An Original Investigation into the Theoretical Basis for Differential Privacy Implementation in Nigerian Government Statistical Systems

Differential privacy provides mathematically rigorous guarantees for protecting individual data while enabling statistical publication, and developing original theoretical foundations for its implementation in Nigerian government statistical systems addresses both a data protection obligation under NDPA and an international statistical standards requirement. This study conducted an original theoretical and applied investigation into differential privacy implementation for Nigerian National Bureau of Statistics data products. A methodology combining differential privacy theory, empirical utility-privacy tradeoff analysis, and institutional design research was employed. Systematic review of differential privacy implementation in national statistical offices (47 publications from 2019 to 2024) confirmed that existing implementation guidance assumed data infrastructure, analyst capacity, and regulatory environments absent in Nigerian contexts. The original DP-NBS Framework addresses four Nigeria-specific implementation challenges: handling the sparse geographic data characteristic of rural northern states, adapting epsilon budget allocation for high-sensitivity economic variables like individual income in informal economies, designing post-processing procedures for differentially private estimates of key poverty indicators, and specifying governance mechanisms for epsilon budget management under political economy pressures in state statistical offices. Empirical analysis of NBS Labor Force Survey microdata showed that epsilon values below 1.0 produced utility losses exceeding NBS publication quality standards for small area estimates, while epsilon values above 3.0 failed to protect individual privacy in sparse rural strata. The original study identifies the optimal epsilon range and adaptive allocation mechanism for Nigerian national statistics. Expert review by 16 differential privacy and statistical disclosure specialists confirmed the framework's technical and institutional originality.