Fighting the Illusion: Exploring Consumer Defense Against Deepfake Technology Using Protection Motivation Theory

With an emphasis on comprehending and mitigating the adverse effects of Deepfake in the metaverse, this study seeks to create a thorough understanding of the nuances of how people protect themselves from the adverse effects of Deepfake. Drawing from Protection Motivation Theory (PMT), we propose a framework to explore protection motivation from deepfakes'. Deepfakes, acting as stressors, can trigger anxiety, fear, and selfdoubt. Studying the interplay between deepfake threats and coping mechanisms can reveal interventions for protection motivation. This can guide the development of secure measures for a safer, more enjoyable virtual experience. This empirical research relies on quantitative data collected from 291 consumers, which was analysed using structural equation modeling. Perceived Severity, Perceived Vulnerability, and Self-Efficacy, had significant influence on Protective Motivation from Deepfakes. However, Response Efficacy and Response Cost influence on protection motivation was found insignificant. This Research paper shall help Technology practitioners, Metaverse Designers, IT professionals in Improving Deepfake Detection and Mitigation, Enhancing User Awareness and Education, designing user-friendly deepfake detection tools, and Strengthening Metaverse Security and Trust. Research is essential to creating safeguards, defending marginalised populations, and guaranteeing a secure and wholesome virtual future.

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Publication Details

Published
2025-01-09
DOI
https://doi.org/10.1109/icaect63952.2025.10958930
Primary Topic
Cybercrime and Law Enforcement Studies
Type
article
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article

Fighting the Illusion: Exploring Consumer Defense Against Deepfake Technology Using Protection Motivation Theory

Dhanya Pramod, Samiran Mitra, Kanchan Patil, Shikhar Kumar Sarma et al.
Cybercrime and Law Enforcement Studies
article

Fighting the Illusion: Exploring Consumer Defense Against Deepfake Technology Using Protection Motivation Theory

Dhanya Pramod, Samiran Mitra, Kanchan Patil, Shikhar Kumar Sarma, Pranavi Sodagiri, Sudhansu Saraswat
article en

Abstract

With an emphasis on comprehending and mitigating the adverse effects of Deepfake in the metaverse, this study seeks to create a thorough understanding of the nuances of how people protect themselves from the adverse effects of Deepfake. Drawing from Protection Motivation Theory (PMT), we propose a framework to explore protection motivation from deepfakes'. Deepfakes, acting as stressors, can trigger anxiety, fear, and selfdoubt. Studying the interplay between deepfake threats and coping mechanisms can reveal interventions for protection motivation. This can guide the development of secure measures for a safer, more enjoyable virtual experience. This empirical research relies on quantitative data collected from 291 consumers, which was analysed using structural equation modeling. Perceived Severity, Perceived Vulnerability, and Self-Efficacy, had significant influence on Protective Motivation from Deepfakes. However, Response Efficacy and Response Cost influence on protection motivation was found insignificant. This Research paper shall help Technology practitioners, Metaverse Designers, IT professionals in Improving Deepfake Detection and Mitigation, Enhancing User Awareness and Education, designing user-friendly deepfake detection tools, and Strengthening Metaverse Security and Trust. Research is essential to creating safeguards, defending marginalised populations, and guaranteeing a secure and wholesome virtual future.

Symbiosis International University (IN)
Openalex Percentile: Top 90%
Cybercrime and Law Enforcement Studies
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Fighting the Illusion: Exploring Consumer Defense Against Deepfake Technology Using Protection Motivation Theory — Dhanya Pramod, Samiran Mitra, et al. · (2025) | TGRS Research Map | TGRS