Deepfake awareness and privacy protective behaviours: evidence from Vietnamese young faceswap apps users

Purpose Deepfakes are synthetic media (audio recordings, videos or photos) created using artificial intelligence. In recent years, deepfakes have become an increasing concern for internet users; therefore, protecting oneself from cybercrime attacks is vital. The purpose of this study is to use the Technology Acceptance Model and Protection Motivation Theory to build a serial mediation model of the relation between deepfake awareness, perceived security and privacy risks, perceived usefulness, ease of use and online protection behaviors. Design/methodology/approach Based on a survey of 321 faceswap app users, an analysis was performed using the structural equation modeling method. Findings The results reveal that although deepfake awareness does not directly affect online protection behavior, it indirectly increases online protection behavior through perceived privacy risk, security risk, perceived usefulness and perceived ease of use of the behaviors. In addition, perceived risks significantly increase online protection behavior by having a higher perceived usefulness of online protection behavior. Practical implications The theoretical and managerial implications of this study are discussed in this paper to gain benefits and manage the potential threats from this new technology. Originality/value This study enriches the cybersecurity literature by evaluating the serial mediating effect of security, privacy risks and perceived usefulness on the relationship between internet users’ deepfake awareness and their online self-protective behaviors.