National Identity Management and National Security in Nigeria in the Era of Artificial Intelligence: The Imperative of AI-Driven Joint National Identity Database

This paper examines national identity management and national security in Nigeria in the era of Artificial Intelligence, with a special focus on the need for an AI-driven joint national identity database for a holistic and robust identity management towards ensuring security and strengthening national security in the era of terrorism and banditry. The paper adopts the Information Systems Success Model as its theoretical framework. The model developed by William H. DeLone and Ephraim R. McLean is a foundational framework in information systems research. The paper argued that creating a joint database of all hitherto existing national identity data will ensure holistic, more effective and efficient national identity management that will promote national security and enhance all efforts at tackling insecurity in the country. The paper recommended a joint national identity database domiciled in the office of the National Security Adviser, and a mandatory transfer of all old and new identity data to the created database. The paper concluded that national identity management plays an important role in national security in Nigeria and that the creation of an AI-driven joint identity database is a right and important step towards strengthening national security in Nigeria. Keywords: national identity, national identity management, security, national security, artificial intelligence and joint database. Proceedings Citation Format Akande, A.T., Akande, J., Ozomata, B.U., & Edibo, D.M. (2024): National Identity Management and National Security in Nigeria in the Era of Artificial Intelligence: The Imperative of AI-Driven Joint National Identity Database. Proceedings of the Cyber Secure Nigeria Conference held at The Ballroom Center, Central Business District, Federal Capital Territory, Abuja, Nigeria - 25th - 26th September, 2024. Pp 151-164. cybersecurenigeria.org dx.doi.org