A Statistical Evaluation Of Artificial Intelligent (AI) And Big Data Analytics On National Security Performance Indicators In Nigeria: A Simulation-Based Analysis
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Due to the rise in the security threats in Nigeria, adoption of advanced technological systems that is capable of improving detection accuracy, cyber resilience, and operational responsiveness becomes necessary. This paper looks into the evaluation of Artificial Intelligence (AI) and Big Data Analytics (BDA) on national security performance indicators in Nigeria. 180 paired observations was simulated to represent before AI and after AI operational performance across five key indicators; threat detection accuracy, response time, cyber-attack interceptions, false alarm rates, and a composite operational efficiency index. Following the incorporation of AI, descriptive statistics indicate considerable improvements in all indicators. Paired samples t-tests show significant gains in threat detection accuracy (t = 14.21, p < 0.001) and cyber-attack interceptions (t = 16.33, p < 0.001), as well as substantial decrease in response time (t = 11.45, p < 0.001) and false alarm rates (t = 9.72, p < 0.001). Pearson correlations reveal that the adoption of AI is strongly related to higher efficiency (r = .63, p < 0.001), while there is significant differences in efficiency across levels of AI intensity (F = 8.72, p < 0.001) based on the result of one-way ANOVA. Findings show that AI and BDA have ground breaking ability in strengthening Nigeria’s national security architecture by improving accuracy, speed, reliability, and overall operational effectiveness. This study provides empirical evidence supporting the strategic deployment of AI-enhanced systems for modern security optimization.
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