元宇宙中AIGC的安全和隐私挑战:综合调查

IF 28 1区 计算机科学 Q1 COMPUTER SCIENCE, THEORY & METHODS
Shoulong Zhang, Haomin Li, Kaiwen Sun, Hejia Chen, Yan Wang, Shuai Li
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引用次数: 0

摘要

Metaverse是一个混合环境,它集成了物理和虚拟领域。由于许多便利的技术,元宇宙已经可以进入。AIGC是构成元宇宙的基本技术之一。它对于创建人工资产和高效地呈现自然交互至关重要。然而,AIGC模型在其发展的每个阶段都会遇到安全、隐私和道德方面的外部和内部障碍。为了对风险和威胁进行深入的分析和调查,我们提出了一种新的分类系统,该系统基于三个主要因素对问题进行分类:威胁暴露的阶段、关注的特定领域和威胁的来源。此外,我们提出了具体的未解决的问题,促使对AIGC带来的风险进行进一步调查,并采取措施在Metaverse艺术创作和互动方法中抵消这些风险。这种全面的评估为AIGC在Metaverse中使用的安全措施提供了一个广泛的视角。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Security and Privacy Challenges of AIGC in Metaverse: A Comprehensive Survey
The Metaverse is a hybrid environment that integrates both physical and virtual realms. The Metaverse has been accessible due to many facilitating technologies. One of the essential technologies that contribute to the Metaverse is AIGC. It is crucial in creating artificial assets and presenting natural interactions efficiently and effectively. Nevertheless, AIGC models encounter external and internal obstacles in security, privacy, and ethics during every level of their development. To conduct a thorough analysis and investigation of risks and threats, we propose a new taxonomy system that categorizes the issues based on three primary factors: the stage of threat exposure, the specific area of the concerns, and the origin of the threats. Furthermore, we present specific unresolved questions that prompt additional investigation into the risks posed by AIGC and the steps taken to counteract them in Metaverse art creation and interactive methodologies. This thorough evaluation offers a broad perspective on the security measures AIGC uses in the Metaverse.
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来源期刊
ACM Computing Surveys
ACM Computing Surveys 工程技术-计算机:理论方法
CiteScore
33.20
自引率
0.60%
发文量
372
审稿时长
12 months
期刊介绍: ACM Computing Surveys is an academic journal that focuses on publishing surveys and tutorials on various areas of computing research and practice. The journal aims to provide comprehensive and easily understandable articles that guide readers through the literature and help them understand topics outside their specialties. In terms of impact, CSUR has a high reputation with a 2022 Impact Factor of 16.6. It is ranked 3rd out of 111 journals in the field of Computer Science Theory & Methods. ACM Computing Surveys is indexed and abstracted in various services, including AI2 Semantic Scholar, Baidu, Clarivate/ISI: JCR, CNKI, DeepDyve, DTU, EBSCO: EDS/HOST, and IET Inspec, among others.
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