Security and Privacy in Metaverse: A Comprehensive Survey

IF 7.7 1区计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Big Data Mining and Analytics Pub Date : 2023-01-26 DOI:10.26599/BDMA.2022.9020047

Yan Huang;Yi Joy Li;Zhipeng Cai

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引用次数: 28

Abstract

Metaverse describes a new shape of cyberspace and has become a hot-trending word since 2021. There are many explanations about what Meterverse is and attempts to provide a formal standard or definition of Metaverse. However, these definitions could hardly reach universal acceptance. Rather than providing a formal definition of the Metaverse, we list four must-have characteristics of the Metaverse: socialization, immersive interaction, real world-building, and expandability. These characteristics not only carve the Metaverse into a novel and fantastic digital world, but also make it suffer from all security/privacy risks, such as personal information leakage, eavesdropping, unauthorized access, phishing, data injection, broken authentication, insecure design, and more. This paper first introduces the four characteristics, then the current progress and typical applications of the Metaverse are surveyed and categorized into four economic sectors. Based on the four characteristics and the findings of the current progress, the security and privacy issues in the Metaverse are investigated. We then identify and discuss more potential critical security and privacy issues that can be caused by combining the four characteristics. Lastly, the paper also raises some other concerns regarding society and humanity.

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Metaverse中的安全与隐私：综述

元宇宙描述了一种新的网络空间形态，自2021年以来已成为热门词汇。关于Meterverse是什么，有很多解释，并试图提供元宇宙的正式标准或定义。然而，这些定义很难得到普遍接受。我们没有提供元宇宙的正式定义，而是列出了元宇宙的四个必备特征：社交化、沉浸式互动、现实世界构建和可扩展性。这些特征不仅将元宇宙塑造成一个新奇而奇妙的数字世界，还使其面临所有安全/隐私风险，如个人信息泄露、窃听、未经授权访问、网络钓鱼、数据注入、身份验证失败、设计不安全等。本文首先介绍了元宇宙的四个特点，然后对元宇宙的当前进展和典型应用进行了综述，并将其分为四个经济领域。基于这四个特征和当前进展的发现，对元宇宙中的安全和隐私问题进行了研究。然后，我们确定并讨论了结合这四个特征可能导致的更多潜在的关键安全和隐私问题。最后，本文还提出了一些关于社会和人性的其他问题。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Big Data Mining and Analytics Computer Science-Computer Science Applications

CiteScore

20.90

自引率

2.20%

发文量

期刊介绍： Big Data Mining and Analytics, a publication by Tsinghua University Press, presents groundbreaking research in the field of big data research and its applications. This comprehensive book delves into the exploration and analysis of vast amounts of data from diverse sources to uncover hidden patterns, correlations, insights, and knowledge. Featuring the latest developments, research issues, and solutions, this book offers valuable insights into the world of big data. It provides a deep understanding of data mining techniques, data analytics, and their practical applications. Big Data Mining and Analytics has gained significant recognition and is indexed and abstracted in esteemed platforms such as ESCI, EI, Scopus, DBLP Computer Science, Google Scholar, INSPEC, CSCD, DOAJ, CNKI, and more. With its wealth of information and its ability to transform the way we perceive and utilize data, this book is a must-read for researchers, professionals, and anyone interested in the field of big data analytics.