Comparative analysis of legal approaches to countering deepfake fraud and social engineering: the experience of the USA, the EU, and the Republic of Kazakhstan

Abstract

In the context of modern digital transformation, the rapid development of deepfake technologies leads to the emergence of new, more sophisticated forms of online fraud. Content created using Deepfake technology, especially when combined with social engineering techniques, poses a serious threat to the rights and legitimate interests of individuals, public safety, and institutions of digital trust. In this regard, the development by States of legal mechanisms to combat fraud committed with the help of deepfakes is of urgent scientific and practical importance.

This article presents a comparative legal analysis of legal approaches to countering online fraud and social engineering carried out using deepfake technologies. The study is based on the legislative practice of the United States, the European Union, and the Republic of Kazakhstan and covers key regulatory decisions in the field of criminal law regulation, digital content control, responsibility of online platforms, and personal data protection. In particular, the article analyzes specific legislative initiatives related to deepfake content in the United States, acts of the European Union aimed at regulating artificial intelligence, as well as the specifics of the current criminal and information legislation of the Republic of Kazakhstan.

In the course of the research, the methods of comparative legal, formal-logical, and system analysis were used. The scientific novelty of the article is characterized by a comprehensive consideration of the legal threats arising at the junction of deepfake and social engineering, and the development of proposals aimed at improving national legislation. The results of the study are of practical importance in improving the legal policy of the Republic of Kazakhstan in the field of digital security and the formation of effective legal mechanisms to combat online fraud.