Artificial Intelligence-Based Cybersecurity for the Metaverse: Research Challenges and Opportunities

被引:9
作者
Awadallah, Abeer [1 ]
Eledlebi, Khouloud [1 ]
Zemerly, Mohamed Jamal [1 ]
Puthal, Deepak [2 ]
Damiani, Ernesto [1 ]
Taha, Kamal [1 ]
Kim, Tae-Yeon [3 ]
Yoo, Paul D. [4 ]
Choo, Kim-Kwang Raymond [5 ]
Yim, Man-Sung [6 ]
Yeun, Chan Yeob [1 ]
机构
[1] Khalifa Univ, Dept Elect Engn & Comp Sci, Abu Dhabi, U Arab Emirates
[2] Indian Inst Management Bodh Gaya, IT Syst & Analyt, Bodh Gaya 824234, India
[3] Khalifa Univ, Civil & Environm Engn Dept, Abu Dhabi, U Arab Emirates
[4] Univ London, Dept Comp Sci & Informat Syst, London, England
[5] Univ Texas San Antonio, Dept Informat Syst & Cyber Secur, San Antonio, TX 78249 USA
[6] Korea Adv Inst Sci & Technol, Dept Nucl & Quantum Engn, Daejeon, South Korea
关键词
Metaverse; Computer security; Artificial intelligence; Surveys; Security; Reviews; Privacy; biometrics; continuous authentication; cybersecurity; digital twins; intrusion detection; metaverse; multimodality; NFTs; BIOMETRIC AUTHENTICATION; BLOCKCHAIN TECHNOLOGIES; INTRUSION DETECTION; ECG AUTHENTICATION; HEALTH-CARE; SECURITY; INTERNET; ISSUES; FRAMEWORK; SYSTEMS;
D O I
10.1109/COMST.2024.3442475
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The metaverse, known as the next-generation 3D Internet, represents virtual environments that mirror the physical world. It is supported by innovative technologies such as digital twins and extended reality (XR), which elevate user experiences across various fields. However, the metaverse also introduces significant cybersecurity and privacy challenges that remain underexplored. Due to its complex multi-tech infrastructure, the metaverse requires sophisticated, automated, and intelligent cybersecurity measures to mitigate emerging threats effectively. Therefore, this paper is the first to explore Artificial Intelligence (AI)-driven cybersecurity techniques for the metaverse, examining academic and industrial perspectives. First, we provide an overview of the metaverse, presenting a detailed system model, diverse use cases, and insights into its current industrial status. We then present attack models and cybersecurity threats derived from the unique characteristics and technologies of the metaverse. Next, we review AI-driven cybersecurity solutions based on three critical aspects: User authentication, intrusion detection systems (IDS), and the security of digital assets, specifically for Blockchain and Non-fungible Tokens (NFTs). Finally, we highlight challenges and suggest future research opportunities to enhance metaverse security, privacy, and digital asset transactions.
引用
收藏
页码:1008 / 1052
页数:45
相关论文
共 287 条
[1]   Multimodal biometric authentication based on deep fusion of electrocardiogram (ECG) and finger vein [J].
Abd El-Rahiem, Basma ;
Abd El-Samie, Fathi E. ;
Amin, Mohamed .
MULTIMEDIA SYSTEMS, 2022, 28 (04) :1325-1337
[2]  
Abdallah E.E., 2022, Procedia Computer Science, V201, P205, DOI [10.1016/j.procs.2022.03.029, DOI 10.1016/J.PROCS.2022.03.029]
[3]   Cyber-security and reinforcement learning - A brief survey [J].
Adawadkar, Amrin Maria Khan ;
Kulkarni, Nilima .
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2022, 114
[4]  
adobe, Metaverses and other shared immersive experiences
[5]   An Intelligent Multimodal Biometric Authentication Model for Personalised Healthcare Services [J].
Ahamed, Farhad ;
Farid, Farnaz ;
Suleiman, Basem ;
Jan, Zohaib ;
Wahsheh, Luay A. ;
Shahrestani, Seyed .
FUTURE INTERNET, 2022, 14 (08)
[6]   Zero-day attack detection: a systematic literature review [J].
Ahmad, Rasheed ;
Alsmadi, Izzat ;
Alhamdani, Wasim ;
Tawalbeh, Lo'ai .
ARTIFICIAL INTELLIGENCE REVIEW, 2023, 56 (10) :10733-10811
[7]   A Survey on Physiological Signal-Based Emotion Recognition [J].
Ahmad, Zeeshan ;
Khan, Naimul .
BIOENGINEERING-BASEL, 2022, 9 (11)
[8]   Network intrusion detection system: A systematic study of machine learning and deep learning approaches [J].
Ahmad, Zeeshan ;
Shahid Khan, Adnan ;
Wai Shiang, Cheah ;
Abdullah, Johari ;
Ahmad, Farhan .
TRANSACTIONS ON EMERGING TELECOMMUNICATIONS TECHNOLOGIES, 2021, 32 (01)
[9]  
Ahmed Fazal A., 2023, Int. J. Electron. Crime Invest., V7, P1, DOI [10.54692/ijeci.2023.0702155, DOI 10.54692/IJECI.2023.0702155]
[10]   A Critical Survey of EEG-Based BCI Systems for Applications in Industrial Internet of Things [J].
Ajmeria, Rahul ;
Mondal, Mayukh ;
Banerjee, Reya ;
Halder, Tamesh ;
Deb, Pallav Kumar ;
Mishra, Debasish ;
Nayak, Pravanjan ;
Misra, Sudip ;
Pal, Surjya Kanta ;
Chakravarty, Debashish .
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS, 2023, 25 (01) :184-212