employee from 01.01.2022 until now
Moscow, Moscow, Russian Federation
UDC 343.9
Introduction. The article is dedicated to the actual problem of remote fraud in the context of digital transformation of society, with a particular focus on the use of artificial intelligence (AI) by criminals. Methods. The author carried out a comprehensive victimological analysis of modern fraud schemes based on deep learning technologies, text generation, and audio and video forgeries (deepfakes). Results. The author emphasises that the accessibility and development of AI technologies significantly increase the possibilities for fraudsters to create personalised attacks and automated social engineering schemes. The victimological consequences of such a phenomenon are considered, including the increased vulnerability of broad segments of the population and the reduced effectiveness of traditional protective measures. The research is based on foreign scientific traditions reflecting advanced approaches to understanding the social and technical aspects of digital victimisation. Key areas for counteracting fraud are identified, including the development of anti-fraud systems, multi-level authentication, integration of educational materials into popular online platforms, and improvement of international legal regulation. Conclusions. The author concludes that in order to effectively reduce victimisation in the context of AI use, a comprehensive approach integrating technological innovation, increased digital literacy and development of legal protection mechanisms is required.
remote fraud, artificial intelligence, victimological analysis, digital victimisation, deepfake, social engineering, anti-fraud systems, machine learning, personalised attacks, digital security, international cooperation, cybercrime
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