Improving digital fraud prevention in Uzbekistan: evidence from 2019-2026 official statistics and the adaptive MKP-5 model

Abstract

This article examines how the system for preventing technology-enabled crime in Uzbekistan can be improved in the context of a sharp rise in threats related to cyber fraud and the theft of citizens’ funds through electronic payment instruments. According to official data, 863 technology-enabled crimes were recorded in 2019; by 2024 this figure had reached 58,800, and in 2025 cybercrimes totalled 76,852, accounting for 49.6% of all 155,002 registered crimes. The central problem of the study is the gap between the quantitative reach of prevention activities and citizens’ actual safe behaviour. Although more than 23 million people were reportedly reached by cyber-prevention awareness campaigns in the first half of 2026, international meta-analytic evidence shows that cybersecurity training affects knowledge and attitudes considerably more strongly than actual behaviour. Drawing on descriptive statistics, formal legal analysis, systems analysis and comparative analysis, the author proposes MKP-5, a five-stage adaptive model of targeted cyber prevention. The model integrates diagnosis, risk segmentation, scenario-based prevention, rapid warning and outcome measurement into a single feedback cycle. The article argues that the effectiveness of cyber prevention should be assessed not only by the number of people reached, but also by indicators of threat recognition, safe decision-making, speed of reporting, repeat victimisation and financial loss. MKP-5 is presented as a conceptual and applied model that requires pilot validation, not as an intervention whose causal effectiveness has already been demonstrated.