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ArticlesMetaQ: A Quantum Approach for Secure and Optimized Metaverse Environment
  • Hyuk-Jun Kwon1, Abir El Azzaoui2, and Jong Hyuk Park2, *

Human-centric Computing and Information Sciences volume 12, Article number: 42 (2022)
Cite this article 2 Accesses
https://doi.org/10.22967/HCIS.2022.12.042

Abstract

Recently, Metaverse technology became the topic of today’s following the news of major companies intending to create their Metaverse environment for various application such as gaming, assets, virtual meetings, and so on. The success of Metaverse-based application is highly depending on fast and secure connectivity, integrated high-end technologies such as virtual reality (VR), augmented reality (AR), and mixed reality (MR). The current Metaverse applications has critical challenges in both hardware and software that urge immediate mitigation. Issues such as security, privacy, connectivity, and computation complexity are the main reasons behind the slow integration of Metaverse. On the other hand, Quantum technology promises fast, optimized, and scalable computation results due to its exponentially fast processing power. To this end, in this paper we propose a comprehensive and detailed review of all the possible cases of Quantum implementation into Metaverse environment. Moreover, we propose as a case scenario the deployment of a hybrid Quantum kernels approach to apply an optimized linear statistical method and fed the results to a classical supervised vector machine model to improve the scalability and performance of Metaverse applications. We believe this work would be a steppingstone for future research direction in order to develop Quantum-based Metaverse applications.


Keywords

Metaverse, Quantum Information Technology, Quantum Kernels, Hybrid-Quantum-Classical Machine Learning


Introduction

The term “Metaverse” is composed of two words, Meta and Universe [1] and refers to the virtual 3D words where a person can create an avatar or a character that can be similar or opposite of real-world persona and engage in various activities such as games, education, social, cultural, and so on. Although the public attention to Metaverse is relatively recent following the emerging announcement of tech giants’ companies such as Microsoft and Facebook announcements to create Metaverse related applications and products. Yet, the term itself is not new, in 1992 a science fiction novel named Snow Crash was published where the term “Metaverse” was discussed for the first time [2]. The story talks about a parallel virtual world where the main character can be a hero unlike the real life. Using hardware such as head mounted display (HMD) and technologies such as extended reality (XR) that includes virtual reality (VR), augmented reality (AR), and mixed reality (MR) [3], a person can fully be immersed in a virtual world where their characters are engaged in all sorts of activities from gaming and entertainment to education and cultural experiences. The Metaverse environment is being developed to create a parallel virtual universe where people from different locations and different continents can share the same experience. With this sudden and fast growing of Metaverse applications, critical issues are being discovered that urge immediate mitigations before Metaverse industry develops any further. Issues such as connectivity, complex data and computation, optimization, security, privacy, and so on, are an obstacle for Metaverse platforms and applications. For instance, the success of Metaverse application is directly related to the fast and accurate data processing including user’s movements and actions to mirror them in the virtual environment. Collecting heterogenous data from the real-world environment such as sound, movement, space, videos, and processing them simultaneously and momently is a very hard and complex task to perform. Any delay or inaccurate data output will directly affect the quality-of-experience (QoE) of the Metaverse application. Moreover, connectivity issues are also critical for the success of Metaverse applications. Metaverse relies extensively on low-latency and high throughput network services such as 5G and future 6G, which means that network connectivity issues can have serious consequences on the performance of Metaverse. Not to mention security and privacy issues such as identity theft, behavior analysis, personal information privacy, communication privacy, authentication, and so on, that are arising with the continuous development of Metaverse applications, however, to the best of our knowledge, there is no state-of-art to approach these issues and proposed effective and secure solutions yet. Currently, the research and studies regarding these the hardware, software, and security issues are very limited as the technology is fairly still advertised as a beta version.
On the other hand, Quantum information techniques has been an active topic for research and development recently. Quantum information promises an exponential faster computation power, unconditional security protocol, and a heuristic system optimization [4]. Quantum computers and processors are continuously being developed to solve complex problems in notably lesser time than today’s most powerful supper computers [5]. The concept of Quantum computing [68] was first introduced by the Russian-German mathematician Yuri Manin in 1980, however, Richard P. Feynman, the Nobel Prize physicist, was the first scientist to notice that it is not possible to simulate a Quantum physical system of ℝ particles by a classical computer, because of the size of a particle system (exponential in ℝ in Quantum physics) [7].
Quantum information technology can surely improve Metaverse environment and applications in term of fast and efficient computation, heuristic optimization, and unconditional security. To this end, in this paper, we propose a comprehensive survey of some of the most critical issues with Metaverse environment and we discuss the possible case scenarios where Quantum should be integrated to solve these issues. The main contribution of this paper can be depicted as follows:

We depict the software, security, and privacy issues with current Metaverse applications and discuss some of the available solutions based on recent state-of-arts.

We provide detailed case scenario of the implementation of Quantum technology into Metaverse applications and the areas where Quantum can improve Metaverse environments such as security, privacy, computation, simulation, advanced machine learning, and communication.

In this paper, we provide an overview framework design of a secure and heuristic optimized Metaverse environment based on Quantum technology which we believe to be the first work to adapt this approach at the moment. This work can be a paved step for future Quantum-based Metaverse’s research and development.


The rest of the paper is organized as follows: in Section 2, we depict the key concept of core technologies behind this paper including Metaverse and Quantum information technology. Section 3 discusses the main software and security issues with metaverse along with related state-of-the-arts’ solutions. Section 4 presents our main contribution that consists of various case studies where Quantum can be implemented into Metaverse for system optimization and security. We conclude this paper with Section 5.


Core Technologies

Metaverse
Lee et al. [9] defined Metaverse as a dual of a real world with a copy of it in a digital environment. The creation of Metaverse went through three main phases: digital twin phase, digital native phase, and co-existence twin phase. Digital twin can be defined as the soft copy of a physical entity duplicated in a digital environment. What makes digital twin valuable is the collected data and information from its respective physical twin. A digital twin is the main fundamental phase to create Metaverse. The real-world environment, such as objects, motions, temperature, dimension, along with the physical persona such as the real-world character. All these elements should be duplicated as a digital environment, avatars, and characters controlled by the one or multiple people. After creating the virtual environment and characters, the next step is to design a digital native. Digital native can be defined as the native content creation [10], where the avatar or the character in the Metaverse can create a scenario and content based on their need. Digital native is what makes Metaverse unique, avatars do not have to act based on a prewriting scripted scenario, instead, they act freely and create their own content. After creating a digital native content, the final stage of Metaverse is the co-existence between the real world and the digital world. The Metaverse dost not only allow avatars to use one static virtual world, but it opens the opportunity for them to use multiple Metaverse platforms at once, mimicking by that the real world. The interoperability between various and different platforms in Metaverse helps the users to create their unique contents and distribute it across platforms of their choice [11].
Metaverse is built upon various advanced technologies such as extended reality (XR) that includes VR, AR, and MR. AR is the technology that use computer vision to recognize real-world objects. It is a software-based technology, and it is used in various industries and applications such as face recognition, drone detection, movement tracking, and so on. Unlike AR, VR deploys the combination of software and hardware to create a digital environment for the users. Once the user puts the headsets, they will be completely disconnected from the real world and immersed into a virtual one. On the other hand, the mixing of real and virtual worlds to create new habitats and representations in which physical and digital items co-exist and interact in real time is known as mixed reality or polyplexity. On social networks currently, mobile AR offers the most mainstream MR options. People may be unaware that the Instagram AR filters they use are MR experiences. With a mix of really gorgeous holographic representations of humans, high-definition holographic 3D models, and the actual environment around them, Windows MR takes all of these user experiences to the next level. While XR is a broad word that encompasses immersive learning technologies such as VR, AR, and MR. These technologies add to or simulate reality through digital materials, and they are an effective approach to update corporate training programs. You may immerse your learners in a multimodal world that is more interactive, interesting, and successful over time by incorporating XR into your training. XR is the main technology behind the development of Metaverse. The foundation for learning about the best metaverse applications is a fundamental understanding of the metaverse and its characteristics. As the usage of technologies like as VR, AR, and XR grows by the day, it's only natural to question how they may be used to increase metaverse instances in the real world. In answer to concerns about metaverse uses, gaming and social media are two of the most common responses. However, there are a slew of additional interesting metaverse applications that demonstrate the Metaverse's full potential in the future. Fig. 1 depicts the top five metaverse applications in different industries. Table 1 presents a summary of the recent state-of-the-art discussing Metaverse application in various industries [1224] as depicted below.

Fig. 1. Metaverse applications.


Healthcare: In the healthcare industry, the use of AR-based healthcare services is considered one of the most used cases for medical Metaverse technology. AR has emerged as a crucial tool for improving the experience and knowledge base of medical students. Surgical support tools like Microsoft Hololens, for example, practitioners in a variety of surgical procedures. This innovation is among the most extensively utilized Metaverse technologies for improving surgical precision, patterns, and speed. In addition to pre-operative imaging like magnetic resonance imaging (MRI), computed tomography (CT), and 3D scans, AR headgear can be utilized to visualize critical and essential patient information. As a consequence, the Metaverse might make healthcare information like heart rate easier to track. The Metaverse instances further point to the possibility of using AR technology to improve vein detection. As a result, Metaverse technology can help with the difficulty of spotting a vessel, especially whenever the skin is strongly tinted or the blood vessels are tiny. Graphical representations technology such as CT scans and X-rays can be utilized to shift healthcare to the Metaverse as well, considering a virtual environment where medical specialists and health professionals could explore and navigate through the insides of individuals' organs for a much more precise diagnosis.

Real estate: Real estate industry is defined as one of the first services to benefit from Metaverse platforms and applications. Since Metaverse is mainly relying on VR technology to provide real and enhanced experience for the users, deploying VR and Metaverse, real estate applications will be capable of providing the client and user with realistic and immersive experience. Real estate brokers, for example, may use VR to provide buyers with interactive digital tours of homes. Furthermore, the Metaverse's potential opens up new possibilities for incorporating other multimedia components into VR trips. For instance, VR real estate tours might incorporate narrative as well as ambient soundscapes, light, and sound effects. Each of these features, when integrated in its most popular real estate metaverse applications, may provide users a near-real-time view of the listings. As a result, real estate advertising agencies may find that essentially allowing clients to visualize the property in real time increases consumer trust. Customers could be satisfied in a variety of factors before purchasing items, and real estate brokers can save a lot of time and money. Brokers could also use metaverse cases to create custom experiences according to their customers' tastes.

Education: Recently, Metaverse has gained more attention of academia and industry to be applied for education sector. The visualization of the studied curriculum can be integrated in VR where students will be able to efficiently attend courses across the globe, which will radically change the traditional education systems. Students at various learning institutions may benefit from the best metaverse applications in the education industry, which can assist in developing interesting and immersive learning environments. VR might facilitate the quick and frequent discovery of faults while also allowing for real-time modification. Most importantly, the greatest Metaverse apps in the education industry may help students overcome barriers to learning. Any language may be included into a Metaverse system for teaching, therefore eliminating the language barrier.

Military: The military industry is another high-ranking sector in the metaverse industries list. Army VR and AR technologies show the Metaverse's capacity to support practical applications. Probably one of the best instances of military metaverse technology is tactical augmented reality, or TAR. It's similar to night-vision goggles, but with a few extra characteristics. TAR could rapidly display a soldier's exact location as well as the locations of allies and foes. In addition, TAR has shown to be a great alternative to current handheld navigation gadgets and headsets. Synthetic Competence Development is also addressed in the military industry's Metaverse examples. It's an augmented reality system that allows soldiers to practice in a realistic environment. By recreating physically and mentally intense combat scenarios in virtual locations, the Synthetic Training Environment delivers an immersive training experience.

Table 1. Summary of Metaverse use cases in different industries
Industrial application Study Proposed application
Healthcare [12] Collaborative working between doctors across the globe
Interactive education for medical students
Telehealth clinical care and improved online regular health screening and patient monitoring.
[13] Socioemotional environments for real-time interactions, collaborations, and knowledge sharing between patients
[14] Telepresence for telemedicine for an improved remote treatment
Digital Twins of patients to enhance the efficacy of treatment
[15] Medical Internet of Things (MIoT) using AR and VR glasses
Holographic construction and emulation of patient’s case
Collaborative medical and clinical research 
Chronic disease management using in-home care and outpatient attendance and consultation
[16] Remote surgery and augmented reality surgery 
Holographic anatomy modeling to improve diagnosis and surgery planning
Medical database visualization and improved big data analysis
Psychotherapy support and virtual support group meetings
Education, training, and virtual simulation 
Real estate [17] Virtual reality-based property tours that allow customers to visit and review as many properties as possible while reducing the travel time to zero
Education [18] Improving simulations, experiments, and practices for students across the globe
[19] Interactive virtual classes 
[20] Enhanced anatomic models and VR goggle for dental education
[21] Improved self-learning, collaborative learning, and student support using virtual classes with students as avatars
Military [22] Intense virtual battle simulation and training
[23] Using metaverse to simulate the trauma created by wars to stimulate human society’s interest in peace
Manufacturing [24] Building digital factories on metaverse in order to replicate and analyze operations and production processes, predict future errors, and optimize production and logistic line


Manufacturing: VR applications, as one of the most popular Metaverse technologies, may assist instruct employees on safety procedures while also encouraging involvement in risk simulations. As a consequence, metaverse applications have the potential to significantly reduce the likelihood of accidents. In the long run, the most prominent metaverse applications in production might help with the development of superior goods. A virtual reality headset, for example, can assist producers in thoroughly inspecting all aspects of a product. Furthermore, metaverse applications aid in landscape design for industrial plants and improved equipment location. Ford is a well-known brand that is utilizing virtual reality technology to gain access to its locked-down cars via a metaverse.

Quantum Information Technology
The subject of Quantum computing brings together ideas from classical information theory, computer science, and Quantum physics [9] (Fig. 2). Theatrically, a Quantum computer is capable of solving problems that would be intractable on conventional computers. Russian-German mathematician Yuri Manin was the first to propose the idea of Quantum computing in his book Computable and Non-computable, published in 1980 [58, 10, 11, 25, 26]. Two years later, the Nobel Prize winner physicist Richard P. Feynman published an article when he noticed that a Quantum physical system of ℝ particles could not be simulated by an ordinary computer without an exponential slowdown in the efficiency of the simulation [8].

Fig. 2. IBM representation of Quantum Computer


However, a system of ℝ particles in classical physics can be simulated well with only a polynomial slowdown. Accordingly, the reason is that the description size of a particle system is linear in ℝ in classical physics but exponential in ℝ in Quantum physics [2629]. Thus, Feynman proposed the use of a computer-based on Quantum physics laws to solve this problem. A classical computer uses transistors to process information in the form of various combinations of 0 and 1 to accomplish the calculations [30]; the computer processing power depends on the number of transistors. On the other way, a Quantum computer uses the Quantum mechanical states of elementary particles, specifically the internal angular momentum known as spin. In this case, a spin-up is accorded to a binary one, and spin down is accorded to binary 0. According to Quantum physics laws, every elementary particle can be in multiple states simultaneously. Thus, the spin can be up and down at the same time, introducing the concept of Qbit [31, 32]. Instead of two values, 0 or 1, a Qbit stores proportion of the two values 0 and 1 at the same time. A computer with n Qbit is capable of performing 2n combinations synchronously. This functionality speeds up the computations exponentially, allowing a Quantum computer to solve hard mathematical problems in a short time.


Security Issues in Metaverse Environment

Metaverse is known as Web 3.0, a novel generation of web-based technology where the user enters a digital virtual world that can either be a mirror of reality or a new designed world. Metaverse technology is still at an infancy stage, thus, multiple security and privacy issues are yet to be addressed. In this section, we will depict the most critical security issues with Metaverse environment.

Identity theft: Identity management is critical in the metaverse for enormous users/avatars using Metaverse services [33]. Users’/avatars’ identities in the Metaverse can be unlawfully taken, impersonated, and authentication difficulties can arise between virtual worlds.

Impersonation: An attacker can use impersonation to obtain access to the content or network in the metaverse by impersonating another authorized entity [34]. Hackers, for example, can infiltrate helmets or wearable gadgets and use them as entry points to mimic the victim and obtain access to his or her service credentials illegally [35]. Real-world location traceability: Since Metaverse is an openly shared and interoperated environment, player have the possibility to tack other player’s location using the name tag in displayed on top of each one of them. Moreover, hackers may get the user’s location by compromising VR headsets as well. The user’s location is critical personal and private information that should be secured in Metaverse environment for the safety of the users.

Cross-platforms authentication: As we explained earlier, Metaverse is designed to support interconnectivity between multiple platforms to mimic by that real-world case scenarios. For example, a character or an avatar should be able to attend a virtual Metaverse-based campus lecture, once the virtual classes are finished, the same avatar may exist the education environment and immediately enters an entertaining environment. Information and data about the avatar are shared between multiple Metaverse platforms, thus, a secure, reliable, and fast interconnected authentication mechanism should be designed while maintaining the user’s private information secured. This problem is also critical for both security measurements and QoE level.

Private data leakage: to assure the required quality-of-service (QoS) and QoE level in Metaverse-based platforms and applications, data regarding users, platforms, hardware, and software should be uploaded to their respective servers for real-time big data analysis. During the phase of data transmission, communication, and storage, private and sensitive data may be leaked and viewed by an unauthorized entity. To this end, securing cloud/edge-based storage and processing shall be highly considered to prevent such attacks from occurring. Moreover, the computation and processing rate of data should be improved exponentially to support real-time optimization and management.

Network threats: Metaverse applications require continuous data communication across multiple platforms and between multiple users. The data is transmitted upon classical network channels such as 5G networks. Thus, it is prone to various security attacks such as spoofing attack, Sybil attacks, distributed denial-of-service (DDoS) attacks, and so on. Enhancing the network security and performance will by its role enhance the privacy and security of communicated data in a Metaverse environment [36, 37].

Fig. 3. Overview on Quantum applications for Metaverse.


The implementation of Quantum technology in Metaverse environment can be applied into multiple utilizations as mentioned above. However, we believe that it is most feasible when deployed for security reasons and for computations to enhance machine learning algorithm and reach the required heuristic optimization level. To this end, in this paper, we propose as a case scenario the deployment of a hybrid Quantum kernels approach to apply an optimized linear statistical method and fed the results to a classical supervised vector machine model to improve the scalability and performance of Metaverse applications.

Quantum Kernel Machine Learning: A Case Study

Kernel methods in machine learning in general allows the application of a linear classification to nonlinear problems [36, 37]. Applying kernel methods on Metaverse platforms and applications helps us mapping the nonlinear nature of Metaverse generated data into a higher dimensional space, which by itself facilitate the classification and lead to an exponential acceleration in the training and learning phases and produce much more accurate results. Moreover, to reduce the complexity of mapping data from 2D into 3D high-dimensional space, we propose in the paper the deployment of Quantum kernel method, which benefits from the computational power of a Quantum server to execute Quantum kernel machine learning faster and more efficiently.
Classically, to deploy kernel machine learning methods, we use the following kernel function such as:


Proposed Quantum Approaches for Metaverse

System Overview

Metaverse is currently relying on classical computational resource to host the provided services. This approach has its limitations in term of security and performance. To this end, we propose in this paper an overview of all possible case scenarios where Quantum information technology could support Metaverse environment, enhance its security, and provide the desirable heuristic optimization. Notably, Quantum machine learning it the most promising Quantum-based field to be implemented into Metaverse. Quantum machine learning has proved its potentials and highly scalable and optimized performance in various domains and sectors from finance, manufacturing, and pharmaceutical field.
Regarding Metaverse environment, Quantum information technology is capable of enhancing the system’s security and privacy, improving the computational scales, and optimizing the output, improving the communication, and securing the network channels, providing an absolute randomness for Metaverse-based simulations, support machine learning application in Metaverse by integrating Quantum machine learning, and so on. The detailed information about Quantum approaches in Metaverse can be depicted in Fig. 3 and in the follow points.

Security: Quantum computing is commonly viewed as a potential threat, however since most of our connections are kept in the Metaverse, we will need Quantum resilient protection to secure all activities and business. Quantum resistance technology could be necessary to provide data integrity from methods like Shor’s algorithm. Contemplate blockchains that can withstand quantum attacks.

Randomness: To create authenticity, metaverses will require a measure of randomness to guarantee that occupants and their ways do not manipulate the system. Quantum randomness, which entails using a series of qubits to create random bits instead of an arbitrarily produced integer, is one technique to ensure that there is indeed a high level of uncertainty. Quantum random number generation, or QRNGs, is a field wherein Quantum dice is involved.

Computation: One of the possible applications of Quantum computing is to make an application highly efficient. Researchers have been developing applications for optimization jobs, and with the massive amounts of processing and modeling required in the metaverse, each advantage that can be utilized to improve the experience will almost likely be utilized. Researchers are developing a number of Quantum algorithms that might be beneficial in the alternative Metaverse.

Communication: The Quantum key distribution (QKD) protocol can be used to improve the security of transmission in the Metaverse. QKD is a secure method of sending secret keys that can only be read by two or more people. The networking method takes advantage of quantum physics events to send encryption techniques in a reliable and safe manner.


(1)


Noting that K refers to kernel function, both are the n dimensional input, in this case in a two-dimensional input, f is a map from one dimension to a higher one. However, in a Quantum kernel machine learning environment, the Quantum feature map is deployed to map the classical feature vector into the Quantum Hilbert space such as follows:

(2)


and

(3)


Kernel is used to transform data from regular inputs into a higher required form to facilitate mapping and training. In this paper, we deploy a Quantum kernel method for Metaverse-based video classification and regression. For the purpose of this study, we used IBM’s Quantum Lab platform with Qiskit software, we encoded the code based on Python using 2 CPUs and 6 GB RAM on a Linux operating system. After preparing the training dataset, we run Quantum kernel method using Qiskit’s ZZFeatureMap based on a second-order Pauli-Z evolution circuit, and the BasicAer qasm_simulator using 1024 shots in order to calculate the kernel matrix. The benefits of using Quantum kernel is that it allows us to precompute and plot the training kernel matrix, as shown in Fig. 4(a), the training Quantum kernel matrix and classification scores 1.0. We fed the obtained results to an unsupervised machine learning algorithm for clustering. Since the class labels are obtained, we can directly precompute them using Quantum kernel to get a clustering Quantum kernel matrix. As shown in Fig. 4(b), the clustering scores 0.7, better results than classical kernel methods.
The results obtained using Quantum kernel can be fed to a classical supervised vector machine model for faster computation, which by its turn, improves the scalability and performance of Metaverse applications. As we discussed previously in this paper, Quantum technology is capable of improving Metaverse application in various sectors including sectors including security, communication, and computation. One of the earliest adaptation of Quantum into Metaverse would be in computation and machine learning applications since Quantum machine learning has been highly adapted and attracts the interest of both researches and industries.
This paper provides an overview of the possible implementations of Quantum technology into Metaverse, proving a simple case study of Quantum kernel, and hoping it will be a step for further research and development in this area. As a future direction of this work, we will deploy Quantum algorithms for optimizations in order to improve Metaverse environments and prove the feasibility of the convergence of Quantum technology with Metaverse.

Fig. 4. (a) Quantum kernel precomputed classification and (b) clustering score of Quantum kernel matrix.



Conclusion

The current Metaverse applications has critical challenges in both hardware and software that urge immediate mitigation. Issues such as security, privacy, connectivity, and computation complexity are the main reasons behind the slow integration of Metaverse into real-world applications. On the other hand, Quantum information technology is currently a fast-growing research field. Quantum technology promises fast, optimized, and scalable computation results due to its exponentially fast processing power. Moreover, Quantum is being deployed actively in security and privacy areas to create a Quantum-resistant applications. Quantum can surely benefit Metaverse in various applications including security and processing, yet, to the best of knowledge, no state-of-the-art has discussed a Quantum approach for Metaverse. To this end, in this paper we propose a comprehensive and detailed review of all the possible cases of Quantum implementation into Metaverse environment. Moreover, we propose as a case scenario the deployment of a hybrid Quantum kernels approach to apply an optimized linear statistical method to the complex, heterogenous, and streaming nature of Metaverse data, and fed the results to a classical supervised vector machine model for faster computation, which by its turn, improves the scalability and performance of Metaverse applications.


Author’s Contributions

Conceptualization, HJK. Data curation, HJK, AEA. Formal analysis, HJK, AEA. Funding acquisition, HJK. Investigation, HJK, AEA, JHP. Methodology, HJK, AEA. Project administration, JHP. Resources, HJK. Software, HJK, AEA. Supervision, JHP. Visualization, HJK. Writing – original draft, HJK, AEA, JHP. Writing – review & editing, HJK, AEA, JHP.


Funding

This work was supported by the Soonchunhyang University Research Fund (No. 10220011).


Competing Interests

The authors declare that they have no competing interests.


Author Biography

Author
Name : Hyuk-Jun Kwon
Affiliation : Dept. of Economics & Finance, Soonchunhyang University, Asan, South Korea
Biography : Hyuk-Jun Kwon is a professor of Economics and Finance at Soonchunhyang University, Korea. He received his Ph.D. in Information System from Graduate School of Information at Yonsei University, Korea. He has published many research papers in international journals and conferences. He has been serve as program committee for international conferences and workshop; UNESST, CSA, ISA, and so on. His works have been published in Journals such as Journal of Computational Information Systems, and Computing Informatics and Blockchain. His areas of concern are Multimedia Security, Information Security Management, Blockchain Systems and Fintech.

Author
Name : Abir El Azzaoui
Affiliation : Dept. of Computer Science and Engineering, Seoul National University of Science & Technology (SeoulTech), Seoul, Korea
Biography : Abir El Azzaoui is currently pursuing her Ph.D degree in computer science and engineering, Seoul National University of Science and Technology with the Ubiquitous Computing Security (UCS) Laboratory, under the supervision of Prof. Jong Hyuk Park. She received a B.S. degree in computer science from the University of Picardie Jules-Verne, Amiens, France, and a master’s degree in computer science and engineering, from Seoul National University of Science and Technology, Seoul, South Korea. Some of her research findings are published in the most cited journals. Her current research interests include Quantum communication, post-Quantum security, Blockchain, Internet-of-Things (IoT) security, and cloud security. She is also a reviewer of IEEE Access journal, IEEE TII journal, and HCIS journal.

Author
Name : Prof. Jong Hyuk (James J.) Park
Affiliation : Dept. of Computer Science and Engineering, Seoul National University of Science & Technology (SeoulTech), Seoul, Korea
Biography : Hereceived Ph.D. degrees in the Graduate School of Information Security from Korea University, Korea. He is a professor at the Department of Computer Science and Engineering and Department of Interdisciplinary Bio IT Materials, Seoul National University of Science and Technology (SeoulTech), Korea. He is editor-in-chief of Human-centric Computing and Information Sciences (HCIS) by KIPS, The Journal of Information Processing Systems (JIPS) by KIPS, and Journal of Convergence (JoC) by KIPS CSWRG. His research interests include IoT, Human-centric Ubiquitous Computing, Information Security, Digital Forensics, Vehicular Cloud Computing, Multimedia Computing, and so on. In addition, he has been serving as a Guest Editor for international journals by some publishers: Springer, Elsevier, John Wiley, Oxford University Press, Emerald, Inderscience, and MDPI.



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Hyuk-Jun Kwon1, Abir El Azzaoui2, and Jong Hyuk Park2, *, MetaQ: A Quantum Approach for Secure and Optimized Metaverse Environment, Article number: 12:42 (2022) Cite this article 2 Accesses

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  • Received23 March 2022
  • Accepted24 May 2022
  • Published15 September 2022
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