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  • Open Access


    AI-Enabled Grouping Bridgehead to Secure Penetration Topics of Metaverse

    Woo Hyun Park1, Isma Farah Siddiqui3, Nawab Muhammad Faseeh Qureshi2,*

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5609-5624, 2022, DOI:10.32604/cmc.2022.030235

    Abstract With the advent of the big data era, security issues in the context of artificial intelligence (AI) and data analysis are attracting research attention. In the metaverse, which will become a virtual asset in the future, users’ communication, movement with characters, text elements, etc., are required to integrate the real and virtual. However, they can be exposed to threats. Particularly, various hacker threats exist. For example, users’ assets are exposed through notices and mail alerts regularly sent to users by operators. In the future, hacker threats will increase mainly due to naturally anonymous texts. Therefore, it is necessary to use… More >

  • Open Access


    Enhancing the Prediction of User Satisfaction with Metaverse Service Through Machine Learning

    Seon Hong Lee1, Haein Lee1, Jang Hyun Kim2,*

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4983-4997, 2022, DOI:10.32604/cmc.2022.027943

    Abstract Metaverse is one of the main technologies in the daily lives of several people, such as education, tour systems, and mobile application services. Particularly, the number of users of mobile metaverse applications is increasing owing to the merit of accessibility everywhere. To provide an improved service, it is important to analyze online reviews that contain user satisfaction. Several previous studies have utilized traditional methods, such as the structural equation model (SEM) and technology acceptance method (TAM) for exploring user satisfaction, using limited survey data. These methods may not be appropriate for analyzing the users of mobile applications. To overcome this… More >

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