Tecnologías biométricas para interoperabilidad financiera y seguridad en el metaverso

Carlos Eduardo Cobos Gutierrez

doi:10.46794/gacien.11.1.2342

Authors

Carlos Eduardo Cobos Gutierrez Escuela de Educación Superior Tecnológica IDAT, Perú

DOI:

https://doi.org/10.46794/gacien.11.1.2342

Keywords:

metaverse, identification technologies, financial compatibility, sense of security, desire to adopt

Abstract

Objective: The objective of this study was to examine of manner quantitatively how biometric technologies can improve financial interoperability in the metaverse. The impact of facial recognition and biometric authentication on security perceptions, user experience, and usage intent in virtual environments was analyzed, as well as the relationship between security perceptions and users' willingness to adopt these technologies in their financial transactions. Materials and methods: A quantitative method was used with a non-experimental, cross-sectional, and descriptive design. Surveys were applied to 150 participants, including financial technology experts and active users of the metaverse. The key variables, such as perception of security, ease of use, and adoption intention, were measured using Likert-type scales and analyzed using descriptive and inferential statistics, including correlation coefficients and reliability analysis through of the alpha of Cronbach's. Results: The results showed a significant positive correlation (r = 0.78; p < 0.001) between the perception of security and the intention to use these technologies. 92% of participants signaled improved security as their primary benefit, and 90% highlighted faster transaction times. The scales used were highly reliable (α > 0.87), demonstrating the consistency of the instruments employed. Conclusions: It is conclusion is that biometric technologies are an effective solution for improving financial interoperability in the metaverse, as a positive perception of security significantly increases adoption intention. Furthermore, the need to establish regulations and ethical standards to guarantee data privacy is highlighted. Implementing these technologies in financial institutions would not only optimize their services but also strengthen user trust and engagement in digital environments.

Downloads

Download data is not yet available.

References

Ashani, N. Z. N. (2024). Comparative analysis of deepfake image detection method using VGG16, VGG19 and RESNEt50. Journal of Advanced Research in Applied Sciences and Engineering Technology, 47(1), 16–28. https://doi.org/10.37934/araset.47.1.1628

Assiouras, I., Laserer, C., & Buhalis, D. (2024). The evolution of artificial empathy in the hospitality metaverse era. International Journal of Hospitality Management, 126, 104063. https://doi.org/10.1016/j.ijhm.2024.104063

Baghirov, E. (2024). A Comprehensive Investigation into Robust Malware Detection with Explainable AI. Cyber Security and Applications, 3, 100072. https://doi.org/10.1016/j.csa.2024.100072

Bamberger, B., Reinartz, W., & Ulaga, W. (2024). Navigating the future of B2B marketing: The transformative impact of the industrial metaverse. Journal of Business Research, 188, 115057. https://doi.org/10.1016/j.jbusres.2024.115057

Das, S., Nakshatram, S. V., Söbke, H., Hauge, J. B., & Springer, C. (2024). Towards gamification for spatial digital learning environments. Entertainment Computing. https://doi.org/10.1016/j.entcom.2024.100893

Di Paolo, F., Bettiga, D., & Lamberti, L. (2024b). Leveraging social capital for destination promotion in the metaverse: The Enoverse case. Tourism Management, 107, 105072. https://doi.org/10.1016/j.tourman.2024.105072

Fiore, U., & Palmieri, F. (2024). A distance-based network activity correlation framework for defeating anonymization overlays. Information Sciences, 690, 121559. https://doi.org/10.1016/j.ins.2024.121559

Gorman, K. R., Wrightson-Hester, A., Landman, M., & Mansell, W. (2024). How can virtual reality help to understand consciousness? A thematic analysis of students’ experiences in a novel virtual environment. Consciousness and Cognition, 127, 103792. https://doi.org/10.1016/j.concog.2024.103792

Gorur, K. (2023). Fourier Synchrosqueezing Transform-ICA-EMD Framework based EOG-Biometric Sustainable and continuous authentication via voluntary eye blinking activities. Biomimetics, 8(4), 378. https://doi.org/10.3390/biomimetics8040378

Guarino, A., Malandrino, D., Zaccagnino, R., Capo, C., & Lettieri, N. (2023). Touchscreen gestures as images. A transfer learning approach for soft biometric traits recognition. Expert Systems With Applications, 219, 119614. https://doi.org/10.1016/j.eswa.2023.119614

Kumar, A., Shankar, A., Behl, A., & Wamba, S. F. (2024). Do you believe in the metaverse NFTs? Understanding the value proposition of NFTs in the metaverse. Technological Forecasting and Social Change, 210, 123880. https://doi.org/10.1016/j.techfore.2024.123880

Lim, W. M., Bansal, S., Nangia, P., & Singh, S. (2024). The bright and dark side of metaverse marketing. Global Business and Organizational Excellence. https://doi.org/10.1002/joe.22271

Maharjan, P., Shrestha, K., Bhatta, T., Cho, H., Park, C., Salauddin, M., Rahman, M. T., Rana, S. S., Lee, S., & Park, J. Y. (2021). Keystroke Dynamics based Hybrid Nanogenerators for Biometric Authentication and Identification using Artificial Intelligence. Advanced Science, 8(15). https://doi.org/10.1002/advs.202100711

Mariana, C. D., Husodo, Z. A., Ekaputra, I. A., & Fahlevi, M. (2024). The Advancement of Digital Payment Ecosystem in Metaverse: A Literature review. Computers in Human Behavior Reports. https://doi.org/10.1016/j.chbr.2024.100570

Park, W. H., Shin, D. R., & Mutahira, H. (2024). An integrated approach to Bayesian weight regulations and multitasking learning methods for generating emotion-based content in the metaverse. Expert Systems With Applications, 259, 125197. https://doi.org/10.1016/j.eswa.2024.125197

Rahman, S. M., Chowdhury, N. H., Bowden, J. L., & Carlson, J. (2024). Metaverse platform attributes and customer experience measurement. Journal of Retailing and Consumer Services, 83, 104159. https://doi.org/10.1016/j.jretconser.2024.104159

Sánchez-Vaquerizo, J. A. (2024). Urban Digital Twins and metaverses towards city multiplicities: uniting or dividing urban experiences? Ethics and Information Technology, 27(1). https://doi.org/10.1007/s10676-024-09812-3

Sazali, N., Dickson, K. Y. C., Maurice, K., Christian, F., Constantin, S., Salim, N., Ishak, I., & Ghani, S. a. C. (2024). Synthetic image data generation via rendering techniques for training AI-based Instance Segmentation. Journal of Advanced Research in Applied Sciences and Engineering Technology, 237–253. https://doi.org/10.37934/aram.53.1.237253

Seok, C. L., Song, Y. D., An, B. S., & Lee, E. C. (2023). PhotoPlethysmogram biometric authentication using a 1D Siamese network. Sensors, 23(10), 4634. https://doi.org/10.3390/s23104634

Szolin, K., Kuss, D. J., Nuyens, F. M., & Griffiths, M. D. (2024). The Proteus effect in Fallout: New Vegas: Investigating gender-conforming behaviours in videogames. Entertainment Computing, 52, 100765. https://doi.org/10.1016/j.entcom.2024.100765

Vernuccio, M., Boccalini, S., & Patrizi, M. (2024). “Being” with the brand in the metaverse: Strengthening brand anthropomorphism to foster brand love. Journal of Retailing and Consumer Services, 84, 104204. https://doi.org/10.1016/j.jretconser.2024.104204

Xiangjuan, J., Xinwei, F., Yijie, Z., Heng, Y., Xiaofeng, C., Wenfei, G., Weinan, L., & Fanglei, H. (2024). Integration and innovation of blockchain in Web3.0: current status and standardization prospects. World Wide Web, 28(1). https://doi.org/10.1007/s11280-024-01319-7

Zahoor, E. a. M. S. (2023). Biometric Encryption: Integrating artificial intelligence for robust authentication. Dandao Xuebao/Journal of Ballistics, 35(3), 25–33. https://doi.org/10.52783/dxjb.v35.121

Zhang, H., Lv, Y., Zhang, J. Z., Hollebeek, L. D., Behl, A., & Urbonavicius, S. (2024). Exploring purchase intention in metaverse retailing: Insights from an automotive platform. Journal of Retailing and Consumer Services, 82, 104144. https://doi.org/10.1016/j.jretconser.2024.104144