Rodrigo Dutra Garcia, Gowri Ramachandran, Christian Esteve Rothenberg, Daniel Macêdo Batista · 5 authors
The transition to 6G networks is expected to support a broader range of user-centric applications. As these applications expand, Quality of Experience (QoE) has emerged as a key metric for evaluating user satisfaction. However, the use of centralized systems lacks transparency and limits users’ ability to govern their data usage. It also introduces challenges in managing QoE data while preserving privacy. At the same time, verification mechanisms are needed that allow regulators to evaluate compliance without exposing confidential business information. To address this, we propose a decentralized, privacy-preserving QoE system that integrates blockchain with fully homomorphic encryption (FHE). This design enables transparent evaluations between users and service providers by supporting computations directly on encrypted data, ensuring that all information remains protected throughout the process. Users contribute QoE metrics through a decentralized infrastructure and retain control over their data. Regulators can monitor compliance without accessing raw data, and service providers can use encrypted QoE data to perform privacy-preserving computations via smart contracts without relying on a central authority. We developed a proof-of-concept integrating FHE smart contracts compatible with Ethereum Virtual Machine (EVM) blockchains and evaluated their performance using a video streaming dataset. Our results show that encryption and FHE operations consistently occur within milliseconds when tested in a local environment. We also evaluated these operations on a public blockchain testnet. In this setting, our system adds a millisecond-scale delay while supporting privacy-preserving computations directly on encrypted user data.
The Bitcoin network comprises numerous nodes, necessitating users to invest significant network requests and time in comprehending its network topology. In this paper, we propose a Bitcoin network topology discovery algorithm that utilizes lightweight probe nodes to facilitate rapid transmission of network protocols. Building upon this, we introduce a node layer clustering algorithm based on filtering stable network nodes, enabling parallel discovery of the network topology. Additionally, we present an adaptive method for dynamically displaying the layered structure of the network topology. Experimental results demonstrate that our proposed method reduces communication overhead by approximately 72.16% when achieving a 95% similarity in network topology. Furthermore, the algorithm is applicable for discovering the network topology in other blockchain networks with similar structures.
This paper aims to analyze and improve user experience (UX) in cryptocurrency applications. The study takes an interdisciplinary approach combining UX design principles, behavioral economics, and fintech innovation. Key UX challenges are identified, including cognitive complexity, security concerns, limited integration with traditional finance, and the impact of volatility. Innovative solutions are proposed with a focus on intuitive interfaces, educational elements and hybrid financial instruments. As an example, a cryptocurrency card with a line of credit function was presented. Quantitative results show a significant improvement in usability metrics: SUS scores improved, user retention rates increased, and key transaction times decreased. The study concludes that improving UX is critical for cryptocurrency adoption and integration into the global financial system. Future research directions include longitudinal studies on the impact of UX, developing standardized metrics, and exploring cultural factors of cryptocurrency interface perception.
This study delves into the relationship between emotional trends from X platform data and the market dynamics of well-known cryptocurrencies Cardano, Binance, Fantom, Matic, and Ripple over the period from October 2022 to March 2023. Leveraging SenticNet, we identified emotions like Fear and Anxiety, Rage and Anger, Grief and Sadness, Delight and Pleasantness, Enthusiasm and Eagerness, and Delight and Joy. Following data extraction, we segmented each month into bi-weekly intervals, replicating this process for price data obtained from Finance-Yahoo. Consequently, a comparative analysis was conducted, establishing connections between emotional trends observed across bi-weekly intervals and cryptocurrency prices, uncovering significant correlations between emotional sentiments and coin valuations.
The emergence of Distributed Ledger Technologies (DLT) in the past decade has challenged our imagination to discover new, innovative and disruptive solutions to problems in domains ranging from finance and healthcare to supply chain and Smart Cities. However, the enormous energy consumption that has been observed in some of the most successful DLT applications raises the question of their long term sustainability. This article reviews the standardization efforts of the International Telecommunications Union (ITU) to provide guidelines to regulators and policy makers for making informed decisions on the applicability and sustainability of DLT architectures from the point of view of energy consumption.
Simone Casale-Brunet, Marco Mattavelli, Leonardo Chiariglione
In recent years, the concept of the metaverse has evolved significantly, with the aim of defining richer immersive and interactive environments that can support various types of virtual experiences and interactions among users. This evolution has given rise to several metaverse platforms that utilize blockchain technology and non-fungible tokens (NFTs) to establish ownership of metaverse elements and attach features and information to them. This article seeks to delve into the complexity and heterogeneity of the data involved in these metaverse platforms and highlight some of the dynamics and features that make them unique. Additionally, the paper introduces a metaverse analysis tool developed by the authors, which leverages machine learning techniques to collect and analyze daily data, including blockchain transactions, platform-specific metadata, and social media trends. The experimental results of our approach are presented with a use-case scenario focused on the trading of digital parcels, commonly referred to as metaverse real estate. This scenario allows us to demonstrate the effectiveness of our tool and showcase the potential of using machine learning techniques to analyze and gain insights into the metaverse ecosystem.
The adoption of non-fungible tokens (NFTs) has revolutionized digital art transactions, providing artists with unprecedented opportunities to tokenize and monetize their generative creations, leading to increased scrutiny and demand within blockchain-oriented marketplaces. The pricing of NFT artworks, however, exhibits substantial variations within and across collections, influenced by various factors. This study aims to investigate the relationship between visual features and pricing, shedding light on the variations underlying the pricing of NFTs. First, measures of both computational aesthetics and visual complexity were applied to extract multi-faceted visual aesthetic features, encompassing aesthetic factors such as color and composition as well as complexity factors like entropy. Second, with extracted visual aesthetic features and preprocessed price data, the study proceeds to conduct correlation analysis within collections and statistical modeling across collections. Through these approaches, we reveal a moderate correlation between visual features and prices within collections, while also identifying different influential visual features across collections. The differential performance of price models highlights the distinctiveness and unique pricing characteristics of NFT collections.
Evaluating1 the popularity of content, developing personalized recommendation algorithms, and optimizing advertising revenue are crucial aspects of Over-the-Top (OTT) media content services. In order to achieve these goals, accurate viewership measurement of OTT content is essential. However, due to the stringent security policies of mobile platforms, it has been challenging to propose an easy and reliable method for measuring viewership. In this paper, we propose an efficient and secure viewership measurement technique for OTT content on the iOS platforms. The proposed technique utilizes audio filtering and zero-knowledge proof techniques to address the challenges. By leveraging audio filtering, the content can be quickly identified, enabling accurate viewership measurement. Additionally, the use of zero-knowledge proof ensures the protection of users' personal information, preventing indiscriminate acquisition of user data in OTT services.
Recently, the concept of metaverse has been rapidly emerging, which highly expands the human living space. Specifically, 3D models are at the heart of building a vast metaverse space, so a massive number of 3D models are needed. Existing 3D model libraries and platforms have achieved great results. However, most of them are unscalable, insufficiently open, inefficient to collect, and at risk of service disruption and data corruption. Therefore, we propose and implement Web3DP, a crowdsourcing platform for 3D models based on Web3 (a.k.a. Web 3.0) infrastructure. By using the decentralized blockchain technology, Web3DP has the advantages of transparency, auditability, traceability, data tamper-proof, high file transfer efficiency, and service stability. Experiments are conducted to validate the performance of the proposed platform. It illustrates that Web3DP shows better file transmission capabilities with an acceptable transaction fee to facilitate 3D model collecting and managing for metaverse, games, cultural heritage, etc.
Simone Casale-Brunet, Leonardo Chiariglione, Marco Mattavelli
In recent years the concept of metaverse has evolved in the attempt of defining richer immersive and interactive environments supporting various types of virtual experiences and interactions among users. This has led to the emergence of various different metaverse platforms that utilize blockchain technology and non-fungible tokens (NFTs) to establish ownership of metaverse elements and attach features and information to it. This article will delve into the heterogeneity of the data involved in these metaverse platforms, as well as highlight some dynamics and features of them. Moreover, the paper introduces a metaverse analysis tool developed by the authors, which leverages machine learning techniques to collect and analyze daily data, including blockchain transactions, platform-specific metadata, and social media trends. Experimental results are reported are presented with a use-case scenario focused on the trading of digital parcels, commonly referred to as metaverse real estate.
The Metaverse is gaining attention among academics as maturing technologies empower the promises and envisagements of a multi-purpose, integrated virtual environment. An interactive and immersive socialization experience between people is one of the promises of the Metaverse. In spite of the rapid advancements in current technologies, the computation required for a smooth, seamless and immersive socialization experience in the Metaverse is overbearing, and the accumulated user experience is essential to be considered. The computation burden calls for computation offloading, where the integration of virtual and physical world scenes is offloaded to an edge server. This paper introduces a novel Quality-of-Service (QoS) model for the accumulated experience in multi-user socialization on a multichannel wireless network. This QoS model utilizes deep reinforcement learning approaches to find the near-optimal channel resource allocation. Comprehensive experiments demonstrate that the adoption of the QoS model enhances the overall socialization experience.
Reza Aria, Norm Archer, Moein Khanlari, Bharat Shah
This paper summarizes the work of many different authors, industries, and countries by introducing important and influential factors that will help in the development, successful adoption, and sustainable use of the Web3/metaverse and its applications. We introduce a few important factors derived from the current state-of-the-art literature, including four essential elements including (1) appropriate decentralization, (2) good user experience, (3) appropriate translation and synchronization to the real world, and (4) a viable economy, which are required for appropriate implementation of a metaverse and its applications. The future of Web3 is all about decentralization, and blockchain can play a significant part in the development of the Metaverse. This paper also sheds light on some of the most relevant open issues and challenges currently facing the Web3/metaverse and its applications, with the hope that this discourse will help to encourage the development of appropriate solutions.
Abstract The potential of the metaverse in the field of education is an area of increasing interest, with many researchers exploring the space to increase the ease and efficacy of student education while reducing time and labor requirements to deliver effective teaching. However, there has been little work into the systematic and technological aspects of delivering education through the metaverse. To fill this gap, we propose a metaverse education system that takes good advantages of virtual reality and Web3 blockchain techologies to create a social learning environment. With this added emphasis on social aspects, learners are able to socialize and engage in collaborative efforts to improve their own knowledge. Using blockchain technology, the system can also help to ensure security and transparency while also keeping progression and grading fair for all participating students.
Compact block, which replaces transactions in the block with their hashes, is an effective means to speed up block propagation in the Bitcoin network. The compact block mechanism in Bitcoin counts on the fact that many nodes may already have the transactions (or most of the transactions) in the block, therefore sending the complete block containing the full transactions is unnecessary. This fact, however, does not hold in the Ethereum network. Adopting compact block directly in Ethereum may degrade the block propagation speed significantly because the probability of a node not having a transaction in the sending block is relatively high in Ethereum and requesting the missing transactions after receiving the compact block takes much additional time. To investigate the factors that prevent compact block in Ethereum, we set up probe nodes to collect data from Ethereum MainNet and performed data analysis. Our analysis results indicate that the missing transactions could be attributed to factors such as small transaction pools, network latency, and miners' selfish behaviors. Moreover, simply enlarging the transaction pool and using the prediction algorithm proposed for Bitcoin to predict the missing transactions and prefetch them do not work for Ethereum. This article proposes hybrid-compact block (HCB), an efficient compact block propagation scheme for Ethereum and other similar blockchains. First, we develop a Secondary Pool to store the low-fee transactions, which are removed from the primary transaction pool, to conserve storage space. As simple auxiliary storage, the Secondary Pool does not affect the normal block processing of the primary pool in Ethereum. Second, we design a machine learning-based transaction prediction module to precisely predict the missing transactions caused by network latency and selfish behaviors. We implemented our HCB scheme and other compact-block-like schemes (as benchmarks) and deployed a number of worldwide nodes over Ethereum MainNet to experimentally investigate them. Experimental results show that HCB performs best among the existing compact-block-like schemes and can reduce propagation time by more than half with respect to the current block propagation scheme in Ethereum.
Since Facebook officially changed its name to Metaverse in Oct. 2021, the metaverse has become a new norm of social networks and three-dimensional (3D) virtual worlds. The metaverse aims to bring 3D immersive and personalized experiences to users by leveraging many pertinent technologies. Despite great attention and benefits, a natural question in the metaverse is how to secure its users' digital content and data. In this regard, blockchain is a promising solution owing to its distinct features of decentralization, immutability, and transparency. To better understand the role of blockchain in the metaverse, we aim to provide an extensive survey on the applications of blockchain for the metaverse. We first present a preliminary to blockchain and the metaverse and highlight the motivations behind the use of blockchain for the metaverse. Next, we extensively discuss blockchain-based methods for the metaverse from technical perspectives, such as data acquisition, data storage, data sharing, data interoperability, and data privacy preservation. For each perspective, we first discuss the technical challenges of the metaverse and then highlight how blockchain can help. Moreover, we investigate the impact of blockchain on key-enabling technologies in the metaverse, including Internet-of-Things, digital twins, multi-sensory and immersive applications, artificial intelligence, and big data. We also present some major projects to showcase the role of blockchain in metaverse applications and services. Finally, we present some promising directions to drive further research innovations and developments towards the use of blockchain in the metaverse in the future.
Taras Maksymyuk, Juraj Gazda, Gabriel Bugár, Vladimír Gazda · 6 authors
The future of networking will be driven by the current emerging trends of combining the physical and virtual realities in cyberspace. Considering the ambient pandemic challenges, the role of virtual and augmented reality will definitely grow over time by transforming into the paradigm of the Metaverse of Things, where each person, thing or other entity will simultaneously exist within multiple synchronized realities. In this paper, we propose a novel framework for future metaverse applications composed of multiple synchronized data flows from multiple operators through multiple wearable devices and with different quality requirements. A new service quality model is proposed based on a customizable utility function for each individual data flow. The proposed approach is based on dynamic fine-grained data flow allocation and service selection using non-fungible tokens, which can be traded over the blockchain among users and operators in a decentralized mobile network environment.
Lik‐Hang Lee, Tristan Braud, Pengyuan Zhou, Lin Wang · 9 authors
Since the popularisation of the Internet in the 1990s, the cyberspace has kept evolving. We have created various computer-mediated virtual environments including social networks, video conferencing, virtual 3D worlds (e.g., VR Chat), augmented reality applications (e.g., Pokemon Go), and Non-Fungible Token Games (e.g., Upland). Such virtual environments, albeit non-perpetual and unconnected, have bought us various degrees of digital transformation. The term `metaverse' has been coined to further facilitate the digital transformation in every aspect of our physical lives. At the core of the metaverse stands the vision of an immersive Internet as a gigantic, unified, persistent, and shared realm. While the metaverse may seem futuristic, catalysed by emerging technologies such as Extended Reality, 5G, and Artificial Intelligence, the digital `big bang' of our cyberspace is not far away. This survey paper presents the first effort to offer a comprehensive framework that examines the latest metaverse development under the dimensions of state-of-the-art technologies and metaverse ecosystems, and illustrates the possibility of the digital `big bang'. First, technologies are the enablers that drive the transition from the current Internet to the metaverse. We thus examine eight enabling technologies rigorously - Extended Reality, User Interactivity (Human-Computer Interaction), Artificial Intelligence, Blockchain, Computer Vision, Edge and Cloud computing, and Future Mobile Networks. In terms of applications, the metaverse ecosystem allows human users to live and play within a self-sustaining, persistent, and shared realm. Therefore, we discuss six user-centric factors -- Avatar, Content Creation, Virtual Economy, Social Acceptability, Security and Privacy, and Trust and Accountability. Finally, we propose a concrete research agenda for the development of the metaverse.
Lik‐Hang Lee, Tristan Braud, Pengyuan Zhou, Lin Wang · 9 authors
Since the popularisation of the Internet in the 1990s, the cyberspace has kept evolving. We have created various computer-mediated virtual environments, including social networks, video conferencing, virtual 3D worlds (e.g., VR Chat), augmented reality applications (e.g., Pokémon Go), and Non-Fungible Token Games (e.g., Upland). Such virtual environments, albeit non-perpetual and unconnected, have brought us various degrees of digital transformation. The term “metaverse” has been coined to facilitate further digital transformation in every aspect of our physical lives. At the core of the metaverse stands the vision of an immersive Internet as a gigantic, unified, persistent, and shared realm. While the metaverse may seem futuristic, catalyzed by emerging technologies such as Extended Reality, 5G, and Artificial Intelligence, the digital “big bang” of our cyberspace is not far away. This survey presents the first effort to offer a comprehensive framework that examines the latest metaverse development under the dimensions of state-of-the-art technologies and metaverse ecosystems and illustrates the possibility of the digital “big bang”. It is essential to highlight that the metaverse encompasses diverse technologies and ecosystems, calling it an interdisciplinary and emerging field. Its primary objective is to provide users with satisfactory and interactive experiences. First, technologies are the enablers that drive the transition from the current Internet to the metaverse. We thus examine eight enabling technologies rigorously – Extended Reality, User Interactivity (Human-Computer Interaction), Artificial Intelligence, Blockchain, Computer Vision, IoT and Robotics, Edge and Cloud computing, and Future Mobile Networks. In terms of applications, the metaverse ecosystem allows human users to live and play within a self-sustaining, persistent, and shared realm. Therefore, we discuss six user-centric factors – Avatar, Content Creation, Virtual Economy, Social Acceptability, Security and Privacy, and Trust and Accountability. Finally, we propose a concrete research agenda for developing the metaverse.
Anderson Melo de Morais, Jorge da Silva Correia Neto, Robson Wagner Albuquerque de Medeiros, Obionor de Oliveira Nóbrega · 5 authors
Education generates a considerable amount of data and information, it is necessary to manage this data securely, avoiding problems of falsification and tampering with diplomas, certificates, and other important student documents. In addition, distance learning is becoming more popular due to the Covid-19 pandemic period, where courses are offered in virtual learning environments such as Moodle. Blockchain technology can be used as a tool to ensure the security of data managed by Moodle. However, there is a gap in current state-of-the-art solutions for integrating these data with Blockchain platforms. This work proposes BlockMoodle, a solution developed to integrate Moodle with Blockchain Ethereum. This work also performs an analysis of the financial cost of using the tool. In addition, a performance evaluation of the proposed solution is also carried out considering different usage scenarios. Finally, the conclusions and future work to be developed are presented.
Christoph Kinkeldey, Jean‐Daniel Fekete, Tanja Blascheck, Petra Isenberg
We present BitConduite, a visual analytics approach for explorative analysis of financial activity within the Bitcoin network, offering a view on transactions aggregated by entities, i.e., by individuals, companies, or other groups actively using Bitcoin. BitConduite makes Bitcoin data accessible to nontechnical experts through a guided workflow around entities analyzed according to several activity metrics. Analyses can be conducted at different scales, from large groups of entities down to single entities. BitConduite also enables analysts to cluster entities to identify groups of similar activities as well as to explore characteristics and temporal patterns of transactions. To assess the value of our approach, we collected feedback from domain experts.
In this work, we consider community detection in blockchain networks. We specifically take the Bitcoin network and Ethereum network as two examples, where community detection serves in different ways. For the Bitcoin network, we modify the traditional community detection method and apply it to the transaction social network to cluster users with similar characteristics. For the Ethereum network, on the other hand, we define a bipartite social graph based on the smart contract transactions. A novel community detection algorithm which is designed for low-rank signals on graph can help find users' communities based on user-token subscription. Based on these results, two strategies are devised to deliver on-chain advertisements to those users in the same community. We implement the proposed algorithms on real data. By adopting the modified clustering algorithm, the community results in the Bitcoin network is basically consistent with the ground-truth of betting site community which has been announced to the public. At the meanwhile, we run the proposed strategy on real Ethereum data, visualize the results and implement an advertisement delivery on the Ropsten test net.
Natkamon Tovanich, Nicolas Heulot, Jean‐Daniel Fekete, Petra Isenberg
We contribute a systematic review of online visualizations of the Bitcoin blockchain. Bitcoin is currently the most active cryptocurrency with the largest market share among other cryptocurrencies. It has attracted a large user base and more and more businesses are beginning to accept Bitcoin as payment. While there are still relatively few visualization research papers on Bitcoin, a growing number of online tools visualize data about the Bitcoin blockchain. We provide a first systematic assessment of these online tools to inform future research efforts on making the Bitcoin blockchain more accessible.