Technologies Behind Crypto-Based Decentralized Finance

The integration of artificial intelligence (AI) and blockchain technology in curatorial practice offers transformative potential for managing, presenting, and distributing both traditional and digital art. This study explores how AI enhances curatorial processes through advanced data analysis and personalized visitor experiences. AI assists curators in organizing collections and recommending artworks tailored to individual preferences, fostering greater engagement with dynamic, customized exhibitions. Blockchain technology, on the other hand, ensures the provenance of decentralized artworks, guaranteeing authenticity and transparency. It addresses issues like counterfeiting, ownership disputes, and secure transactions, while supporting artists through smart contracts that ensure equitable compensation. However, ethical concerns remain. These include biases in AI algorithms, intellectual property challenges in decentralized NFT platforms, and limited digital access for marginalized artists. Academic studies and case analyses underscore these challenges and advocate for collaboration among curators, artists, technologists, and policymakers. This approach seeks to resolve ethical dilemmas, promote inclusivity, and maintain cultural integrity in implementing these technologies. The study emphasizes the need for public policy frameworks to regulate AI and blockchain, ensuring fair compensation and equitable access to their benefits while safeguarding cultural values. By addressing these concerns, these technologies can unlock new possibilities for the art world. Transformasi Praktik Kuratorial: Peran AI dan Blockchain dalam Membentuk Paradigma Seni-Sains yang Etis untuk Kebijakan Publik Abstrak Integrasi kecerdasan buatan (AI) dan teknologi blockchain dalam praktik kuratorial menawarkan potensi transformatif untuk mengelola, menyajikan, dan mendistribusikan seni baik tradisional maupun digital. Studi ini mengeksplorasi bagaimana AI meningkatkan proses kuratorial melalui analisis data yang mutakhir dan pengalaman pengunjung yang dipersonalisasi. AI membantu kurator dalam mengatur koleksi dan merekomendasikan karya seni yang disesuaikan dengan preferensi individu, mendorong keterlibatan yang lebih besar dengan pameran yang dinamis dan disesuaikan. Di sisi lain, teknologi blockchain memastikan asal-usul karya seni yang terdesentralisasi, menjamin keaslian dan transparansi. Teknologi ini mengatasi masalah seperti pemalsuan, sengketa kepemilikan, dan transaksi yang aman, serta mendukung para seniman melalui kontrak pintar yang memastikan kompensasi yang adil. Akan tetapi, masalah etika tetap ada. Ini termasuk bias dalam algoritma AI, tantangan kekayaan intelektual dalam platform NFT yang terdesentralisasi, dan akses digital yang terbatas untuk seniman yang terpinggirkan. Studi akademis dan analisis kasus menggarisbawahi tantangan-tantangan ini dan mengadvokasi kolaborasi di antara kurator, seniman, ahli teknologi, dan pembuat kebijakan. Pendekatan ini berusaha untuk menyelesaikan dilema etika, mempromosikan inklusivitas, dan menjaga integritas budaya dalam mengimplementasikan teknologi ini. Studi ini menekankan perlunya kerangka kerja kebijakan publik untuk mengatur AI dan blockchain, memastikan kompensasi dan akses yang adil terhadap manfaatnya sambil menjaga nilai-nilai budaya. Dengan mengatasi masalah ini, teknologi ini dapat membuka peluang baru bagi dunia seni.

This chapter investigates the potential for block chain and artificial intelligence (AI) to work together to revolutionise agriculture. Block chain’s decentralised ledger and AI's data-driven decision-making provide disruptive answers to the agriculture sector's multiple concerns, such as climate change and market access. Initially, the chapter presents a complete introduction of block chain and AI technologies, highlighting their distinguishing characteristics and agricultural applications. Block chain enables traceability, supply chain management, and decentralised marketplaces, complimenting artificial intelligence's precision farming, crop monitoring, and decision support systems. In terms of their separate responsibilities, block chain helps with traceability, quality assurance, decentralised marketplaces, and climate resilience, whereas AI helps with precision farming, yield prediction, and animal health monitoring. The intersection of block chain and AI opens significant possibilities for data integrity, safe sharing, smart contracts, and transparent supply chains. This integration enables crop management predictive analytics, autonomous farming machinery, and climate-resilient techniques. However, barriers to seamless integration include data quality, connection, acceptance, scalability, energy usage, and regulatory compliance. To overcome these obstacles, stakeholders must work together to provide fair access and knowledge of new technologies. In conclusion, the chapter depicts a positive future in which block chain and AI drive a more robust, transparent, and productive agriculture industry. It emphasises the importance of social activity and technical understanding in order to fully realise the promise of these advances.

The rapid uptake of blockchain and artificial intelligence (AI) technologies like machine learning (ML) in particular has brought about a paradigm change that is elevating the digital ecosystem for smart cities. The development of new technology can be used to create intelligent societies within smart cities in this era of rapid digital communication. Uses of blockchain technology and ML technologies are proliferating, guaranteeing solutions for issues in a multitude of sectors, such as financial services, cryptocurrency, threat intelligence, social and public services, and the Internet of Things. These “smart cities” are constructed using various technologies, including artificial intelligence and blockchain. As a result, the way these technologies are applied in smart cities both present and future will alter not only the character of governance and human interaction but also the way business is done. The research suggests doing an experimental study to find out how blockchain technology and artificial intelligence are affecting the creation of smart cities. It tries to set the scene for queries like how traditional business models are getting ready for this disruption, what obstacles they might encounter, and what effects both technologies might have on the organization's growth. Blockchain technology and artificial intelligence have a lot of potential to help create smart cities. The results of the research will provide corporations with the rationale to start concentrating on these technologies and putting early adoption strategies into place, which will eventually cause them to change their smart city business models advance.

Given the growing increase in the number of blockchain (BC) platforms, cryptocurrencies, and tokens, non-technical individuals face a complex question when selecting a BC that meets their requirements (e.g., performance or security). In addition, current approaches that aid such a selection process present drawbacks (e.g., require specific BC knowledge or are not automated and scalable), which hinders the decision process even further. Fortunately, techniques such as Machine Learning (ML) allow the creation of selection models without human interaction by identifying the BC features that match the requirements provided by the user in an automated and flexible manner. Thus, this work presents the design and implementation of an ML-based BC selection approach that employs five ML models to select the most suitable BC given user requirements (e.g., BC popularity, fast block inclusion, or Smart Contract - SC support). The approach follows an ML-specific data flow and defines a novel equation to quantify the popularity of a BC. Furthermore, it details the models’ accuracy and functionality in two distinct use cases, which shows their good accuracy (>85%). Finally, discussions on (a) the ML usefulness, (b) advantages over rule-based systems, and (c) the most relevant features for the BC selection are presented.

The integration of emerging technologies like blockchain and artificial intelligence (AI) into educational financial systems has likely to transform the institutions manage payments, ensure data security, and promote operational transparency. This study addresses the awareness and attitudes of students in higher education institutions across Tiruchirappalli regarding the application of blockchain and AI in educational payment systems. Specifically, it aims to assess students’ knowledge of these technologies, examine their views on the role of blockchain and AI in maintaining data security, and explore their opinions on the potential of blockchain–AI integration to enhance payment efficiency and transparency. This study proposes a hybrid framework that leverages the immutable, decentralized ledger of blockchain to secure academic records, personal student data, and financial transactions. Concurrently, AI algorithms are employed to analyze transactional data for fraud detection, optimize payment reconciliation, and provide predictive insights into financial trends. The proposed system utilizes block chain to create a tamper-proof and transparent record of all educational activities, from student enrollments to exam results, accessible only to authorized parties via smart contracts. AI models, integrated with the block chain, can proactively identify anomalies and potential security threats in real time. For payment services, the system facilitates secure, transparent, and instantaneous tuition fee payments and other financial transactions, reducing administrative overhead and eliminating intermediaries. The primary contribution of this research is a proof-of-concept model demonstrating the synergy between block chain's security features and AI's analytical capabilities to create a robust, efficient, and user-centric digital ecosystem for educational institutions. The findings indicate that this integrated approach significantly improves data integrity, reduces the risk of cyber threats, and enhances the overall efficiency of financial and administrative operations. This research provides a valuable blueprint for educational bodies in Tiruchirappalli and beyond to modernize their digital infrastructure and build a foundation of trust and security in the digital age.

With the enormous amount of sensitive data generated by supply chains and with the accession of Industry 4.0, the development of airline supply chain management (SCM) strategies and the preservation of privacy have become a necessity. The implementation of robust privacy strategies allows supply chains to protect their personal data from being lost, used, or accessed in an unauthorized way. Blockchain technologies (BT) allow data to be traded transparently and to automate transactions through smart contracts. Indeed, blockchain technology is attracting more and more attention as it ensures integrity and non-repudiation. However, secure supply chain existing models neglect the complexity of the airline supply chain management (ASCM), data confidentiality, and advanced and persistent attacks (APT) which make them exposed to many vulnerabilities. In this article, we propose a blockchain-based framework suitable for the ASCM context. Thus, we will develop an efficient model based on blockchain and machine learning to authenticate, validate, and secure transactions between suppliers and legitimate users on ASCM environments. The proposed solution reduces transaction costs, enhances security level by detecting and preserving anomalies, and fosters transparency and validity of transactions.KeywordBlockchain technologiesSupply chain managementAirline supply chain managementMachine learningSecurity and privacy

The dynamic nature of international trade finance necessitates innovative risk assessment approaches that transcend traditional models' limitations. This article explores the transformative role of artificial intelligence (AI) and blockchain technologies in addressing critical challenges such as fraud detection, credit risk, and country risk in trade finance. By leveraging AI’s capabilities in predictive analytics, anomaly detection, and machine learning, trade finance institutions can achieve greater accuracy, efficiency, and adaptability in risk management processes. Additionally, blockchain technology enhances transaction security through immutable records and smart contracts, mitigating risks associated with documentation errors and double financing. The article evaluates how AI and blockchain can be implemented within the regulatory frameworks of UCP600 and URDG758, ensuring alignment with global trade standards. Furthermore, it highlights the opportunities and challenges of these technologies, emphasizing the need for stronger data protection measures, regulatory compliance, and ethical considerations. This study concludes by proposing future directions for research and practice, including real-time risk assessment models and automated compliance monitoring, to drive innovation in the trade finance sector

The convergence of blockchain, artificial intelligence (AI), and cloud computing is catalyzing a paradigm shift in developing secure, intelligent, and scalable digital infrastructures. This triad of technologies is increasingly utilized to improve performance, transparency, and trust in engineering-driven and socio-technical environments. This study systematically reviews the evolution, integration strategies, and applications of blockchain, AI, and cloud computing in digital ecosystems. The analysis is based on 108 peer-reviewed studies spanning the years 2012 to 2025. A comprehensive literature analysis was conducted to identify trends, synergies, and sector-specific implementations of these systems. The review explores how their integration supports real-world engineering and operational use cases. Blockchain contributes to decentralized architectures, secure data exchange, and identity verification. AI supports adaptive behavior, autonomous decision-making, and predictive analytics. Cloud computing offers the scalable infrastructure necessary for deployment. Key challenges addressed include interoperability, latency, security trade-offs, and resource allocation. Use cases in digital finance, supply chain management, and industrial automation demonstrate the effectiveness of this integration in building resilient, ethically aligned, and high-performance infrastructures. The findings offer valuable insights and technical considerations for engineers and architects seeking to design next-generation cyber-physical systems that are secure, intelligent, and socially responsive. Clinical Trial Number Not applicable. This article accentuates the extensive use of blockchain, cloud computing, and AI principles, emphasizing their crucial significance in the contemporary digital environment and paths in which blockchain technology may be employed to automate financial transactions, enhance the security of personal data and records, facilitate cross-border transactions, verify identities, execute smart contracts, utilize cryptocurrencies, and manage supply chains. This research systematically assesses the development and practical application of blockchain, cloud computing, and artificial intelligence technologies over the past decade. This study primarily focuses on monitoring the progress, practical applications, and benefits of blockchain technology in the context of financial transactions. This article probes the symbiotic relationship between artificial intelligence, cloud and blockchain technology, analyzing the evolution and fundamental concepts of their integration from 2012 to 2025. This paper also presents a detailed analysis of 108 research works acquitted over the past decade. The study provides a comprehensive examination of the current state and fundamental principles related to the integration of artificial intelligence, cloud, and blockchain technology. This paper offers a comprehensive analysis of the major obstacles confronted by blockchain technology, examining its wide-ranging applications over several industries and its socko role in transaction systems and the domain of cryptocurrencies.

Traditional machine learning algorithms use data from databases that are mutable, and therefore the data cannot be fully trusted. Also, the machine learning process is difficult to automate. This paper proposes building a trustable machine learning system by using blockchain technology, which can store data in a permanent and immutable way. In addition, smart contracts are used to automate the machine learning process. This paper makes three contributions. First, it establishes a link between machine learning technology and blockchain technology. Previously, machine learning and blockchain have been considered two independent technologies without an obvious link. Second, it proposes a unified analytical framework for trustable machine learning by using blockchain technology. This unified framework solves both the trustability and automation issues in machine learning. Third, it enables a computer to translate core machine learning implementation from a single thread on a single machine to multiple threads on multiple machines running with blockchain by using a unified approach. The paper uses association rule mining as an example to demonstrate how trustable machine learning can be implemented with blockchain, and it shows how this approach can be used to analyze opioid prescriptions to help combat the opioid crisis.

SummaryThe block chain is the emerging domain that offers the features like shared, immutable, and decentralized dataset that saves the asset's history. Security and storage are the most challenging aspect. The classical techniques' issues and challenges are an encouragement for developing a fresh block chain‐assisted IPFS model with access control policies. Hence, this research paper introduces an effective access control and authentication based on an interplanetary file system (IPFS)‐based block chain and access control system for attaining secured transactions. The developed method comprises five entities, that is smart contract, data owner, data requester, block chain and IPFS along with eight phases, to be exact setup, user registration, initialization, storage and data encryption, authentication, testing, access control, and decryption phase, to provide better access control and storage capacity. The proposed IPFS‐based block chain and access control system offered effective storage and secure transactions in the block chain network. The highest detection rate (0.870), lowest communication overhead (0.766 MB), and highest privacy rate (0.719) are all achieved by the proposed IPFS‐based block chain and access control system.

Smart contracts (SCs) are digital agreements that execute themselves and are stored on a blockchain. Despite the fact that they offer numerous advantages, such as automation and transparency, they are susceptible to a variety of assaults due to their complexity and lack of standardization. In this paper, we investigate the use of artificial intelligence (AI) to improve SC security. We provide an overview of Smart Contracts (SCs) and blockchain technology, as well as a discussion of possible SC-based attacks. Then, we introduce various AI categories and their applications in cybersecurity, followed by a thorough analysis of how AI can be used to enhance SC security. We also highlight the open questions and future directions of research in this field. Our research demonstrates that AI can provide an effective defense against assaults on SCs and contribute to their security and dependability. This article lays the groundwork for future research in the field of AI for SC security.

this is a potentially game-changing development that could come from fusing blockchain technology with IoT and artificial intelligence (AI) to improve the efficiency of smart contracts in the banking industry. We can greatly increase the transparency, security, and efficiency of banking transactions by utilizing the decentralized and rigid nature of blockchain technology, real-time data from Internet of Things (IoT) devices, and artificial intelligence's (AI) intelligent decision-making capabilities. These three things working together make this possible. This paper examines the methods by which these technologies can facilitate operational simplification, fraud reduction, and stakeholder confidence building. The research specifically focused on how these technologies are used. We have out a thorough analysis of numerous fabrics and case studies to highlight the synergistic advantages of this integration. This helps pave the way for it by making a more open and responsible financial environment feasible. By addressing the challenges that are now being encountered and identifying the unspoken pathways that will lead to the deployment of these cutting-edge technologies in the banking institution, this investigation seeks to shed light on the future of financial transactions. We shall conduct this research too.

As blockchain technology increasingly underpins digital transactions, smart contracts have emerged as a pivotal tool for automating these transactions. While smart contracts offer efficiency and security, their automation introduces significant legal challenges. Detecting and preventing fraud is a primary concern. This paper proposes a novel application of artificial intelligence (AI) to address these challenges. We will develop a machine learning model, specifically a Convolutional Neural Network (CNN), to effectively detect and mitigate fraudulent activities within smart contracts. The AI model will analyze both textual and transactional data from smart contracts to identify patterns indicative of fraud. This approach not only enhances the security of digital transactions on blockchain platforms but also informs the development of legal standards and regulatory frameworks necessary for governing these technologies. By training on a dataset of authentic and fraudulent contract examples, the proposed AI model is expected to offer high predictive accuracy, thereby supporting legal practitioners and regulators in real-time monitoring and enforcement. The ultimate goal of this project is to contribute to legal scholarship by providing a robust technological tool that aids in preventing cybercrimes associated with smart contracts, thereby laying a foundation for future legal research and development at the intersection of law, technology, and security.

Non-Fungible Tokens (NFTs) have been developed over the past few years as an impactful new digital asset class that allows both artists and cultural institutions to securely generate revenue from their digital creations while protecting them. However, limited research exists that fully addresses the integration of NFTs and smart contracts as a technological framework for preserving and promoting artistic and cultural heritage in Malaysia. While there has been much discussion about the economic advantages of NFTs paired with smart contracts, the technical backbone infrastructure remains largely unexplored in many ways for cultural preservation. The research explores NFTs and smart contracts to offer automated royalties and an unprecedented transfer of ownership system with cultural impact. This research, through a mixed-method approach-including a literature review, interviews with experts, and the formulation of relevant mathematical models-conducted an analysis of how smart contracts automate the NFT transaction and royalty distribution. The results have so far shown that, underpinned by blockchain technology, NFTs can offer a promising solution to present and future Malaysian artists and cultural institutions in ensuring the authenticity and financial viability of traditional and modern forms of art. Besides that, scalability, environmental concerns, and legal frameworks are several sober challenges to widespread adoption. Finally, this research concludes that NFTs and smart contracts have the potential to revolutionize Malaysia's cultural economy by offering a sustainable model for heritage preservation and a supporter of the arts in general.

This review explores the transformative impact of Artificial Intelligence (AI) and blockchain technologies on financial operations, with a particular focus on modern payment systems. As the financial sector undergoes rapid digital transformation, AI and blockchain emerge as key drivers reshaping payment processing, fraud detection, transaction security, and operational efficiency. AI enhances payment systems by enabling real-time data analysis, intelligent automation, and adaptive risk management, while blockchain offers decentralized, transparent, and immutable transaction records that increase trust and reduce intermediaries. This examines current advancements in AI-driven payment automation, including machine learning algorithms for fraud detection, natural language processing for customer service, and predictive analytics for transaction risk assessment. It also highlights blockchain’s role in enabling faster cross-border payments, smart contracts for automatic execution of payment terms, and decentralized finance (DeFi) platforms that challenge traditional banking models. The synergy of AI and blockchain technologies is discussed as a powerful combination that addresses limitations inherent in legacy payment infrastructures, such as high costs, slow settlement times, and vulnerability to cyber threats. Through a comprehensive literature review, the study identifies key benefits such as enhanced security, improved transaction transparency, reduced operational costs, and increased accessibility for underbanked populations. However, it also considers challenges including regulatory uncertainty, scalability concerns, data privacy issues, and integration complexities within existing financial systems. The review concludes by emphasizing the need for ongoing innovation, robust regulatory frameworks, and cross-sector collaboration to fully harness the potential of AI and blockchain in payment systems. It calls for further research into scalable solutions and ethical considerations to ensure inclusive, secure, and efficient financial operations worldwide. This thus provides valuable insights for financial institutions, technology developers, and policymakers seeking to navigate and leverage the evolving landscape of AI- and blockchain-enabled payment technologies.