AHCI RESEARCH GROUP
Publications
Papers published in international journals,
proceedings of conferences, workshops and books.
OUR RESEARCH
Scientific Publications
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You can expand the Abstract, Links and BibTex record for each paper.
2025
AlJadaan, O.; Ibrahim, O.; Ani, N. N. Al; Jabas, A.; Alfaress, M.
Navigating Intellectual Property Rights in the Age of AI and the Metaverse Book Section
In: Studies in Systems, Decision and Control, vol. 234, pp. 219–228, Springer Science and Business Media Deutschland GmbH, 2025, ISBN: 21984182 (ISSN).
Abstract | Links | BibTeX | Tags: AI-generated content, Artificial intelligence, Authorship, Blockchain, Copyright law, Creative industries, Cross-jurisdictional issues, Digital assets, Ethical implications, Intellectual property, IP enforcement, Legal frameworks, Metaverse, Non-fungible tokens (NFTs), Ownership, Patent law, Smart contracts, Virtual goods
@incollection{aljadaan_navigating_2025,
title = {Navigating Intellectual Property Rights in the Age of AI and the Metaverse},
author = {O. AlJadaan and O. Ibrahim and N. N. Al Ani and A. Jabas and M. Alfaress},
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year = {2025},
date = {2025-01-01},
booktitle = {Studies in Systems, Decision and Control},
volume = {234},
pages = {219–228},
publisher = {Springer Science and Business Media Deutschland GmbH},
abstract = {The paper examines the challenges that Intellectual Property (IP) rights pose within artificial intelligence (AI) and further into the Metaverse, the constantly developing virtual world wherein one is allowed to create, trade, and own digital assets. The increasing development of AI-generated content and virtual environments has also challenged the traditional notion of authorship and ownership and, thus, to the existing regimes regulating IP. This paper discusses the current legal framework, case studies on AI-generated content, and IP use in Metaverse through smart contracts and blockchain technology. Moreover, this paper examines the ethics involved in such development and public policy reforms that can be implemented in the IP law relating to this evolving technology. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.},
keywords = {AI-generated content, Artificial intelligence, Authorship, Blockchain, Copyright law, Creative industries, Cross-jurisdictional issues, Digital assets, Ethical implications, Intellectual property, IP enforcement, Legal frameworks, Metaverse, Non-fungible tokens (NFTs), Ownership, Patent law, Smart contracts, Virtual goods},
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The paper examines the challenges that Intellectual Property (IP) rights pose within artificial intelligence (AI) and further into the Metaverse, the constantly developing virtual world wherein one is allowed to create, trade, and own digital assets. The increasing development of AI-generated content and virtual environments has also challenged the traditional notion of authorship and ownership and, thus, to the existing regimes regulating IP. This paper discusses the current legal framework, case studies on AI-generated content, and IP use in Metaverse through smart contracts and blockchain technology. Moreover, this paper examines the ethics involved in such development and public policy reforms that can be implemented in the IP law relating to this evolving technology. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
Islayem, R.; Musamih, A.; Salah, K.; Jayaraman, R.; Yaqoob, I.
Enhancing medical digital twins within metaverse using blockchain, NFTs and LLMs Journal Article
In: Internet of Things (The Netherlands), vol. 32, 2025, ISSN: 25426605 (ISSN).
Abstract | Links | BibTeX | Tags: Blockchain, Digital Twins, LLMs, Metaverse, NFTs
@article{islayem_enhancing_2025,
title = {Enhancing medical digital twins within metaverse using blockchain, NFTs and LLMs},
author = {R. Islayem and A. Musamih and K. Salah and R. Jayaraman and I. Yaqoob},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105006652785&doi=10.1016%2fj.iot.2025.101648&partnerID=40&md5=fe58942eabd12704a207b40c2755c2ff},
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year = {2025},
date = {2025-01-01},
journal = {Internet of Things (The Netherlands)},
volume = {32},
abstract = {Medical digital twins (MDTs) are rapidly emerging as transformative tools in healthcare. They provide virtual representations of medical devices and systems that facilitate real-time analysis and enhance decision-making. However, challenges such as secure data management, access control, and the lack of immersive and intelligent patient interactions limit their effectiveness. In this paper, we propose a solution integrating blockchain technology, Non-Fungible Tokens (NFTs), and Large Language Models (LLMs) within a metaverse environment to enhance MDT functionality. Blockchain and NFTs ensure secure ownership and access control, while the metaverse offers an engaging platform for user interaction. An LLM-powered non-player character (NPC) enables intelligent real-time user interactions and personalized insights. We develop two blockchain smart contracts for user registration, NFT ownership, and access control, and utilize decentralized InterPlanetary File System (IPFS) storage for the metaverse, MDT metadata, and interaction logs. We present the system architecture, sequence diagrams, and algorithms, along with the implementation and testing details. We conduct cost, security, and response time analyses to evaluate the smart contracts and LLM performance and compare our solution with existing approaches. We discuss practical implications, as well as challenges and limitations of the proposed solution. Finally, we explore the generalization of our system for various applications. The smart contract code and metaverse files are publicly available on GitHub. © 2025 The Authors},
keywords = {Blockchain, Digital Twins, LLMs, Metaverse, NFTs},
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Medical digital twins (MDTs) are rapidly emerging as transformative tools in healthcare. They provide virtual representations of medical devices and systems that facilitate real-time analysis and enhance decision-making. However, challenges such as secure data management, access control, and the lack of immersive and intelligent patient interactions limit their effectiveness. In this paper, we propose a solution integrating blockchain technology, Non-Fungible Tokens (NFTs), and Large Language Models (LLMs) within a metaverse environment to enhance MDT functionality. Blockchain and NFTs ensure secure ownership and access control, while the metaverse offers an engaging platform for user interaction. An LLM-powered non-player character (NPC) enables intelligent real-time user interactions and personalized insights. We develop two blockchain smart contracts for user registration, NFT ownership, and access control, and utilize decentralized InterPlanetary File System (IPFS) storage for the metaverse, MDT metadata, and interaction logs. We present the system architecture, sequence diagrams, and algorithms, along with the implementation and testing details. We conduct cost, security, and response time analyses to evaluate the smart contracts and LLM performance and compare our solution with existing approaches. We discuss practical implications, as well as challenges and limitations of the proposed solution. Finally, we explore the generalization of our system for various applications. The smart contract code and metaverse files are publicly available on GitHub. © 2025 The Authors
Aloudat, M. Z.; Aboumadi, A.; Soliman, A.; Al-Mohammed, H. A.; Al-Ali, M.; Mahgoub, A.; Barhamgi, M.; Yaacoub, E.
Metaverse Unbound: A Survey on Synergistic Integration Between Semantic Communication, 6G, and Edge Learning Journal Article
In: IEEE Access, vol. 13, pp. 58302–58350, 2025, ISSN: 21693536 (ISSN).
Abstract | Links | BibTeX | Tags: 6g wireless system, 6G wireless systems, Augmented Reality, Block-chain, Blockchain, Blockchain technology, Digital Twin Technology, Edge learning, Extended reality (XR), Language Model, Large language model, large language models (LLMs), Metaverse, Metaverses, Semantic communication, Virtual environments, Wireless systems
@article{aloudat_metaverse_2025,
title = {Metaverse Unbound: A Survey on Synergistic Integration Between Semantic Communication, 6G, and Edge Learning},
author = {M. Z. Aloudat and A. Aboumadi and A. Soliman and H. A. Al-Mohammed and M. Al-Ali and A. Mahgoub and M. Barhamgi and E. Yaacoub},
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issn = {21693536 (ISSN)},
year = {2025},
date = {2025-01-01},
journal = {IEEE Access},
volume = {13},
pages = {58302–58350},
abstract = {With a focus on edge learning, blockchain, sixth generation (6G) wireless systems, semantic communication, and large language models (LLMs), this survey paper examines the revolutionary integration of cutting-edge technologies within the metaverse. This thorough examination highlights the critical role these technologies play in improving realism and user engagement on three main levels: technical, virtual, and physical. While the virtual layer focuses on building immersive experiences, the physical layer highlights improvements to the user interface through augmented reality (AR) goggles and virtual reality (VR) headsets. Blockchain-powered technical layer enables safe, decentralized communication. The survey highlights how the metaverse has the potential to drastically change how people interact in society by exploring applications in a variety of fields, such as immersive education, remote work, and entertainment. Concerns about privacy, scalability, and interoperability are raised, highlighting the necessity of continued study to realize the full potential of the metaverse. For scholars looking to broaden the reach and significance of the metaverse in the digital age, this paper is a useful tool. © 2013 IEEE.},
keywords = {6g wireless system, 6G wireless systems, Augmented Reality, Block-chain, Blockchain, Blockchain technology, Digital Twin Technology, Edge learning, Extended reality (XR), Language Model, Large language model, large language models (LLMs), Metaverse, Metaverses, Semantic communication, Virtual environments, Wireless systems},
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With a focus on edge learning, blockchain, sixth generation (6G) wireless systems, semantic communication, and large language models (LLMs), this survey paper examines the revolutionary integration of cutting-edge technologies within the metaverse. This thorough examination highlights the critical role these technologies play in improving realism and user engagement on three main levels: technical, virtual, and physical. While the virtual layer focuses on building immersive experiences, the physical layer highlights improvements to the user interface through augmented reality (AR) goggles and virtual reality (VR) headsets. Blockchain-powered technical layer enables safe, decentralized communication. The survey highlights how the metaverse has the potential to drastically change how people interact in society by exploring applications in a variety of fields, such as immersive education, remote work, and entertainment. Concerns about privacy, scalability, and interoperability are raised, highlighting the necessity of continued study to realize the full potential of the metaverse. For scholars looking to broaden the reach and significance of the metaverse in the digital age, this paper is a useful tool. © 2013 IEEE.
Banafa, A.
Artificial intelligence in action: Real-world applications and innovations Book
River Publishers, 2025, ISBN: 978-877004619-0 (ISBN); 978-877004620-6 (ISBN).
Abstract | Links | BibTeX | Tags: 5G, Affective Computing, AGI, AI, AI alignments, AI Ethics, AI hallucinations, AI hype, AI models, Alexa, ANI, ASI, Augmented Reality, Autoencoders, Autonomic computing, Autonomous Cars, Autoregressive models, Big Data, Big Data Analytics, Bitcoin, Blockchain, C3PO, Casual AI, Causal reasoning, ChatGPT, Cloud computing, Collective AI, Compression engines, Computer vision, Conditional Automation, Convolutional neural networks (CNNs), Cryptocurrency, Cybersecurity, Deceptive AI, Deep learning, Digital transformation, Driver Assistance, Driverless Cars, Drones, Elon Musk, Entanglement, Environment and sustainability, Ethereum, Explainable AI, Facebook, Facial Recognition, Feedforward. Neural Networks, Fog Computing, Full Automation, Future of AI, General AI, Generative Adversarial Networks (GANs), Generative AI, Google, Green AI, High Automation, Hybrid Blockchain, IEEE, Industrial Internet of Things (IIoT), Internet of things (IoT), Jarvis, Java, JavaScript, Long Short-Term Memory Networks, LTE, machine learning, Microsoft, MultiModal AI, Narrow AI, Natural disasters, Natural Language Generation (NLG), Natural Language Processing (NLP), NetFlix, Network Security, Neural Networks, Nuclear, Nuclear AI, NYTimes, Objective-driven AI, Open Source, Partial Automation, PayPal, Perfect AI, Private Blockchain, Private Cloud Computing, Programming languages, Python, Quantum Communications, Quantum Computing, Quantum Cryptography, Quantum internet, Quantum Machine Learning (QML), R2D2, Reactive machines. limited memory, Recurrent Neural Networks, Responsible AI, Robots, Sci-Fi movies, Self-Aware, Semiconductorâ??s, Sensate AI, Siri, Small Data, Smart Contracts. Hybrid Cloud Computing, Smart Devices, Sovereign AI, Super AI, Superposition, TensorFlow, Theory of Mind, Thick Data, Twitter, Variational Autoencoders (VAEs), Virtual Reality, Voice user interface (VUI), Wearable computing devices (WCD), Wearable Technology, Wi-Fi, XAI, Zero-Trust Model
@book{banafa_artificial_2025,
title = {Artificial intelligence in action: Real-world applications and innovations},
author = {A. Banafa},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105000403587&partnerID=40&md5=4b0d94be48194a942b22bef63f36d3bf},
isbn = {978-877004619-0 (ISBN); 978-877004620-6 (ISBN)},
year = {2025},
date = {2025-01-01},
publisher = {River Publishers},
series = {Artificial Intelligence in Action: Real-World Applications and Innovations},
abstract = {This comprehensive book dives deep into the current landscape of AI, exploring its fundamental principles, development challenges, potential risks, and the cutting-edge breakthroughs that are propelling it forward. Artificial intelligence (AI) is rapidly transforming industries and societies worldwide through groundbreaking innovations and real-world applications. Starting with the core concepts, the book examines the various types of AI systems, generative AI models, and the complexities of machine learning. It delves into the programming languages driving AI development, data pipelines, model creation and deployment processes, while shedding light on issues like AI hallucinations and the intricate path of machine unlearning. The book then showcases the remarkable real-world applications of AI across diverse domains. From preventing job displacement and promoting environmental sustainability, to enhancing disaster response, drone technology, and even nuclear energy innovation, it highlights how AI is tackling complex challenges and driving positive change. The book also explores the double-edged nature of AI, recognizing its tremendous potential while cautioning about the risks of misuse, unintended consequences, and the urgent need for responsible development practices. It examines the intersection of AI and fields like operating system design, warfare, and semiconductor technology, underscoring the wide-ranging implications of this transformative force. As the quest for artificial general intelligence (AGI) and superintelligent AI systems intensifies, the book delves into cutting-edge research, emerging trends, and the pursuit of multimodal, explainable, and causally aware AI systems. It explores the symbiotic relationship between AI and human creativity, the rise of user-friendly "casual AI," and the potential of AI to tackle open-ended tasks. This is an essential guide for understanding the profound impact of AI on our world today and its potential to shape our future. From the frontiers of innovation to the challenges of responsible development, this book offers a comprehensive and insightful exploration of the remarkable real-world applications and innovations driving the AI revolution. © 2025 River Publishers. All rights reserved.},
keywords = {5G, Affective Computing, AGI, AI, AI alignments, AI Ethics, AI hallucinations, AI hype, AI models, Alexa, ANI, ASI, Augmented Reality, Autoencoders, Autonomic computing, Autonomous Cars, Autoregressive models, Big Data, Big Data Analytics, Bitcoin, Blockchain, C3PO, Casual AI, Causal reasoning, ChatGPT, Cloud computing, Collective AI, Compression engines, Computer vision, Conditional Automation, Convolutional neural networks (CNNs), Cryptocurrency, Cybersecurity, Deceptive AI, Deep learning, Digital transformation, Driver Assistance, Driverless Cars, Drones, Elon Musk, Entanglement, Environment and sustainability, Ethereum, Explainable AI, Facebook, Facial Recognition, Feedforward. Neural Networks, Fog Computing, Full Automation, Future of AI, General AI, Generative Adversarial Networks (GANs), Generative AI, Google, Green AI, High Automation, Hybrid Blockchain, IEEE, Industrial Internet of Things (IIoT), Internet of things (IoT), Jarvis, Java, JavaScript, Long Short-Term Memory Networks, LTE, machine learning, Microsoft, MultiModal AI, Narrow AI, Natural disasters, Natural Language Generation (NLG), Natural Language Processing (NLP), NetFlix, Network Security, Neural Networks, Nuclear, Nuclear AI, NYTimes, Objective-driven AI, Open Source, Partial Automation, PayPal, Perfect AI, Private Blockchain, Private Cloud Computing, Programming languages, Python, Quantum Communications, Quantum Computing, Quantum Cryptography, Quantum internet, Quantum Machine Learning (QML), R2D2, Reactive machines. limited memory, Recurrent Neural Networks, Responsible AI, Robots, Sci-Fi movies, Self-Aware, Semiconductorâ??s, Sensate AI, Siri, Small Data, Smart Contracts. Hybrid Cloud Computing, Smart Devices, Sovereign AI, Super AI, Superposition, TensorFlow, Theory of Mind, Thick Data, Twitter, Variational Autoencoders (VAEs), Virtual Reality, Voice user interface (VUI), Wearable computing devices (WCD), Wearable Technology, Wi-Fi, XAI, Zero-Trust Model},
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This comprehensive book dives deep into the current landscape of AI, exploring its fundamental principles, development challenges, potential risks, and the cutting-edge breakthroughs that are propelling it forward. Artificial intelligence (AI) is rapidly transforming industries and societies worldwide through groundbreaking innovations and real-world applications. Starting with the core concepts, the book examines the various types of AI systems, generative AI models, and the complexities of machine learning. It delves into the programming languages driving AI development, data pipelines, model creation and deployment processes, while shedding light on issues like AI hallucinations and the intricate path of machine unlearning. The book then showcases the remarkable real-world applications of AI across diverse domains. From preventing job displacement and promoting environmental sustainability, to enhancing disaster response, drone technology, and even nuclear energy innovation, it highlights how AI is tackling complex challenges and driving positive change. The book also explores the double-edged nature of AI, recognizing its tremendous potential while cautioning about the risks of misuse, unintended consequences, and the urgent need for responsible development practices. It examines the intersection of AI and fields like operating system design, warfare, and semiconductor technology, underscoring the wide-ranging implications of this transformative force. As the quest for artificial general intelligence (AGI) and superintelligent AI systems intensifies, the book delves into cutting-edge research, emerging trends, and the pursuit of multimodal, explainable, and causally aware AI systems. It explores the symbiotic relationship between AI and human creativity, the rise of user-friendly "casual AI," and the potential of AI to tackle open-ended tasks. This is an essential guide for understanding the profound impact of AI on our world today and its potential to shape our future. From the frontiers of innovation to the challenges of responsible development, this book offers a comprehensive and insightful exploration of the remarkable real-world applications and innovations driving the AI revolution. © 2025 River Publishers. All rights reserved.
2024
Truong, V. T.; Le, H. D.; Le, L. B.
Trust-Free Blockchain Framework for AI-Generated Content Trading and Management in Metaverse Journal Article
In: IEEE Access, vol. 12, pp. 41815–41828, 2024, ISSN: 21693536 (ISSN).
Abstract | Links | BibTeX | Tags: AI-generated content, AI-generated content (AIGC), Artificial intelligence, Asset management, Assets management, Block-chain, Blockchain, Commerce, Content distribution networks, Cyber-attacks, Decentralised, Decentralized application, Digital asset management, Digital system, Generative AI, Metaverse, Metaverses, Plagiarism, Security, Trustless service, Virtual Reality
@article{truong_trust-free_2024,
title = {Trust-Free Blockchain Framework for AI-Generated Content Trading and Management in Metaverse},
author = {V. T. Truong and H. D. Le and L. B. Le},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85188472793&doi=10.1109%2fACCESS.2024.3376509&partnerID=40&md5=301939c1faef0c5a7b56d9feadce27ee},
doi = {10.1109/ACCESS.2024.3376509},
issn = {21693536 (ISSN)},
year = {2024},
date = {2024-01-01},
journal = {IEEE Access},
volume = {12},
pages = {41815–41828},
abstract = {The rapid development of the metaverse and generative Artificial Intelligence (GAI) has led to the emergence of AI-Generated Content (AIGC). Unlike real-world products, AIGCs are represented as digital files, thus vulnerable to plagiarism and leakage on the Internet. In addition, the trading of AIGCs in the virtual world is prone to various trust issues between the involved participants. For example, some customers may try to avoid the payment after receiving the desired AIGC products, or the content sellers refuse to grant the products after obtaining the license fee. Existing digital asset management (DAM) systems often rely on a trusted third-party authority to mitigate these issues. However, this might lead to centralization problems such as the single-point-of-failure (SPoF) when the third parties are under attacks or being malicious. In this paper, we propose MetaTrade, a blockchain-empowered DAM framework that is designed to tackle these urgent trust issues, offering secured AIGC trading and management in the trustless metaverse environment. MetaTrade eliminates the role of the trusted third party, without requiring trust assumptions among participants. Numerical results show that MetaTrade offers higher performance and lower trading cost compared to existing platforms, while security analysis reveals that the framework is resilient against plagiarism, SPoF, and trust-related attacks. To showcase the feasibility of the design, a decentralized application (DApp) has been built on top of MetaTrade as a marketplace for metaverse AIGCs. © 2013 IEEE.},
keywords = {AI-generated content, AI-generated content (AIGC), Artificial intelligence, Asset management, Assets management, Block-chain, Blockchain, Commerce, Content distribution networks, Cyber-attacks, Decentralised, Decentralized application, Digital asset management, Digital system, Generative AI, Metaverse, Metaverses, Plagiarism, Security, Trustless service, Virtual Reality},
pubstate = {published},
tppubtype = {article}
}
The rapid development of the metaverse and generative Artificial Intelligence (GAI) has led to the emergence of AI-Generated Content (AIGC). Unlike real-world products, AIGCs are represented as digital files, thus vulnerable to plagiarism and leakage on the Internet. In addition, the trading of AIGCs in the virtual world is prone to various trust issues between the involved participants. For example, some customers may try to avoid the payment after receiving the desired AIGC products, or the content sellers refuse to grant the products after obtaining the license fee. Existing digital asset management (DAM) systems often rely on a trusted third-party authority to mitigate these issues. However, this might lead to centralization problems such as the single-point-of-failure (SPoF) when the third parties are under attacks or being malicious. In this paper, we propose MetaTrade, a blockchain-empowered DAM framework that is designed to tackle these urgent trust issues, offering secured AIGC trading and management in the trustless metaverse environment. MetaTrade eliminates the role of the trusted third party, without requiring trust assumptions among participants. Numerical results show that MetaTrade offers higher performance and lower trading cost compared to existing platforms, while security analysis reveals that the framework is resilient against plagiarism, SPoF, and trust-related attacks. To showcase the feasibility of the design, a decentralized application (DApp) has been built on top of MetaTrade as a marketplace for metaverse AIGCs. © 2013 IEEE.
Cigliano, A.; Fallucchi, F.; Gerardi, M.
An Analysis of the State of Art of the Metaverse and Its Disruptive Impact on Services Proceedings Article
In: R., Fazzolari; A.A., Jaber; C., Randieri (Ed.): CEUR Workshop Proc., pp. 38–46, CEUR-WS, 2024, ISBN: 16130073 (ISSN).
Abstract | Links | BibTeX | Tags: AI: Artificial Intelligence, Artificial intelligence: artificial intelligence, Block-chain, Blockchain, DH: Digital Humanity, Digital humanities, Digital twin: digital twin, DT: Digital Twin, Economic and social effects, ER: Extended Reality, Extended reality: extended reality, GenI: Generative Artificial Intelligence, IoT, Language Model, LLM: Large Language Model, Metaverse, Metaverses, Natural language model, Nft, NLP: Natural Language Model, Quantum Computing, Virtual environments, VR: Virtual Reality
@inproceedings{cigliano_analysis_2024,
title = {An Analysis of the State of Art of the Metaverse and Its Disruptive Impact on Services},
author = {A. Cigliano and F. Fallucchi and M. Gerardi},
editor = {Fazzolari R. and Jaber A.A. and Randieri C.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85213681173&partnerID=40&md5=cf59e812c4d5bdc51c9daae3eb7c0406},
isbn = {16130073 (ISSN)},
year = {2024},
date = {2024-01-01},
booktitle = {CEUR Workshop Proc.},
volume = {3869},
pages = {38–46},
publisher = {CEUR-WS},
abstract = {The metaverse is a virtual environment where individuals may connect with one another, partake in a variety of activities, and access digital content. It coexists with the real world and it has the potential to significantly affect daily life as well as a variety of services and applications as it develops. To understand the importance of the impacts of the metaverse in today’s society, just think of the disruptive technologies that enable it: Artificial Intelligence (AI), Extended Reality (ER), IoT, Digital Twin (DT) and Blockchain/NFT all with assistance with the availability of large, rich and structured/unstructured dataset and advanced computational models. Metaverse is cadidated (and not only) to redefine everyday life, designing activities and services/products provisioning towards increasing efficiencies, money saving and quality performance, with a big impact in everyone and helping the design and testing of next generation of internet. However, there still remain not only technical and interoperability issues but above all ethical, human, social, and cultural concerns as to the metaverse’s influence upon its prospective scope in reconstructing the quality of urban life. This paper undertakes an upper-level scientific literature review of the area of the metaverse from a broader perspective. Further, it maps the some services and the relative requirements for declinate the enabling technologies of the metaverse, and explores their contributions. © 2024 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).},
keywords = {AI: Artificial Intelligence, Artificial intelligence: artificial intelligence, Block-chain, Blockchain, DH: Digital Humanity, Digital humanities, Digital twin: digital twin, DT: Digital Twin, Economic and social effects, ER: Extended Reality, Extended reality: extended reality, GenI: Generative Artificial Intelligence, IoT, Language Model, LLM: Large Language Model, Metaverse, Metaverses, Natural language model, Nft, NLP: Natural Language Model, Quantum Computing, Virtual environments, VR: Virtual Reality},
pubstate = {published},
tppubtype = {inproceedings}
}
The metaverse is a virtual environment where individuals may connect with one another, partake in a variety of activities, and access digital content. It coexists with the real world and it has the potential to significantly affect daily life as well as a variety of services and applications as it develops. To understand the importance of the impacts of the metaverse in today’s society, just think of the disruptive technologies that enable it: Artificial Intelligence (AI), Extended Reality (ER), IoT, Digital Twin (DT) and Blockchain/NFT all with assistance with the availability of large, rich and structured/unstructured dataset and advanced computational models. Metaverse is cadidated (and not only) to redefine everyday life, designing activities and services/products provisioning towards increasing efficiencies, money saving and quality performance, with a big impact in everyone and helping the design and testing of next generation of internet. However, there still remain not only technical and interoperability issues but above all ethical, human, social, and cultural concerns as to the metaverse’s influence upon its prospective scope in reconstructing the quality of urban life. This paper undertakes an upper-level scientific literature review of the area of the metaverse from a broader perspective. Further, it maps the some services and the relative requirements for declinate the enabling technologies of the metaverse, and explores their contributions. © 2024 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
Lin, Y.; Gao, Z.; Du, H.; Niyato, D.; Kang, J.; Xiong, Z.; Zheng, Z.
Blockchain-Based Efficient and Trustworthy AIGC Services in Metaverse Journal Article
In: IEEE Transactions on Services Computing, vol. 17, no. 5, pp. 2067–2079, 2024, ISSN: 19391374 (ISSN).
Abstract | Links | BibTeX | Tags: AI-generated content, Block-chain, Blockchain, Computational modelling, Content services, Data Mining, Digital contents, Information Management, Metaverse, Metaverses, Resource management, Semantic communication, Semantics, Virtual Reality
@article{lin_blockchain-based_2024,
title = {Blockchain-Based Efficient and Trustworthy AIGC Services in Metaverse},
author = {Y. Lin and Z. Gao and H. Du and D. Niyato and J. Kang and Z. Xiong and Z. Zheng},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85189177655&doi=10.1109%2fTSC.2024.3382958&partnerID=40&md5=5e3e80fbc88a49293b892acd762af3e9},
doi = {10.1109/TSC.2024.3382958},
issn = {19391374 (ISSN)},
year = {2024},
date = {2024-01-01},
journal = {IEEE Transactions on Services Computing},
volume = {17},
number = {5},
pages = {2067–2079},
abstract = {AI-Generated Content (AIGC) services are essential in developing the Metaverse, providing various digital content to build shared virtual environments. The services can also offer personalized content with user assistance, making the Metaverse more human-centric. However, user-assisted content creation requires significant communication resources to exchange data and construct trust among unknown Metaverse participants, which challenges the traditional centralized communication paradigm. To address the above challenge, we integrate blockchain with semantic communication to establish decentralized trust among participants, reducing communication overhead and improving trustworthiness for AIGC services in Metaverse. To solve the out-of-distribution issue in data provided by users, we utilize the invariant risk minimization method to extract invariant semantic information across multiple virtual environments. To guarantee trustworthiness of digital contents, we also design a smart contract-based verification mechanism to prevent random outcomes of AIGC services. We utilize semantic information and quality of digital contents provided by the above mechanisms as metrics to develop a Stackelberg game-based content caching mechanism, which can maximize the profits of Metaverse participants. Simulation results show that the proposed semantic extraction and caching mechanism can improve accuracy by almost 15% and utility by 30% compared to other mechanisms. © 2008-2012 IEEE.},
keywords = {AI-generated content, Block-chain, Blockchain, Computational modelling, Content services, Data Mining, Digital contents, Information Management, Metaverse, Metaverses, Resource management, Semantic communication, Semantics, Virtual Reality},
pubstate = {published},
tppubtype = {article}
}
AI-Generated Content (AIGC) services are essential in developing the Metaverse, providing various digital content to build shared virtual environments. The services can also offer personalized content with user assistance, making the Metaverse more human-centric. However, user-assisted content creation requires significant communication resources to exchange data and construct trust among unknown Metaverse participants, which challenges the traditional centralized communication paradigm. To address the above challenge, we integrate blockchain with semantic communication to establish decentralized trust among participants, reducing communication overhead and improving trustworthiness for AIGC services in Metaverse. To solve the out-of-distribution issue in data provided by users, we utilize the invariant risk minimization method to extract invariant semantic information across multiple virtual environments. To guarantee trustworthiness of digital contents, we also design a smart contract-based verification mechanism to prevent random outcomes of AIGC services. We utilize semantic information and quality of digital contents provided by the above mechanisms as metrics to develop a Stackelberg game-based content caching mechanism, which can maximize the profits of Metaverse participants. Simulation results show that the proposed semantic extraction and caching mechanism can improve accuracy by almost 15% and utility by 30% compared to other mechanisms. © 2008-2012 IEEE.
Bandara, E.; Foytik, P.; Shetty, S.; Hassanzadeh, A.
Generative-AI(with Custom-Trained Meta's Llama2 LLM), Blockchain, NFT, Federated Learning and PBOM Enabled Data Security Architecture for Metaverse on 5G/6G Environment Proceedings Article
In: Proc. - IEEE Int. Conf. Mob. Ad-Hoc Smart Syst., MASS, pp. 118–124, Institute of Electrical and Electronics Engineers Inc., 2024, ISBN: 979-835036399-9 (ISBN).
Abstract | Links | BibTeX | Tags: 5G, 6G, Adversarial machine learning, Bill of materials, Block-chain, Blockchain, Curricula, Data privacy, Distance education, Federated learning, Generative adversarial networks, Generative-AI, Hardware security, Llama2, LLM, Medium access control, Metaverse, Metaverses, Network Security, Nft, Non-fungible token, Personnel training, Problem oriented languages, Reference architecture, Steganography
@inproceedings{bandara_generative-aicustom-trained_2024,
title = {Generative-AI(with Custom-Trained Meta's Llama2 LLM), Blockchain, NFT, Federated Learning and PBOM Enabled Data Security Architecture for Metaverse on 5G/6G Environment},
author = {E. Bandara and P. Foytik and S. Shetty and A. Hassanzadeh},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85210243120&doi=10.1109%2fMASS62177.2024.00026&partnerID=40&md5=70d21ac1e9c7b886da14825376919cac},
doi = {10.1109/MASS62177.2024.00026},
isbn = {979-835036399-9 (ISBN)},
year = {2024},
date = {2024-01-01},
booktitle = {Proc. - IEEE Int. Conf. Mob. Ad-Hoc Smart Syst., MASS},
pages = {118–124},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {The Metaverse is an integrated network of 3D virtual worlds accessible through a virtual reality headset. Its impact on data privacy and security is increasingly recognized as a major concern. There is a growing interest in developing a reference architecture that describes the four core aspects of its data: acquisition, storage, sharing, and interoperability. Establishing a secure data architecture is imperative to manage users' personal data and facilitate trusted AR/VR and AI/ML solutions within the Metaverse. This paper details a reference architecture empowered by Generative-AI, Blockchain, Federated Learning, and Non-Fungible Tokens (NFTs). Within this archi-tecture, various resource providers collaborate via the blockchain network. Handling personal user data and resource provider identities is executed through a Self-Sovereign Identity-enabled privacy-preserving framework. AR/NR devices in the Metaverse are represented as NFT tokens available for user purchase. Software updates and supply-chain verification for these devices are managed using a Software Bill of Materials (SBOM) and a Pipeline Bill of Materials (PBOM) verification system. Moreover, a custom-trained Llama2 LLM from Meta has been integrated to generate PBOMs for AR/NR devices' software updates, thereby preventing malware intrusions and data breaches. This Llama2-13B LLM has been quantized and fine-tuned using Qlora to ensure optimal performance on consumer-grade hardware. The provenance of AI/ML models used in the Metaverse is encapsu-lated as Model Card objects, allowing external parties to audit and verify them, thus mitigating adversarial learning attacks within these models. To the best of our knowledge, this is the very first research effort aimed at standardizing PBOM schemas and integrating Language Model algorithms for the generation of PBOMs. Additionally, a proposed mechanism facilitates different AI/ML providers in training their machine learning models using a privacy-preserving federated learning approach. Authorization of communications among AR/VR devices in the Metaverse is conducted through a Zero-Trust security-enabled rule engine. A system testbed has been implemented within a 5G environment, utilizing Ericsson new Radio with Open5GS 5G core. © 2024 IEEE.},
keywords = {5G, 6G, Adversarial machine learning, Bill of materials, Block-chain, Blockchain, Curricula, Data privacy, Distance education, Federated learning, Generative adversarial networks, Generative-AI, Hardware security, Llama2, LLM, Medium access control, Metaverse, Metaverses, Network Security, Nft, Non-fungible token, Personnel training, Problem oriented languages, Reference architecture, Steganography},
pubstate = {published},
tppubtype = {inproceedings}
}
The Metaverse is an integrated network of 3D virtual worlds accessible through a virtual reality headset. Its impact on data privacy and security is increasingly recognized as a major concern. There is a growing interest in developing a reference architecture that describes the four core aspects of its data: acquisition, storage, sharing, and interoperability. Establishing a secure data architecture is imperative to manage users' personal data and facilitate trusted AR/VR and AI/ML solutions within the Metaverse. This paper details a reference architecture empowered by Generative-AI, Blockchain, Federated Learning, and Non-Fungible Tokens (NFTs). Within this archi-tecture, various resource providers collaborate via the blockchain network. Handling personal user data and resource provider identities is executed through a Self-Sovereign Identity-enabled privacy-preserving framework. AR/NR devices in the Metaverse are represented as NFT tokens available for user purchase. Software updates and supply-chain verification for these devices are managed using a Software Bill of Materials (SBOM) and a Pipeline Bill of Materials (PBOM) verification system. Moreover, a custom-trained Llama2 LLM from Meta has been integrated to generate PBOMs for AR/NR devices' software updates, thereby preventing malware intrusions and data breaches. This Llama2-13B LLM has been quantized and fine-tuned using Qlora to ensure optimal performance on consumer-grade hardware. The provenance of AI/ML models used in the Metaverse is encapsu-lated as Model Card objects, allowing external parties to audit and verify them, thus mitigating adversarial learning attacks within these models. To the best of our knowledge, this is the very first research effort aimed at standardizing PBOM schemas and integrating Language Model algorithms for the generation of PBOMs. Additionally, a proposed mechanism facilitates different AI/ML providers in training their machine learning models using a privacy-preserving federated learning approach. Authorization of communications among AR/VR devices in the Metaverse is conducted through a Zero-Trust security-enabled rule engine. A system testbed has been implemented within a 5G environment, utilizing Ericsson new Radio with Open5GS 5G core. © 2024 IEEE.
Otoum, Y.; Gottimukkala, N.; Kumar, N.; Nayak, A.
Machine Learning in Metaverse Security: Current Solutions and Future Challenges Journal Article
In: ACM Computing Surveys, vol. 56, no. 8, 2024, ISSN: 03600300 (ISSN).
Abstract | Links | BibTeX | Tags: 'current, Block-chain, Blockchain, digital twin, E-Learning, Extended reality, Future challenges, Generative AI, machine learning, Machine-learning, Metaverse Security, Metaverses, Security and privacy, Spatio-temporal dynamics, Sustainable development
@article{otoum_machine_2024,
title = {Machine Learning in Metaverse Security: Current Solutions and Future Challenges},
author = {Y. Otoum and N. Gottimukkala and N. Kumar and A. Nayak},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85193466017&doi=10.1145%2f3654663&partnerID=40&md5=b35485c5f2e943ec105ea11a80712cbe},
doi = {10.1145/3654663},
issn = {03600300 (ISSN)},
year = {2024},
date = {2024-01-01},
journal = {ACM Computing Surveys},
volume = {56},
number = {8},
abstract = {The Metaverse, positioned as the next frontier of the Internet, has the ambition to forge a virtual shared realm characterized by immersion, hyper-spatiotemporal dynamics, and self-sustainability. Recent technological strides in AI, Extended Reality, 6G, and blockchain propel the Metaverse closer to realization, gradually transforming it from science fiction into an imminent reality. Nevertheless, the extensive deployment of the Metaverse faces substantial obstacles, primarily stemming from its potential to infringe on privacy and be susceptible to security breaches, whether inherent in its underlying technologies or arising from the evolving digital landscape. Metaverse security provisioning is poised to confront various foundational challenges owing to its distinctive attributes, encompassing immersive realism, hyper-spatiotemporally, sustainability, and heterogeneity. This article undertakes a comprehensive study of the security and privacy challenges facing the Metaverse, leveraging machine learning models for this purpose. In particular, our focus centers on an innovative distributed Metaverse architecture characterized by interactions across 3D worlds. Subsequently, we conduct a thorough review of the existing cutting-edge measures designed for Metaverse systems while also delving into the discourse surrounding security and privacy threats. As we contemplate the future of Metaverse systems, we outline directions for open research pursuits in this evolving landscape. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.},
keywords = {'current, Block-chain, Blockchain, digital twin, E-Learning, Extended reality, Future challenges, Generative AI, machine learning, Machine-learning, Metaverse Security, Metaverses, Security and privacy, Spatio-temporal dynamics, Sustainable development},
pubstate = {published},
tppubtype = {article}
}
The Metaverse, positioned as the next frontier of the Internet, has the ambition to forge a virtual shared realm characterized by immersion, hyper-spatiotemporal dynamics, and self-sustainability. Recent technological strides in AI, Extended Reality, 6G, and blockchain propel the Metaverse closer to realization, gradually transforming it from science fiction into an imminent reality. Nevertheless, the extensive deployment of the Metaverse faces substantial obstacles, primarily stemming from its potential to infringe on privacy and be susceptible to security breaches, whether inherent in its underlying technologies or arising from the evolving digital landscape. Metaverse security provisioning is poised to confront various foundational challenges owing to its distinctive attributes, encompassing immersive realism, hyper-spatiotemporally, sustainability, and heterogeneity. This article undertakes a comprehensive study of the security and privacy challenges facing the Metaverse, leveraging machine learning models for this purpose. In particular, our focus centers on an innovative distributed Metaverse architecture characterized by interactions across 3D worlds. Subsequently, we conduct a thorough review of the existing cutting-edge measures designed for Metaverse systems while also delving into the discourse surrounding security and privacy threats. As we contemplate the future of Metaverse systems, we outline directions for open research pursuits in this evolving landscape. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.
2023
Banafa, A.
Transformative AI: Responsible, Transparent, and Trustworthy AI Systems Book
River Publishers, 2023, ISBN: 978-877004018-1 (ISBN); 978-877004019-8 (ISBN).
Abstract | Links | BibTeX | Tags: 5G, Affective Computing, AI, AI Ethics, Alexa, Augment Reality, Autoencoders, Autonomous Cars, Autoregressive models, Big Data, Big Data Analytics, Bitcoin, Blockchain, C3PO, ChatGPT, Cloud computing, CNN, Computer vision, Conditional Automation, Convolutional Neural Networks, Cryptocurrency, Cybersecurity, Deep learning, Digital transformation, Driver Assistance, Driverless Cars, Entanglement, Ethereum, Explainable AI. Environment and sustainability, Facebook, Facial Recognition, Feedforward. Neural Networks, Fog Computing, Full Automation, General AI, Generative Adversarial Networks (GANs), Generative AI, Google, High Automation, Hybrid Blockchain, IEEE, IIoT, Industrial Internet of Things, Internet of Things, IoT, Jarvis, Long Short-Term Memory Networks, LTE, Machin Learning, Microsoft, Narrow AI, Natural Language Generation (NLG), Natural Language Processing (NLP), NetFlix, Network Security, Neural Networks, NYTimes, Open Source, Partial Automation, PayPal, Private Blockchain, Private Cloud Computing, Quantum Communications, Quantum Computing, Quantum Cryptography, Quantum Internet. Wearable Computing Devices (WCD). Autonomic Computing, Quantum Machine Learning (QML), R2D2, Reactive Machines . Limited Memory, Recurrent Neural Networks, Robots, Sci-Fi movies, Self-Aware, Siri, Small Data, Smart Contracts. Hybrid Cloud Computing, Smart Devices, Super AI, Superposition, Theory of Mind, Thick Data, Twitter, Variational Autoencoders (VAEs), Virtual Reality, Voice User Interface, VUI, Wearable Technology, Wi-Fi, Zero-Trust Model
@book{banafa_transformative_2023,
title = {Transformative AI: Responsible, Transparent, and Trustworthy AI Systems},
author = {A. Banafa},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85180544759&partnerID=40&md5=c1fcd00f4b40e16156d9877185f66554},
isbn = {978-877004018-1 (ISBN); 978-877004019-8 (ISBN)},
year = {2023},
date = {2023-01-01},
publisher = {River Publishers},
series = {Transformative AI: Responsible, Transparent, and Trustworthy AI Systems},
abstract = {Transformative AI provides a comprehensive overview of the latest trends, challenges, applications, and opportunities in the field of Artificial Intelligence. The book covers the state of the art in AI research, including machine learning, natural language processing, computer vision, and robotics, and explores how these technologies are transforming various industries and domains, such as healthcare, finance, education, and entertainment. The book also addresses the challenges that come with the widespread adoption of AI, including ethical concerns, bias, and the impact on jobs and society. It provides insights into how to mitigate these challenges and how to design AI systems that are responsible, transparent, and trustworthy. The book offers a forward-looking perspective on the future of AI, exploring the emerging trends and applications that are likely to shape the next decade of AI innovation. It also provides practical guidance for businesses and individuals on how to leverage the power of AI to create new products, services, and opportunities. Overall, the book is an essential read for anyone who wants to stay ahead of the curve in the rapidly evolving field of Artificial Intelligence and understand the impact that this transformative technology will have on our lives in the coming years. © 2024 River Publishers. All rights reserved.},
keywords = {5G, Affective Computing, AI, AI Ethics, Alexa, Augment Reality, Autoencoders, Autonomous Cars, Autoregressive models, Big Data, Big Data Analytics, Bitcoin, Blockchain, C3PO, ChatGPT, Cloud computing, CNN, Computer vision, Conditional Automation, Convolutional Neural Networks, Cryptocurrency, Cybersecurity, Deep learning, Digital transformation, Driver Assistance, Driverless Cars, Entanglement, Ethereum, Explainable AI. Environment and sustainability, Facebook, Facial Recognition, Feedforward. Neural Networks, Fog Computing, Full Automation, General AI, Generative Adversarial Networks (GANs), Generative AI, Google, High Automation, Hybrid Blockchain, IEEE, IIoT, Industrial Internet of Things, Internet of Things, IoT, Jarvis, Long Short-Term Memory Networks, LTE, Machin Learning, Microsoft, Narrow AI, Natural Language Generation (NLG), Natural Language Processing (NLP), NetFlix, Network Security, Neural Networks, NYTimes, Open Source, Partial Automation, PayPal, Private Blockchain, Private Cloud Computing, Quantum Communications, Quantum Computing, Quantum Cryptography, Quantum Internet. Wearable Computing Devices (WCD). Autonomic Computing, Quantum Machine Learning (QML), R2D2, Reactive Machines . Limited Memory, Recurrent Neural Networks, Robots, Sci-Fi movies, Self-Aware, Siri, Small Data, Smart Contracts. Hybrid Cloud Computing, Smart Devices, Super AI, Superposition, Theory of Mind, Thick Data, Twitter, Variational Autoencoders (VAEs), Virtual Reality, Voice User Interface, VUI, Wearable Technology, Wi-Fi, Zero-Trust Model},
pubstate = {published},
tppubtype = {book}
}
Transformative AI provides a comprehensive overview of the latest trends, challenges, applications, and opportunities in the field of Artificial Intelligence. The book covers the state of the art in AI research, including machine learning, natural language processing, computer vision, and robotics, and explores how these technologies are transforming various industries and domains, such as healthcare, finance, education, and entertainment. The book also addresses the challenges that come with the widespread adoption of AI, including ethical concerns, bias, and the impact on jobs and society. It provides insights into how to mitigate these challenges and how to design AI systems that are responsible, transparent, and trustworthy. The book offers a forward-looking perspective on the future of AI, exploring the emerging trends and applications that are likely to shape the next decade of AI innovation. It also provides practical guidance for businesses and individuals on how to leverage the power of AI to create new products, services, and opportunities. Overall, the book is an essential read for anyone who wants to stay ahead of the curve in the rapidly evolving field of Artificial Intelligence and understand the impact that this transformative technology will have on our lives in the coming years. © 2024 River Publishers. All rights reserved.
Lin, Y.; Gao, Z.; Du, H.; Niyato, D.
Blockchain-Aided AI-Generated Content Services: Stackelberg Game-Based Content Caching Approach Proceedings Article
In: C., Ardagna; B., Benatallah; H., Bian; C.K., Chang; R.N., Chang; J., Fan; G.C., Fox; Z., Jin; X., Liu; H., Ludwig; M., Sheng; J., Yang (Ed.): Proc. - IEEE Int. Conf. Web Serv., ICWS, pp. 186–195, Institute of Electrical and Electronics Engineers Inc., 2023, ISBN: 979-835030485-5 (ISBN).
Abstract | Links | BibTeX | Tags: AI-generated content, Block-chain, Blockchain, Caching mechanism, Content caching, Content services, Digital contents, Game-Based, Metaverse, Metaverses, Shared virtual environments, Stackelberg Games, Virtual Reality
@inproceedings{lin_blockchain-aided_2023,
title = {Blockchain-Aided AI-Generated Content Services: Stackelberg Game-Based Content Caching Approach},
author = {Y. Lin and Z. Gao and H. Du and D. Niyato},
editor = {Ardagna C. and Benatallah B. and Bian H. and Chang C.K. and Chang R.N. and Fan J. and Fox G.C. and Jin Z. and Liu X. and Ludwig H. and Sheng M. and Yang J.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85173901801&doi=10.1109%2fICWS60048.2023.00038&partnerID=40&md5=3a323f44b98bd9e7a86a22523efcd488},
doi = {10.1109/ICWS60048.2023.00038},
isbn = {979-835030485-5 (ISBN)},
year = {2023},
date = {2023-01-01},
booktitle = {Proc. - IEEE Int. Conf. Web Serv., ICWS},
pages = {186–195},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {AI-Generated Content (AIGC) services are essential in developing the Metaverse, providing various digital content to build shared virtual environments. AIGC services can offer personalized content with user assistance, making the Metaverse more human-centric. However, it is difficult for participants to exchange data and construct trust among unknown Metaverse participants. To address the above challenge, we propose an integration of blockchain and AIGC to construct decentralized trust among participants. We design a smart contract-based verification mechanism to prevent random outcomes of AIGC services and guarantee the authenticity of digital contents. Given the quality of digital contents provided by the previous mechanisms, we then utilize them as metrics to establish a Stackelberg game-based content caching mechanism to maximize Metaverse participants' profits. Simulation results show that the proposed caching mechanism can improve utility by 30% compared to other mechanisms. © 2023 IEEE.},
keywords = {AI-generated content, Block-chain, Blockchain, Caching mechanism, Content caching, Content services, Digital contents, Game-Based, Metaverse, Metaverses, Shared virtual environments, Stackelberg Games, Virtual Reality},
pubstate = {published},
tppubtype = {inproceedings}
}
AI-Generated Content (AIGC) services are essential in developing the Metaverse, providing various digital content to build shared virtual environments. AIGC services can offer personalized content with user assistance, making the Metaverse more human-centric. However, it is difficult for participants to exchange data and construct trust among unknown Metaverse participants. To address the above challenge, we propose an integration of blockchain and AIGC to construct decentralized trust among participants. We design a smart contract-based verification mechanism to prevent random outcomes of AIGC services and guarantee the authenticity of digital contents. Given the quality of digital contents provided by the previous mechanisms, we then utilize them as metrics to establish a Stackelberg game-based content caching mechanism to maximize Metaverse participants' profits. Simulation results show that the proposed caching mechanism can improve utility by 30% compared to other mechanisms. © 2023 IEEE.