شناسایی موانع حریم خصوصی کاربران در محیط متاورس

Purpose: The metaverse has emerged as a widely discussed topic of public interest, with individuals and organizations alike contemplating its potential applications while being significantly concerned about privacy. User privacy in the metaverse environment includes control over personal information and data sharing, protection of digital identity, and prevention of unauthorized access to users’ personal information, among other aspects. The aim of this research is to identify the barriers to user privacy in the metaverse environment.
Methods: This research is applied in terms of purpose and survey in terms of data collection method. First, by reviewing the literature in the field of metaverse, privacy barriers in the field of metaverse were identified, and then in order to identify the most important barriers that affect the development of metaverse and that experts agree on, fuzzy Delphi techniques were used for data analysis. The statistical population of the present study consists of experts in
the fields of metaverse, privacy, law, artificial intelligence, information science, and epistemology. To determine the sample, the judgmental sampling method and the opinions of 16 experts in this field were used. To identify privacy barriers in the field of metaverse, the researchers first extracted 44 barriers to user privacy in the metaverse environment by reviewing the literature and research background, and then the experts were asked to determine the impact of the indicators based on a five-point Likert scale using a semi-structured questionnaire. To collect the opinions of the experts at the end of the six research components, an open question was written at the end and the experts were asked to state if they had any other indicators in mind that were related to the research objective in addition to the mentioned indicators. After selecting the appropriate method and defuzzifying the values, a tolerance threshold should be considered for screening the items. The threshold for confirming the components is 0.75 percent. In this study, each of the barriers to user privacy was ranked using the Cocosu method.
Findings: According to the experts, the higher the number of points given to each of the barrier components, the greater the importance of the component, and it has been confirmed. Also, using the Delphi-Fuzzy method, 26 barriers were screened and selected for the final analysis, and 3 barriers were identified based on the scores obtained. The costs of data protection, personal information leakage, and lack of interactivity of graphics and hardware were the most important, respectively. The findings showed that protecting privacy in the metaverse space has become a multifaceted challenge that requires attention to cultural, educational, and technological issues. One of the most obvious and important barriers identified in the present study is the cost of data protection. This barrier actually reflects the complexities and economic and technical challenges related to collecting, storing, processing, and transferring user data in the metaverse world. Data protection systems require advanced technology infrastructures that incur costs for implementation and maintenance. Especially in the metaverse space, where data exchange takes place extensively and in real time, the need for security systems that can effectively protect users' personal information and identity is felt more than ever. The second obstacle is related to the leakage of personal information in the metaverse environment. The leakage of personal information in the metaverse is one of the most complex and challenging security issues in today's digital world. Given the unique characteristics of this virtual space and the extensive interactions that take place in it, security threats in these environments can be much more complex and impactful than in other online spaces. The third obstacle is also related to the lack of interoperability of graphics and hardware in the metaverse environment. The lack of interoperability between graphics and hardware in the metaverse environment is one of the fundamental challenges that can directly affect the user experience and the efficiency of systems in this space. In other words, to create an efficient and scalable metaverse environment, it is necessary for developers, hardware manufacturers, and standardization bodies to cooperate to ensure the integration between graphics and hardware and to resolve existing problems.
Conclusion: Educating users about better strategies for maintaining privacy and ways to avoid security risks in the metaverse, as well as enhancing awareness of security and privacy issues, can lead to improved and responsible decision-making by users. The actions outlined in this research can help enhance users’ privacy in the metaverse environment and increase their trust in this platform. Given the growing importance of the metaverse and its impact on daily life, addressing privacy barriers and striving to overcome them appears to be essential. This research can assist policymakers, developers, and users in gaining a better understanding of the challenges present in this space and contribute to creating a safer and more private environment for metaverse users.