligence operations.
[1] S. Russell and P. Norvig, Artificial Intelligence: A Modern Approach, 4th ed. Hoboken, NJ, USA: Pearson, 2021. [2] N. Bostrom, Superintelligence: Paths, Dangers, Strategies. Oxford, U.K.: Oxford University Press, 2014. [3] S. Wachter, B. Mittelstadt, and C. Russell, “Why Fairness Cannot Be Automated: Bridging the Gap Between EU Non-Discrimination Law and AI,” Computer Law & Security Review, vol. 41, 2021. [4] European Commission, “Ethics Guidelines for Trustworthy AI,” 2019. European Commission AI Ethics Guidelines [5] IEEE, “Ethically Aligned Design: A Vision for Prioritizing Human Well-being with Autonomous and Intelligent Systems,” 2019. IEEE Ethically Aligned Design [6] OpenAI, “GPT-4 System Card,” 2023. OpenAI GPT-4 System Card [7] A. Doshi-Velez and B. Kim, “Towards a Rigorous Science of Interpretable Machine Learning,” arXiv preprint arXiv:1702.08608, 2017. [8] D. Gunning, “Explainable Artificial Intelligence (XAI),” Defense Advanced Research Projects Agency (DARPA), 2017. DARPA XAI Program [9] B. Schneier, Data and Goliath: The Hidden Battles to Collect Your Data and Control Your World. New York, NY, USA: W. W. Norton & Company, 2015. [10] P. W. Singer and A. Brooking, LikeWar: The Weaponization of Social Media. Boston, MA, USA: Houghton Mifflin Harcourt, 2018.
Publication Date
6/1/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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No funding information available for this research.
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