Predictive Crime Prevention against Cybercrime

Justification and Possibilities for Developing AI-Based Software

Abstract

Aim: The study focuses on the concept of an innovative artificial intelligence (AI)-based software for predictive prevention of crime in the online space. The significant rise of cybercrime has been accompanied by an increased demand for proactive technological tools that are not only capable of detecting crimes after the fact, but also of effectively preventing them. This study addresses the complex question of whether it is possible to develop an adaptive system that can identify in real time users who have a higher risk of victimisation based on their online behaviour.

Methodology: A conceptual framework was developed using a comprehensive, interdisciplinary approach based on predictive policing and risk analysis models. The methodology is based on a comparative analysis of existing AI-based software, a SWOT analysis, research methodological principles to ensure representativeness, and a detailed study of privacy issues.

Findings: Research has shown that intelligent software can identify risk factors for online presence and provide personalized prevention recommendations based on user behaviour patterns. This could significantly promote conscious internet use and make crime prevention strategies more effective.

Value: Based on the results of the study, it is clear that AI-based predictive software can play a significant role in future law enforcement strategies. Priorities for future research directions include practical implementation, the development of a normative framework and the systematic integration of ethical aspects.