Blockchain Papers

Brian Michael Murphy, Asad J. Malik

This interview, which took place in September 2021, explores the history of projects carried out by Jadu and the possibilities of Web3, NFTs, and the futures of data in the metaverse.

Chase Webber

No abstract is available for this record.

Fernando Richter Vidal, Naghmeh Ivaki, Nuno Laranjeiro

No abstract is available for this record.

Pablo Santamaría, Llanos Tobarra, Rafael Vargas, Antonio Robles-Gómez

No abstract is available for this record.

José R. García, Jesús Favela, Carlos Eduardo Sánchez-Torres

No abstract is available for this record.

Tang Gui, Wuzheng Tan, Mei Cai

In the big data era, machine learning has devel-oped prominently and is widely used in real-world systems. Yet, machine learning raises fairness concerns, which incurs discrimination against groups determined by sensitive attributes such as gender and race. Many researchers have focused on developing fairness audit technique of machine learning model that enable users to protect themselves from discrimination. Existing solutions, however, rely on additional external trust as-sumptions, either on third-party entities or external components, that significantly lower the security. In this study, we propose a trustless verifiable fairness audit framework that assesses the fairness of ML algorithms while addressing potential security issues such as data privacy, model secrecy, and trustworthiness. With succinctness and non-interactive of zero knowledge proof, our framework not only guarantees audit integrity, but also clearly enhance security, enabling fair ML models to be publicly auditable and any client to verify audit results without extra trust assumption. Our evaluation on various machine learning models and real-world datasets shows that our framework achieves practical performance.

Sayan Das, Aditya Arsh, Chinmaya Bikram Pattanaik, Nirmalya Kar

No abstract is available for this record.

Eliza Mik

No abstract is available for this record.

Craig Hanson

No abstract is available for this record.

Wanting Hu, Qingfeng Wu, Zhiling Zhang, Lu Cao

No abstract is available for this record.

Chuan Chen, Yuecheng Li, Zhenpeng Wu, Chengyuan Mai · 8 authors

Metaverse, the core of the next-generation Internet, is a computer-generated holographic digital environment that simultaneously combines spatio-temporal, immersive, real-time, sustainable, interoperable, and data-sensitive characteristics. It cleverly blends the virtual and real worlds, allowing users to create, communicate, and transact in virtual form. With the rapid development of emerging technologies including augmented reality, virtual reality and blockchain, the metaverse system is becoming more and more sophisticated and widely used in various fields such as social, tourism, industry and economy. However, the high level of interaction with the real world also means a huge risk of privacy leakage both for individuals and enterprises, which has hindered the wide deployment of metaverse. Then, it is inevitable to apply privacy computing techniques in the framework of metaverse, which is a current research hotspot. In this paper, we conduct comprehensive research on the necessity, taxonomy and challenges when privacy computing meets metaverse. Specifically, we first introduce the underlying technologies and various applications of metaverse, on which we analyze the challenges of data usage in metaverse, especially data privacy. Next, we review and summarize state-of-the-art solutions based on federated learning, differential privacy, homomorphic encryption, and zero-knowledge proofs for different privacy problems in metaverse. Finally, we show the current security and privacy challenges in the development of metaverse and provide open directions for building a well-established privacy-preserving metaverse system. For easy access and reference, we integrate the related publications and their codes into a GitHub repository: https://github.com/6lyc/Awesome-Privacy-Computing-in-Metaverse.git.

K. Ghamya, Chintalacheri Charan Yadav, Devarakonda Venkata Sai Pranav, K. Reddy Madhavi · 5 authors

No abstract is available for this record.

Vasilis Kostakis, Alex Pazaitis, Minas Liarokapis

Technological imaginaries have been increasingly shaping the future perceptions of cities. From artificial intelligence and distributed ledger technology to three-dimensional printing, high-tech artifacts are very often the premises of such imaginaries. However, technology does not only refer to artifacts. Technology also encompasses the processes around the artifacts: how the artifacts are designed, manufactured, used, maintained, and disposed. From this perspective, high-tech visions often disregard problems that pertain to resource extraction, labor exploitation, energy use, and material flows. On the contrary, low-tech and localized alternatives incite lower impact and higher resilience visions. However, they fail to offer solutions of the desired scale and intensity. To address this tension, we provide an alternative vision for mid-tech: a balance between the opposite extreme qualities of low-tech and high-tech. Through a case of open-source prosthetics, we illustrate how to synergistically combine the efficiency and versatility of high-tech solutions with the potential for autonomy and resilience that low-tech offers. Then we discuss a mid-tech approach for distributed ledger technology from a city as a license lens. We provide connections with existing or conceptual applications to show how distributed ledger technology could support more socially and ecologically responsible data practices for city governance.

Nipun Sharma, Swati Sharma, Anupama Sindgi

No abstract is available for this record.

Marco Ortu, Giacomo Ibba, Claudio Conversano, Roberto Tonelli · 5 authors

No abstract is available for this record.

Zeli Wang, Weiqi Dai, Ming Li, Kim‐Kwang Raymond Choo · 5 authors

No abstract is available for this record.

Jerry Huang, Ken Huang

No abstract is available for this record.

Leon Yehuda Anidjar, Nizan Geslevich Packin, Argyri Panezi

No abstract is available for this record.

Qinglin Yang, Huawei Huang, Kaixin Lin, Jiajing Wu

No abstract is available for this record.

Md. Nizamuddin, Krishna Devarapu, Abhishake Reddy Onteddu, RamMohan Reddy Kundavaram

This paper examines how encryption and AI protect financial blockchain transactions. As blockchain technology grows more important in decentralized finance, AI must be included to solve cybersecurity issues. The research focuses on how AI improves cryptography systems, blockchain-based financial operations, and transaction security. Secondary data from the literature, peer-reviewed publications, and case studies are analyzed to synthesize AI-blockchain cryptography expertise. AI provides real-time anomaly identification, fraud prevention, predictive analytics, consensus mechanism optimization, and key management improvements, boosting blockchain security. Traditional cryptography methods become more adaptable and robust to emerging threats using AI. According to the research, the computational complexity of AI-driven solutions and AI model biases are constraints. Regulatory frameworks must be modified to ensure transparency, accountability, and compliance with AI-enhanced cryptography systems. This research shows that AI can strengthen blockchain transactions, indicating that AI and cryptography will shape safe and efficient financial systems in the future.

Jelena Ćeranić Perišić

The metaverse is a concept of cyberspace built on the existing infrastructure of the Internet using emerging technologies of blockchains, cryptocurrency and non-fungible tokens (NFT). In the metaverse, people and various forms of algorithms and artificial intelligence will interact in virtual reality, buy and sell “real world” and “in the metaverse” goods and services and get into legal disputes just like in real life. Trademark law has a decisive role in the development and protection of the brand in virtual reality. The paper first presents the notion of NFT. Then, the protection of trademark in metaverse is analyzed. Special attention is paid to the European Intellectual Property Office Guidelines from July 2022 on its approach to classifying virtual goods and NFTs. Finally, a case from US judicial practice is presented – Hermes Int’l v. Rothschild. This decision provides useful guidance on how courts will treat this issue in the future.

Mao Tian, Junhua Chen

Smart contract is presented as a new infrastructure for programming, deployment and execution with the rapid pace of blockchain technology in recent years. The development of blockchain technology provides a good operational basis for smart contracts, which can play an important role on the blockchain. With the rapid development of blockchain platforms such as bitcoin, smart contracts have a good opportunity for development. However, smart contract applications are still at an early stage of development, with relatively little relevant research, and the applicable scenarios of smart contracts in practical applications are not rich enough. In the paper, we study and discuss several aspects, by changing decentralization to weak-centralization, retaining appropriate supervision, and providing necessary right remedy for users of non-performance clause, can make smart contracts safe to use by compromising part of transaction efficiency.

Ellie Rennie

Abstract The survival of permissionless blockchains is typically cast as a cryptoeconomic security problem for mechanism designers to resolve. This essay argues that, long-term, these networks may require something that looks more like a UNESCO protection convention for machine culture than an equation. Ethereum’s machine culture is observable through the formation of a “’we’-group” (Hartley & Potts, 2014, p. 76), which is necessary for the establishment of common knowledge. While entry to the group is permissionless, maintaining membership boundaries demands active contributions from validator nodes. The paper discusses concerns that Ethereum’s consensus may be used for purposes beyond itself, making Ethereum vulnerable to external, non-machine political forces. As this begins to manifest, the need to safeguard Ethereum’s intrinsic machine culture becomes apparent—not merely for the sake of the blockchain but to maintain a stable foundation for emerging digital economies and governance structures.

Zeinab Shahbazi, Yung-Cheol Byun

Cryptocurrency, often known as virtual or digital currency, is a safe platform and a key component of the blockchain that has recently attracted much interest. Utilizing blockchain technology, bitcoin transactions are recorded in blocks that provide detailed information on all financial transactions. Artificial intelligence (AI) has significant applicability in several industries because of the abundance and processing capacity of large data. One of the main issues is the absence of explanations for AI algorithms in the current decision-making standards. For instance, there is no deep-learning-based reasoning or control for the system's input or output processes. More particularly, the bias for adversarial attacks on the process interface and learning characterizes existing AI systems. This study suggests an AI-based trustworthy architecture that uses decentralized blockchain characteristics such as smart contracts and trust oracles. The decentralized consensuses of AI predictors are also decided by this system using AI, enabling secure cryptocurrency transactions, and utilizing the blockchain technology and transactional network analysis. By utilizing AI for a thorough examination of a network, this system's primary objective is to improve the performance of the bitcoin network in terms of transactions and security. In comparison to other state-of-the-art systems, the results demonstrate that the proposed system can achieve very accurate output.