Enhancing Identity Protection in Metaverse-Based Psychological Counseling System

Non-face-to-face psychological counseling systems rely on network technologies to anonymize information regard-ing client identity.However,these systems often face challenges concerning voice data leaks and the suboptimal communication of the client’s non-verbal expressions,such as facial cues,to the counselor.This study proposes a metaverse-based psychological counseling system designed to enhance client identity protection while ensuring efficient information delivery to counselors during non-face-to-face counseling.The proposed systemincorporates a voicemodulation function that instantlymodifies/masks the client’s voice to safeguard their identity.Additionally,it employs real-time client facial expression recognition using an ensemble of decision trees to mirror the client’s non-verbal expressions through their avatar in the metaverse environment.The system is adaptable for use on personal computers and smartphones,offering users the flexibility to access metaverse-based psychological counseling across diverse environments.The performance evaluation of the proposed system confirmed that the voice modulation and real-time facial expression replication consistently achieve an average speed of 48.32 frames per second or higher,even when tested on the least powerful smartphone configurations.Moreover,a total of 550 actual psychological counseling sessions were conducted,and the average satisfaction rating reached 4.46 on a 5-point scale.This indicates that clients experienced improved identity protection compared to conventional non-face-to-face metaverse counseling approaches.Additionally,the counselor successfully addressed the challenge of conveying non-verbal cues from clients who typically struggled with non-face-to-face psychological counseling.The proposed systemholds significant potential for applications in interactive discussions and educational activities in the metaverse.

A Private User Data Protection Mechanism in TrustZone Architecture Based on Identity Authentication

In Trust Zone architecture, the Trusted Application（TA） in the secure world does not certify the identity of Client Applications（CA） in the normal world that request data access, which represents a user data leakage risk. This paper proposes a private user data protection mechanism in Trust Zone to avoid such risks. We add corresponding modules to both the secure world and the normal world and authenticate the identity of CA to prevent illegal access to private user data. Then we analyze the system security, and perform validity and performance tests.The results show that this method can perform effective identity recognition and control of CA to protect the security of private user data. After adding authentication modules, the data operation time of system increases by about0.16 s, an acceptable price to pay for the improved security.