A Complex Adaptive Systems Framework for Modelling Cybercrime Ecosystem Dynamics in Nigeria Using Agent-Based Simulation

Nigeria's cybercrime ecosystem exhibits complex adaptive system properties including feedback loops, emergent criminal specialisation, and adaptive responses to enforcement, and developing a theoretical framework grounded in complex systems science offers superior explanatory power over static criminological models. This study developed a complex adaptive systems framework for modelling cybercrime ecosystem dynamics in Nigeria. A multi-method complexity science methodology was employed: systematic review of complex systems approaches to cybercrime (44 publications from 2018 to 2024), empirical characterisation of the Nigerian cybercrime ecosystem through EFCC case data analysis and structured interviews with 20 cybercrime investigators and researchers, agent-based model design and simulation, and expert validation. The agent-based model specified four agent types: criminal actors, potential victims, law enforcement, and platform intermediaries, each with defined behavioural rules and adaptation capabilities. Simulation scenarios tested intervention effects including enforcement intensity, consumer awareness, platform regulation, and legitimate economic opportunity expansion. The simulation confirmed that enforcement-only interventions produced short-term crime reduction followed by evolutionary adaptation to enforcement patterns, consistent with empirical observation. Consumer awareness campaigns showed superlinear effects above a critical adoption threshold. Legitimate opportunity provision showed the strongest long-term crime reduction effect but operated on longer time scales. The original Complex Adaptive Systems Framework for Nigerian Cybercrime provides three leverage point categories for policy. Expert review by 18 complex systems and cybercrime specialists confirmed the model's theoretical and methodological originality.

Keywords: complex adaptive systems, cybercrime, agent-based model, Nigeria, simulation