Metaverse, as an evolving paradigm of the next-generation Internet, aims to build a fully immersive, hyper spatiotemporal, and self-sustaining virtual shared space for humans to play, work, and socialize. Driven by recent advances in emerging technologies such as extended reality, artificial intelligence, and blockchain, metaverse is stepping from science fiction to an upcoming reality. However, severe privacy invasions and security breaches (inherited from underlying technologies or emerged in the new digital ecology) of metaverse can impede its wide deployment. At the same time, a series of fundamental challenges (e.g., scalability and interoperability) can arise in metaverse security provisioning owing to the intrinsic characteristics of metaverse, such as immersive realism, hyper spatiotemporality, sustainability, and heterogeneity. In this paper, we present a comprehensive survey of the fundamentals, security, and privacy of metaverse. Specifically, we first investigate a novel distributed metaverse architecture and its key characteristics with ternary-world interactions. Then, we discuss the security and privacy threats, present the critical challenges of metaverse systems, and review the state-of-the-art countermeasures. Finally, we draw open research directions for building future metaverse systems.
Canadian Institute for Cybersecurity, University of New Brunswick（加拿大网络安全研究所，新不伦瑞克大学）；Cheriton School of Computer Science, University of Waterloo（切里顿计算机科学学院，滑铁卢大学）
When VR Meets BCI: (Un)Observable Brainwave-aware Privacy Reconstruction in the Metaverse via Unrestricted Inbuilt Motion Sensors
King Abdullah University of Science and Technology（阿卜杜拉国王科技大学）；National University of Singapore（新加坡国立大学）；City University of Hong Kong（香港城市大学）；Feng Chia University（逢甲大学）；Information Security Research Center, Hon Hai Research Institute（鸿海研究院信息安全研究中心）
Adversarial Attacks and Defenses for Semantic Communication in Vehicular Metaverses
Guangdong University of Technology（广东工业大学）；Nanyang Technological University（南洋理工大学）；Zhejiang University（浙江大学）；Zhejiang Laboratory（之江实验室）；Singapore University of Technology and Design（新加坡科技设计大学）
MetaFed: Advancing Privacy, Performance, and Sustainability in Federated Metaverse Systems
Department of Computer Engineering（计算机工程系）；Faculty of Engineering（工程学院）；Kırıkkale University（Kirikkkale 大学）；Natural Sciences, Sabancı University（自然科学，萨班奇大学）
Blockchain-based Pseudonym Management for Vehicle Twin Migrations in Vehicular Edge Metaverse
School of Automation, Guangdong University of Technology（广东工业大学自动化学院）；School of Computer Science and Engineering, Nanyang Technological University（南洋理工大学计算机科学与工程学院）；School of Electronic Science and Engineering, Nanjing University（南京大学电子科学与工程学院）；Department of Electrical and Computer Engineering, Auburn University（奥本大学电气与计算机工程系）
Cross-reality location privacy protection in 6G-enabled vehicular metaverses: an LLM-enhanced hybrid generative diffusion model-based approach
School of Automation, Guangdong University of Technology（自动化学院，广东技术大学）；School of Computer Science and Engineering, Nanyang Technological University（计算机科学与工程学院，南洋理工大学）；Department of Electrical and Computer Engineering, University of Manitoba（电气与计算机工程系，曼尼托巴大学）；Department of Electrical and Computer Engineering, Sungkyunkwan University（电气与计算机工程系，成均馆大学）
Secure and Trustworthy Artificial Intelligence-Extended Reality (AI-XR) for Metaverses
James Watt School of Engineering, University of Glasgow（格拉斯哥大学詹姆斯·瓦特工程学院）；Information Technology University (ITU)（信息技术大学）；Glasgow Caledonian University（格拉斯哥卡里多尼亚大学）；Qatar University（卡塔尔大学）；Hamad Bin Khalifa University（哈马德·本·哈利法大学）
MetaTrading: An Immersion-Aware Model Trading Framework for Vehicular Metaverse Services
Department of Mathematics and Information Technology, The Education University of Hong Kong（香港教育大学数学与信息技术系）；Pillar of Information Systems Technology and Design, Singapore University of Technology and Design（新加坡科技设计大学信息系统技术与设计学院）；School of Automation, Guangdong University of Technology（广东技术大学自动化学院）；College of Computer Science and Technology, National University of Defense Technology（国防科技大学计算机科学与技术学院）；College of Computing and Data Science, Nanyang Technological University（南洋理工大学计算与数据科学学院）；Department of Computer Science and Engineering, Kyung Hee University（韩国成均馆大学计算机科学与工程系）
Security and Privacy in Big Data Sharing: State-of-the-Art and Research Directions
大数据共享（Big Data Sharing，BDS）是指数据所有者共享数据，使用户能够根据协议查找、访问和使用数据的行为。近年来，由于其广泛的应用，例如大数据交易和跨域数据分析，BDS已经成为一个新兴的话题。然而，由于BDS平台涉及多方，因此出现了安全和隐私侵犯问题。已经有许多解决方案用于在不同的大数据操作中增强安全性和保护隐私（例如，数据操作、数据检索、数据共享和数据外包）。据我们所知，目前还没有专门针对这些安全和隐私解决方案的广泛和系统性发展的调查。在这项研究中，我们对为解决BDS中的安全和隐私问题而引入的最先进的解决方案进行了全面调查。为了更好地理解，我们首先介绍了BDS的一般模型，并确定了安全和隐私要求。我们根据确定的要求讨论和分类最先进的BDS安全和隐私解决方案。最后，基于所获得的见解，我们提出并讨论了新的有前途的研究方向。
