PaperlayerView exact revision on arXiv

Source-linked AI summary

Metaverse Communications, Networking, Security, and Applications: Research Issues, State-of-the-Art, and Future Directions

Mansoor Ali, Faisal Naeem, Georges Kaddoum, Ekram Hossain

arXiv:2212.13993v2cs.CRcs.SYeess.SY

TL;DR

The Metaverse’s immersive, data-intensive services bring privacy and security concerns, while networking and data acquisition present additional challenges. This paper reviews Metaverse technologies and their smart-city applications, threats, and countermeasures. It highlights blockchain-supported identity and data reliability alongside situational awareness approaches, and discusses applications in power systems and health.

  • Problem

    The Metaverse’s massive data exchange and integration of diverse technologies raise privacy and security risks, while acquiring abundant real-time data can challenge data integrity.

    Source: B. Challenges For Metaverse · p. 3, 1) Data Acquisition · p. 23

  • Method

    The paper comprehensively reviews Metaverse architecture, networking, privacy and security threats and countermeasures, and smart-city applications.

    Source: §IX · p. 33

  • Results

    The review identifies blockchain-supported digital identities and data reliability for digital twins, and AR, AI, and SDN as technologies for situational awareness.

    Source: D. Summary and Lessons Learned · pp. 25–26

  • Takeaways & Limitations

    The reviewed applications include power-grid fault localization using MR and XR and health services involving doctors’ interaction with patient 3D models.

    Source: J. Summary and Lessons Learned · p. 30

Abstract

from arXiv · show

Metaverse is an evolving orchestrator of the next-generation Internet architecture that produces an immersive and self-adapting virtual world in which humans perform activities similar to those in the real world, such as playing sports, doing work, and socializing. It is becoming a reality and is driven by ever-evolving advanced technologies such as extended reality, artificial intelligence, and blockchain. In this context, Metaverse will play an essential role in developing smart cities, which becomes more evident in the post COVID 19 pandemic metropolitan setting. However, the new paradigm imposes new challenges, such as developing novel privacy and security threats that can emerge in the digital Metaverse ecosystem. Moreover, it requires the convergence of several media types with the capability to quickly process massive amounts of data to keep the residents safe and well-informed, which can raise issues related to scalability and interoperability. In light of this, this research study aims to review the literature on the state of the art of integrating the Metaverse architecture concepts in smart cities. First, this paper presents the theoretical architecture of Metaverse and discusses international companies interest in this emerging technology. It also examines the notion of Metaverse relevant to virtual reality, identifies the prevalent threats, and determines the importance of communication infrastructure in information gathering for efficient Metaverse operation. Next, the notion of blockchain technologies is discussed regarding privacy preservation and how it can provide tamper-proof content sharing among Metaverse users. Finally, the application of distributed Metaverse for social good is highlighted.

I. INTRODUCTION

The introduction frames the Metaverse as a convergence of digital and physical worlds with potential smart-city applications, alongside substantial technical, security, and social challenges. It positions this paper as a review of Metaverse technologies, threats, smart-city roles, and research directions.

A. Background

  • The introduction describes the Metaverse as integrating digital and physical entities through XR, web technologies, and the Internet, with VR, MR, and AR representing varying degrees of integration.Source: A. Background · p. 1
  • Metaverse development is presented in three phases: digital twins, digital natives, and a mature, persistent surreality that absorbs reality.Source: A. Background · pp. 1–2

B. Challenges For Metaverse

  • Smart-city virtualization can overlook low-income communities’ needs, including education, living conditions, and water access, unless modeling is inclusive and multidimensional.Source: B. Challenges For Metaverse · p. 2
  • Immersive Metaverse services require stringent network performance, including VR streaming up to 1 Gbps, motion-to-photon latency below 20 ms, and haptic latency below 1 ms with 99.999% reliability.Source: B. Challenges For Metaverse · p. 2
  • Metaverse privacy and security risks include pervasive profiling, data mismanagement, inequitable AI outcomes, virtual spying, and possible compromise of connected real-world systems.Source: B. Challenges For Metaverse · p. 3

C. Related Work And Contributions

  • The paper distinguishes its smart-city focus from prior reviews of generic, AI-enabled, and edge-enabled Metaverse topics.Source: C. Related Work And Contributions · pp. 3–4
  • The paper reviews Metaverse concepts and smart-city applications, identifies privacy and security threats and countermeasures, and outlines future research directions for secure integration.Source: C. Related Work And Contributions · p. 4
  • The paper surveys computation, networking, communication, and distributed-ledger technologies, including blockchain approaches for cross-chain sharing, decentralized storage, and edge data sharing.Source: C. Related Work And Contributions · p. 4

II. AN OVERVIEW OF METAVERSE

The Metaverse blends digital, human, and physical worlds, with supporting infrastructure and an engine that processes information across them. Its architecture encompasses human interaction, physical-world infrastructure, digital environments, and information flows.

A. Metaverse Architecture

  • The Metaverse is a synthetic space blending digital, human, and physical worlds, where users interact through avatars.Its architecture connects computer-generated environments, digital things, and user-controlled avatars.Source: A. Metaverse Architecture · p. 4

1) The Human World:

  • Human users direct avatars to interact, socialize, work, and play through XR and human-computer interaction technologies.The human world comprises users, their social communications, and personal psychologies.Source: 1) The Human World · p. 4

2) The Physical World:

  • The physical world supplies storage, computation, communication, and sensing infrastructure for data perception, processing, transmission, and physical control.Heterogeneous networks provide connectivity, while cloud-edge-end computing supports storage and computation for the many frames generated in virtual worlds.Source: 2) The Physical World · p. 4

3) The Digital World:

  • The digital world links distributed virtual worlds, or sub-Metaverses, that provide virtual environments, services, and goods [10].Its information sources include real-space inputs exhibited digitally and outputs produced by virtual services, objects, and avatars [10].Source: 3) The Digital World · p. 4

4) Metaverse Engine:

  • The Metaverse engine uses physical-world data to generate, maintain, and update virtual space through blockchain, digital twins, and AI [32].AI-based analysis can support digital-twin simulations of real space, while blockchain can support transparent transactions among avatars [10]. The paper identifies information flow across the three worlds as the Metaverse’s main resource.Source: 4) Metaverse Engine · pp. 4, 6

5) Intra-World Flow of Information:

Information moves within and between the Metaverse’s human, physical, and digital worlds, while its attributes describe requirements for effective operation. The section also identifies six fundamental enabling technologies.

5) Intra-World Flow of Information:

  • The human world relies on social communication, the physical world senses and processes data, and the digital world manages information to render the Metaverse and provide services.Users can also create and distribute digital content across sub-Metaverses.Source: 5) Intra-World Flow of Information · p. 6

6) Inter-World Flow of Information:

  • IoT, the Internet, and human consciousness link the three worlds, with processed digital information feeding back to transform the physical world [10].Humans turn physical-world information into knowledge; HCI and XR support interaction with physical objects and virtual AR.Source: 6) Inter-World Flow of Information · p. 6

1) Heterogeneity:; 2) Scalability:

  • Heterogeneity spans communications, data, devices, virtual environments, and human psyche, while scalability means remaining effective with many concurrent users, scenario complexities, and interaction modes.Source: 1) Heterogeneity · p. 6, 2) Scalability · p. 6

3) Interoperability:; 4) Sustainability:

  • Interoperability covers both smooth user travel between sub-Metaverses and exchange of digital assets across platforms [7].Sustainability calls for a decentralized framework that maintains persistence and avoids single points of failure, alongside continued user enthusiasm for creating content [10].Source: 3) Interoperability · p. 6, 4) Sustainability · pp. 6–7

5) Hyper-Spatiotemporality:; 6) Immersiveness:

  • Hyper-spatiotemporality describes virtual time-space perpetuity that allows movement between worlds with different spatiotemporal dimensions [28].Immersiveness means a virtual environment is realistic enough for emotional and psychological immersion, also termed “immersive realism”.Source: 5) Hyper-Spatiotemporality · p. 7, 6) Immersiveness · p. 7

C. Enabling Metaverse Technologies

1) Interactivity:

The section describes technologies that connect users and avatars with immersive virtual worlds, link virtual entities to physical systems, and support interoperable services. It also outlines blockchain, standards, and development platforms as parts of the Metaverse ecosystem.

1) Interactivity:

  • XR devices combine MR, AR, and VR to support immersive, real-time user–avatar interaction through 3D modeling, sensing, and varied input devices.MR supports transitions between AR and VR; wearable XR can sense human-specific details and surrounding objects.Source: 1) Interactivity · p. 7

2) Digital Twin (DT):

  • Digital twins mirror real-world systems and objects, using input data and AI-assisted models for self-adaptation, simulation, traceability, and predictive maintenance.The bidirectional link between virtual entities and physical counterparts is described as reducing physical-world risks and improving efficiency.Source: 2) Digital Twin (DT) · p. 7

3) Ubiquitous Computing:

  • Ubiquitous computing connects users and smart devices, while cloud-edge-end cooperation allocates resources to Metaverse applications in response to demand.The passage describes heterogeneous edge infrastructure coordinated with scalable cloud infrastructure for real-time resource allocation.Source: 3) Ubiquitous Computing · p. 7

4) Networking:

  • IoT, SDN, B5G, and 6G support ubiquitous access and real-time data transmission; SDN enables dynamic allocation of virtualized network and computing resources.SAGIN is identified as a potential 6G paradigm for ubiquitous access, and IoT sensors extend human senses.Source: 4) Networking · p. 7
  • AI supports personalized services, avatar creation, multilingual support, and intelligent interactions such as movement prediction and shopping guidance.The passage characterizes AI as the Metaverse’s “brain.”Source: 4) Networking · p. 7

6) Blockchain:

  • Blockchain provides a decentralized, auditable, transparent, and immutable basis for a persistent virtual economy, with smart contracts, NFTs, and De-Fi supporting its functions.Blockchain categories differ in decentralization, while consensus protocols affect scalability and ledger consistency.Source: 6) Blockchain · p. 8

D. Existing Metaverse-Related Standards

  • ISO/IEC 23005 supports information exchange and adaptation between real and virtual worlds, while IEEE 2888 specifies interfaces for physical–cyber synchronization.The standards cover real-to-virtual, virtual-to-real, and virtual-to-virtual adaptation; IEEE 2888 adds sensor, actuator, synchronization, and disaster-response components.Source: D. Existing Metaverse-Related Standards · p. 8

E. Tool and Platforms for Metaverse

2) Unreal Engine:

The section surveys development platforms, devices, and application prototypes, from avatar and environment creation to collaboration, social experiences, simulation, and user-generated content. It also notes infrastructure and interoperability demands that complicate implementation.

2) Unreal Engine:

  • Unreal Engine supports creation of Metaverse assets, and its MetaHuman Creator can significantly reduce the time needed to create digitized human avatars.The passage also identifies marketplace assets as a use of the platform.Source: 2) Unreal Engine · p. 9

3) Roblox:

  • Roblox combines avatar and teleportation development tools with a 3D engine, design studio, and marketplace for avatar trading.The platform is described as having evolved from a game into a development platform.Source: 3) Roblox · p. 9

4) Meta Avatars:

  • Meta Avatars lets users customize avatars across Unity-supported Quest and other VR platforms, with hand, motion, and audio tracking supporting expressive representations.The system is intended to make avatar functionality consistently reflect its user.Source: 4) Meta Avatars · p. 9

5) Hololens2:

  • HoloLens 2 is an MR headset that connects through Microsoft Mesh for remote communication, eye contact, and observation of other users’ behavior.The passage also notes built-in Wi-Fi and computing, along with computation power and battery life.Source: 5) Hololens2 · p. 9

6) Oculus Quest2:

  • Oculus Quest 2 is a Meta VR headset for running VR applications, connected to a computer by USB or Wi-Fi.The supplied passage describes the device as a head-mounted VR device.Source: 6) Oculus Quest2 · p. 9
  • Metaverse implementations require substantial computation, intensive rendering, real-time digital-twin updates, low-latency communication, and more standardized protocols and platforms.The passage links standardization to avatars moving between virtual spaces and creating content across them.Source: 6) Oculus Quest2 · p. 9

F. Existing Modern Prototypes of Metaverse Applications

5) Creator Economy:

  • Metaverse content creation spans AI-generated, user-generated, professional-generated, and mixed professional–user modes.The passage suggests AIGC may help providers produce customized content at lower cost and higher efficiency, while UGC gives users control over creation.Source: 5) Creator Economy · p. 10

III. COMMUNICATION AND NETWORKING

The section reviews communication demands and networking approaches for immersive Metaverse services, including VR broadcasting and AR adaptation. It surveys resource-allocation and human-in-the-loop methods that address service quality under latency, accuracy, bandwidth, and resource constraints.

III. COMMUNICATION AND NETWORKING

  • Metaverse networking must support ubiquitous, persistent connectivity, low-friction interaction, and real-time synchronization across physical and virtual worlds, despite heavy 3D multimedia demands on existing infrastructure.The section frames edge-driven networking, user-focused and semantic communication, and smart infrastructures such as UAVs and RIS as relevant approaches.Source: §III · p. 10

A. Data Rate, Reliability, and Latency of 3D Multimedia Networks

1) Resource Allocation for VR Broadcasting:

  • VR broadcasting faces resource-allocation trade-offs; reviewed approaches include learned transmission-mode selection, privacy-preserving viewpoint prediction, adaptive service optimization, and learned pricing and matching.The cited hybrid transmission-mode framework achieved a higher data rate than macrocell-only broadcasting or small-cell-only unicasting; a learning-based auction approach achieved near-optimal social welfare while reducing information-exchange cost.Source: 1) Resource Allocation for VR… · pp. 12–13

2) Resource Allocation for Adapting AR:

  • AR adaptation must balance interaction latency and analysis accuracy under limited edge resources, with approximate and precise AR differing in detection scope and service demands.A dynamic MAR framework adjusts upload and processing configurations to user capabilities and network conditions; other reviewed work addresses latency–accuracy balancing and multi-user cooperation.Source: 2) Resource Allocation for Adapting AR · p. 13, B. Human-in-the-Loop Communication · p. 13

B. Human-in-the-Loop Communication

  • Human-in-the-loop communication approaches adapt AR processing to user and network conditions and address multi-user coordination, cross-platform interaction, and shared AR experiences.The reviewed methods include a network coordinator for balancing latency and accuracy, Edge AR X5 for cooperative multi-user MAR, and a shared AR architecture.Source: B. Human-in-the-Loop Communication · p. 13

1) Edge Caching for VR/AR Content:

The section reviews communication approaches for immersive Metaverse services, from edge caching and tactile interaction to semantic communication. It describes resource and latency demands alongside techniques and reported outcomes for addressing them.

1) Edge Caching for VR/AR Content:

  • FoV-aware caching improved bandwidth savings/cache-hit ratio by a factor of two for panoramic VR streaming.The reviewed approach used probabilistic learning based on users’ current preferences and historical viewing data.Source: 1) Edge Caching for VR/AR Content · p. 14

2) Holography:

  • Holographic communication uses wavefront recording and reproduction, while reviewed work explores unequal error protection and wireless light-field interaction.Huo et al. proposed coding for varied protection levels; related work considers point-cloud delivery over wireless networks,.Source: 2) Holography · p. 14

3) The Tactile Internet with Haptic Feedback:

  • Tactile Internet interactions are latency-sensitive, with teleoperation requiring about 1 ms end-to-end latency; large-scale deployment is not expected soon.Reviewed work addresses testing and resource allocation, including prediction of lost or delayed data and bandwidth reservation under reliability and service constraints.Source: 3) The Tactile Internet with Haptic… · pp. 14–15

4) Goal-Aware/Semantic Communication:

  • Semantic communication transmits task-relevant information, using semantic encoding and decoding to remove unnecessary content and restore meaning for the recipient.The approach has potential to overcome the Shannon capacity limit [109].Source: 4) Goal-Aware/Semantic Communication · p. 15
  • A deep-learning translation system using sentence similarity transmitted information more efficiently than its benchmark, particularly at low signal-to-noise ratio.Semantic communication evaluates human perception rather than relying only on classic bit error rate.Source: 4) Goal-Aware/Semantic Communication · p. 15
  • A semantic-service provider auction evaluated with BLEU and sentence similarity found incentive compatibility and individual rationality sufficient to maximize provider revenue.The reviewed work also identifies resource allocation as a concern for reducing computational consumption in semantic communications.Source: 4) Goal-Aware/Semantic Communication · pp. 15–16

C. Real-Time Bidirectional Synchronization Between the Virtual and Physical Worlds

This section surveys synchronization between virtual and physical entities through edge resources, digital twins, and network management. It also outlines demands from multimodal interaction, AI-based communication management, and human-centered services.

1) Resource Allocation for Synchronizing the Virtual and Physical Worlds:

  • A distributed incentive method for vehicles contributing resources to virtual–physical synchronization can maximize energy efficiency in vehicular twin networks under dynamic scenarios.The approach extends an earlier edge-device data-collection incentive mechanism to dynamic Internet of Vehicles scenarios.Source: 1) Resource Allocation for… · p. 16, C. Real-Time Bidirectional… · p. 16

2) Physical/ Virtual Synchronization Through Intelligent Edge Networks:

  • Digital twins are reviewed for edge-network optimization, including joint offloading, resource allocation, and user grouping, as well as RIS configuration prediction and SAGIN communication.Other reviewed work uses twins for network slicing and synchronization, including temporal value decay and UAV state collection.Source: 2) Physical/ Virtual Synchronization… · pp. 16–17

1) High-Performance Networks for Real-Time User Interaction and Multimodal Content Delivery:

  • Multimodal Metaverse interaction combines touch, audio, and images, while real-time 3D rendering and many concurrent users raise edge-resource demands.The section also describes emergency or extreme URLLC service needs under temporally and spatially changing traffic, device density, infrastructure, and spectrum availability.Source: 1) High-Performance Networks for… · p. 17, 5) Break-in-Presence Feeling · p. 17

2) AI for Smart Edge Communication :

  • AI can support edge resource management, task offloading, and service pricing, but training and storing models is computationally costly on resource-constrained devices.Source: 2) AI for Smart Edge Communication · p. 17

3) Semantic-Aware Content Popularity:

IV. PRIVACY AND SECURITY THREATS TO METAVERSE

  • The section introduces privacy and security threats spanning governance, social and physical effects, the economy, privacy, data, and identity.Source: §IV · p. 17

A. Identity-Related Threats

The section describes identity threats across authentication and virtual worlds, alongside data risks involving injection, tampering, quality, and sensitive information. These risks can affect users, avatars, digital assets, and physical entities.

A. Identity-Related Threats

3) Impersonation Attacks:

B. Data-Related Threats

1) Falsely Injected Data:

  • False instructions or poisoned training data can produce biased AI models and threaten people or equipment, while data tampering can disrupt entities and conceal attacks.Attackers may alter raw data or distort message digests and logs.Source: 1) Falsely Injected Data · p. 18, 2) Data Tampering · p. 18

4) Problems in Managing New Forms of Metaverse Data:

5) Threats to UGC Provenance and Ownership:

The section surveys risks to user-generated content provenance and privacy across data collection, transmission, processing, storage, and devices. It also describes threats to digital footprints, data access, and network availability.

5) Threats to UGC Provenance and Ownership:

  • Without centralized asset registration, tracing ownership and provenance of user-generated content across sub-Metaverses is difficult.The section connects this difficulty to turning user-generated content into secured assets.Source: 5) Threats to UGC Provenance and… · p. 19

1) Ubiquitous Data Collection:

  • Immersive services collect detailed profiling data, including biometrics and movement, which can expose users’ habits, location, and behavior.The section describes real-time tracking by VR-device cameras and motion sensors, with sensitive collected information potentially exploited by attackers.Source: 1) Ubiquitous Data Collection · p. 19, C. Privacy Threats · p. 19

2) Privacy Leakage during Data Transmission:

5) Compromised or Rogue End Devices:

6) Threats to Digital Footprints:

1) DDoS:

2) SPoF:

The section surveys threats across decentralized services, digital-asset markets, human safety, physical infrastructure, and governance. It highlights how distributed participation and weak trust mechanisms can expose users and systems to abuse.

2) SPoF:

  • Centralized Metaverse frameworks simplify user management but remain vulnerable to DDoS-related single points of failure, while Sybil identities can manipulate services or compromise the network.The centralized design also raises transparency and trust concerns in exchanges between sub-Metaverses.Source: 2) SPoF · p. 20, 3) Sybil Attacks · p. 20

1) Threats to Digital Asset Ownership:

  • NFTs may support asset provenance and identification, but remain exposed to phishing, scams, ransomware, duplicate minting across blockchains, and value manipulation.Complex ownership and the absence of central authority complicate traceability, trading, pricing, and asset generation; blockchain-backed NFTs have potential to address provenance and identification [52].Source: 1) Threats to Digital Asset Ownership · p. 20

2) Service Trust Issues During Virtual Object Trading & UGC:

  • Unreliable avatars and fraud risks in virtual trading and user-generated content complicate trust; smart-contract flaws caused a Binance Metaverse project loss of $1.7 million [10].Digital copies built with DT technology also require reliable and authentic generation and deployment.Source: 2) Service Trust Issues During Virtual… · p. 20

3) Threats to Economic Fairness:

  • Creator-economy fairness is threatened by collusion, free-riding, and strategic manipulation of supply, demand, or auction bids –.Free-riding may compromise the viability of the creator economy.Source: 3) Threats to Economic Fairness · p. 20

1) Threats to Personal Safety:

  • Attacks on cameras and wearable devices can reveal users’ locations and routines, threatening personal safety; the Metaverse may also expose users to mental stress and crime.The authors note that physical trauma risk is limited, while lack of regulation and laws may increase abusive or criminal actions.Source: 1) Threats to Personal Safety · p. 20

2) Social Effects:

  • Potential social harms include cyberstalking, cyber-bullying, extortion, biased outcomes, child pornography, rumors, and addiction; immersive environments may also aid extremist recruitment and training, –.Source: 2) Social Effects · p. 20

3) Threats to the Safety of Infrastructure:

  • Compromised devices in an integrated Metaverse could provide entry points for advanced persistent threats against critical infrastructure, including rail and power systems,.Source: 3) Threats to the Safety of… · p. 20

G. Governance-Related Threats

1) New Regulations & Laws for Virtual Crimes:

The section examines challenges in applying law and accountability to virtual conduct, alongside security countermeasures and their limits. It emphasizes that dynamic, interoperable Metaverse settings complicate enforcement and forensic analysis.

1) New Regulations & Laws for Virtual Crimes:

2) Misbehaving Regulators:

  • Smart contracts could automate regulations without trusted intermediaries, but remain vulnerable to re-entry and short-address attacks, mishandled exceptions, and information disclosure,.The section also calls for dynamic reward and punishment mechanisms, upheld democratically by most avatars, to encourage honest regulators.Source: 2) Misbehaving Regulators · p. 21

3) Threats to Digital Forensics:

  • Digital forensics combines evidence from virtual and real worlds, but interoperability problems, dynamic environments, anonymity, and identity manipulation with deepfakes complicate analysis.Source: 3) Threats to Digital Forensics · p. 21

H. Summary and Lessons Learned

  • The paper’s threat summary links evolving technologies to inherited vulnerabilities, pervasive personal data, new defenses, physical-world harms, and regulatory challenges.It argues that Metaverse heterogeneity, scalability, decentralization, and interoperability make existing countermeasures challenging to apply, motivating context-specific privacy and security solutions.Source: H. Summary and Lessons Learned · p. 21

A. Security Threat Countermeasures

  • Proposed measures include wearable-device key establishment from wireless channel attributes and device authentication using encryption, bloom filters, and MinHash,.Source: A. Security Threat Countermeasures · p. 21
  • A DT state-replication approach was validated for efficiency, but did not examine the reliability of data gathered from distinct repositories.Source: A. Security Threat Countermeasures · p. 22
  • Other measures include controlled AR content sharing, intrusion detection with over 90% mean accuracy but no defense against unknown attacks, and blockchain-based free-rider mitigation.A misinformation-blocking method is limited to static online social networks and is difficult to apply to the Metaverse’s time-varying, massive social graph.Source: A. Security Threat Countermeasures · pp. 22–23
  • Blockchain approaches address cross-domain authentication and decentralized governance, while AI models target malicious accounts; privacy-preserving forensics uses RAM mirroring and taint analysis, –.The forensic scheme seeks digital proof without touching users’ private data.Source: A. Security Threat Countermeasures · pp. 21–23

B. Blockchain for Securing Metaverse

The section reviews blockchain’s potential roles in Metaverse data acquisition, storage, sharing, interoperability, and privacy. It also notes costs and latency associated with distributed replication and validation.

1) Data Acquisition

  • Metaverse data acquisition supplies machine-learning training and supports adaptation and insights, but massive unstructured real-time data and unreliable sources challenge data quality and system reliability,.Source: 1) Data Acquisition · p. 23
  • Blockchain validation and consensus can make acquired Metaverse data traceable, tamper-resistant, and less prone to duplication, supporting data integrity and reliability –.The paper cautions that blockchain acquisition can be slow and costly, with chain replication increasing storage demand –.Source: 1) Data Acquisition · p. 23

2) Data Storage

  • As Metaverse participation grows, physical-world storage may become inadequate, making storage a concern for healthcare, real estate, entertainment, and gaming applications.Blockchain can back up data across blocks and improve availability, transparency, and reliability, but mirroring data throughout the chain raises latency concerns.Source: 2) Data Storage · pp. 23–24

3) Sharing of Acquired Data

  • Shared Metaverse platforms can support collaboration, but centralized sharing risks exposing sensitive data, while mutable data can reduce availability and increase latency –.Real-time data volume makes flexibility a concern in conventional sharing environments.Source: 3) Sharing of Acquired Data · p. 24

B. Blockchain for Securing Metaverse

  • Blockchain can increase transaction precision and transparency, let data owners completely control information and facilitate audits, and make data sharing more flexible by automating agreement execution with smart contracts.Because copies must be replicated along a chain, information transfer is delayed. As Metaverse users grow, block numbers and computing needs rise, making shared-transaction verification costly.Source: 3) Sharing of Acquired Data · pp. 24–25

4) Data Interoperability

  • Cross-chain protocols could connect fragmented digital realms and enable exchanges of payments, NFTs, and avatars between virtual spaces without intermediaries, –.Source: 4) Data Interoperability · p. 25

5) Data Privacy Preservation

  • Blockchain users can manage data through public and private keys, restrict intermediary access, and use ledger audit trails to check transaction consistency and completeness.Privacy can still be compromised by lost private keys or attacks exploiting third-party application weaknesses.Source: 5) Data Privacy Preservation · p. 25

1) Introduction:

  • Digital twins represent real-world systems and objects; bidirectional IoT links synchronize chosen models with the physical world and may help predict user needs or hardware servicing,,.Source: 1) Introduction · p. 25

2) Challenges:

The section reviews challenges and applications across digital twins, blockchain, power systems, and health. It highlights data reliability, security and privacy risks, and the need to address scalability and governance concerns.

2) Challenges:

  • Combining real-time sensor data from diverse devices makes digital-twin models difficult to secure from malware and botnets, while model accuracy depends on high-quality, genuine source data,.Digital twins across virtual worlds and markets also need to cooperate and respond to rapid change.Source: 2) Challenges · p. 25

3) Significance of blockchain:

  • Blockchain can help digital twins resist attacks and securely share data across virtual environments, with immutable transactions requiring consensus to alter,.The paper identifies scalability, privacy, and standardization as unresolved implementation issues; combining federated learning, AI, and blockchain may improve DT quality [213].Source: 3) Significance of blockchain · p. 25, 4) Summary · p. 25

D. Summary and Lessons Learned

  • The paper’s lessons identify blockchain as a means to support reliable DT data, while fusing IoT and wearable sensory signals with biometrics may benefit authentic identity management and blockchain may secure digital identities.Source: D. Summary and Lessons Learned · p. 25
  • Metaverse technologies may expand attack surfaces and amplify privacy threats affecting digital footprints; AR, AI, and SDN can support situation awareness for monitoring threats across sub-Metaverses.Source: D. Summary and Lessons Learned · p. 26

A. The Role of MetaVerse in Power Systems

  • Power-sector applications include blockchain smart contracts for transparent energy measurement and peer-to-peer trading, while MR/AR/VR support remote assistance, virtual visits, and asset maintenance.The section also raises sustainability concerns about the energy use of bitcoin transactions.Source: A. The Role of MetaVerse in Power… · p. 26
  • MR/VR/AR and IoT could support virtual power plants and real-time asset monitoring, shared operation centers, and manpower optimization.Automated alerts may help detect and resolve bottlenecks, potentially reducing failures and downtime.Source: A. The Role of MetaVerse in Power… · p. 26

B. Metaverse for Internet of Health Things

  • Health Metaverse applications include surgery assistance, virtual care, telemedicine, immersive health monitoring, and patient-professional interaction –.Professional medical treatment and advice remain the gold standard in the health Metaverse.Source: B. Metaverse for Internet of Health… · p. 27
  • Health applications raise patient safety and privacy concerns; inappropriate handling of mental or physical health activities may endanger patients, and gamified health services require regulation,.The section also flags the effects of gamifying medical expertise, platform upgrades, tensions between regulation and Metaverse freedom, and user personalization, safety, and privacy.Source: B. Metaverse for Internet of Health… · p. 27

C. Distributed Metaverse

Centralized virtual-world servers constrain user capacity and fragment control, motivating a distributed Metaverse that shares computation and data management across physical entities and nearby infrastructure.

C. Distributed Metaverse

  • Distributed Metaverse architecture assigns personal-data control and some computation to corresponding physical entities, addressing server bottlenecks and fragmentation [220].Cloud, edge, and fog servers respectively simulate the virtual world, handle grid-area computations, and perform tasks near end users; this distributes heavy computational costs and supports a universal Metaverse [220].Source: C. Distributed Metaverse · pp. 27–28

D. Use Case: Distributed Social Metaverse

  • The fog-edge Metaverse has the shortest latency as user count increases, whereas cloud-based latency rises substantially.The comparison used a cloud framework as the baseline and varied the number of Metaverse users.Source: D. Use Case: Distributed Social… · p. 28

E. Metaverse for Social Good

  • Metaverse is presented as supporting cultural preservation, diverse scenarios, avatar-led governance, and lower-cost virtual events for social good.Examples include digital reconstruction of cultural relics, Decentraland policy voting, and virtual events such as UC Berkeley’s 2020 Minecraft graduation.Source: 1) Humanity · p. 28, 2) Diversity · p. 29, 3) Equality · p. 29

F. Virtual Metaverse Campus

  • The Chinese University of Hong Kong campus prototype mirrors student activity between physical and virtual environments and uses smart contracts for transactions while encouraging user-created content.The prototype was developed with Unity and Blender, and users can trade or display their creations and personalize rooms.Source: F. Virtual Metaverse Campus · p. 29

G. Entertainment

  • Users can create and share entertainment applications, while concerts can host physical and virtual audiences who interact as if at the same event.The paper notes that Metaverse entertainment is still at an early stage and that further features may emerge.Source: G. Entertainment · p. 29

H. Gaming

The section surveys Metaverse applications and blockchain projects, alongside smart-city uses and infrastructure constraints. It describes XR-based gaming, virtual testing for autonomous vehicles, and several distinct project economies.

H. Gaming

  • XR gaming uses gestures and body movements to control characters, while augmented-reality games can place virtual objects in physical surroundings.Examples include HoloLens, Omni One, and Pokémon Go.Source: H. Gaming · p. 29

I. Autonomous Vehicles

  • Metaverse testing can provide autonomous vehicles with a virtual driving environment and richer data gathered from vehicles and drivers worldwide.The paper notes that simulated and physical worlds differ, so test results may not transfer effectively.Source: §I · p. 30

J. Summary and Lessons Learned

  • Smart-city uses include 3D-model diagnoses and simulated treatment; XR entertainment strains infrastructure, while Metaverse education can ease space and pandemic constraints.The section also describes Metaverse applications in power grids and healthcare, including operator visualization of compromised lines.Source: J. Summary and Lessons Learned · p. 30

VII. METAVERSE PROJECTS

  • The surveyed blockchain projects support applications and services ranging from e-commerce to real estate, with Fig. 16 depicting their virtual spaces.The projects named are Illuvium, Axie Infinity, Sandbox, and Decentraland.Source: §VII · p. 30

1) Sandbox:

  • Sandbox lets users create, trade, and monetize voxel assets on Ethereum; scalability concerns motivated its team to seek layer-2 solutions.The platform uses IPFS to store digital assets and prevent unauthorized modifications.Source: 1) Sandbox · p. 30

2) Decentraland:

  • Decentraland represents land as scarce, transferable NFTs in Ethereum smart contracts, with no central organization controlling the world’s rules or access.Its protocol has real-time, land-content, and consensus layers, supported by identity and payment systems.Source: 2) Decentraland · p. 30

3) Illuvium:

  • Illuvium combines open-world exploration with player-versus-player battles; its NFTs use Immutable X, a layer-2 scaling solution.The game describes zero-gas-fee NFT trading through an external exchange or in-game marketplace.Source: 3) Illuvium · p. 31

4) Axie Infinity:

  • Axie Infinity pairs creature battles and collection with a user-based economy, governance rewards, NFT trading, and a lower-fee Ethereum-linked sidechain.Players can collect, breed, and battle Axies; AXS rewards may be earned through staking, play, and governance participation.Source: 4) Axie Infinity · p. 31

VIII. FUTURE DIRECTIONS AND CHALLENGES

The paper reviews future Metaverse challenges spanning security, ethics, immersion, energy, computing, and communication. It concludes that these issues remain part of the wider effort to integrate Metaverse concepts into smart cities.

VIII. FUTURE DIRECTIONS AND CHALLENGES

  • The Metaverse vision remains constrained by sensory devices, computational power, and resources, and the survey reviews its principles, applications, privacy, security, and smart-city role [228].The authors also review networking and communication procedures and identify possible countermeasures for privacy and security challenges.Source: §VIII · p. 31, §IX · p. 33

A. Security

  • Wearables collect identity-sensitive data, and server attacks or failures may expose it; blockchain is anticipated as a security-enhancing approach [228].The passage identifies risks including identity theft, body swapping, and false-avatar scandals.Source: A. Security · p. 31

B. Code of Ethics

  • Unfettered avatar behavior may harm minors, motivating proposed controls on user behavior and clearer virtual-world ethical norms [28].The paper links the concern to conflicts between avatar behavior and physical-world moral values.Source: B. Code of Ethics · p. 31

C. Perceptual Realization

  • BCI could improve immersion, but non-invasive devices trade easier wearability for recognition errors, whereas invasive devices use implanted electrodes for precise signals [228].The paper identifies balancing convenience and precision as a future research direction.Source: C. Perceptual Realization · pp. 31–32

D. Balance Between Real and Virtual

  • Excessive Metaverse involvement may blur real and virtual life and harm study, work, and daily life; proposed directions include limits on use, age access, or realism [228].The passage also proposes a regulatory body to scrutinize negative effects.Source: D. Balance Between Real and Virtual · p. 32

E. Energy-Efficient and Green Metaverse

  • Persistent Metaverse data centers carry energy costs, and the paper calls for research into distributing their impact geographically.Intel determined that powering the Metaverse would require a thousand-fold increase over its existing combined computational capacity.Source: E. Energy-Efficient and Green Metaverse · p. 32

F. Cloud-Edge-End Orchestrated Metaverse

H. Communications and Protocol Design

  • Metaverse protocols should be goal-oriented, semantic-aware, and unified across heterogeneous systems; AI-enabled blockchain may support resource allocation, access control, monitoring, and secure transmission.The paper also notes blockchain’s interoperability, finance, standardization, and malicious-activity challenges.Source: H. Communications and Protocol Design · p. 32, §I · p. 33
Loading 2212.13993v2…