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Challenges of Verifying the Video Call Authenticity in Remote Investment Negotiations

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Remote Investment Transactions in the Digital Age

Abstract

The purpose of the study is to analyze threats to image authentication and identity verification that refers to online communication by video calls between several participants of remote digital investment transactions. While there is a strong focus on hacking and identity theft, challenges of videocall falsification via deep fakes in digital sphere is poorly examined. This article discusses the current problems of detecting the deep fake fraud in remote investment negotiations. The authors substantiate the proposals aimed at strengthening security of online communication and video-messaging in remote investing to escape risks that the deep fake technology promotes. Using the criminalistic methodology of scientific research the authors trace the signs of artificial synthesis of voice and image having been produced with deep fake technology. Determined on the comparative analysis, an overview of techniques for generating and detecting specific defects (artefacts) in audio and video indicating forgery is proposed. The analysis shows the need to make proposals aimed at improving the legal regulation of deep fake technologies preventing their abuse for the purpose of fraud in the field of remote investment including criminal penalties for substituting a person's voice or image. Result is based on the conducted research; the opinion is justified that comprehensive competence of a private investor in remote negotiating is the key to overcome the risk of being deceived with the use of temped voice or image in video online communication (call or messaging) in the investment environment of the Internet.

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Correspondence to Elena I. Galyashina .

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Galyashina, E.I., Kruchinina, N.V., Solovyeva, N.A. (2024). Challenges of Verifying the Video Call Authenticity in Remote Investment Negotiations. In: Inshakova, A., Matytsin, D., Inshakova, E. (eds) Remote Investment Transactions in the Digital Age. Intelligent Systems Reference Library, vol 250. Springer, Cham. https://doi.org/10.1007/978-3-031-51536-1_26

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