Smart contracts, closely intertwined with cryptocurrency transactions, have sparked widespread concerns about considerable financial losses of security issues. To counteract this, a variety of tools have been developed to identify vulnerability in smart contract. However, they fail to overcome two challenges at the same time when faced with smart contract bytecode: (i) strong interference caused by enormous non-relevant instructions; (ii) missing semantics of bytecode due to incomplete data and control flow dependencies. In this paper, we propose a multi-teacher based bytecode vulnerability detection method, namely Multi-Teacher Vulnerability Hunter (MTVHunter), which delivers effective denoising and missing semantic to bytecode under multi-teacher guidance. Specifically, we first propose an instruction denoising teacher to eliminate noise interference by abstract vulnerability pattern and further reflect in contract embeddings. Secondly, we design a novel semantic complementary teacher with neuron distillation, which effectively extracts necessary semantic from source code to replenish the bytecode. Particularly, the proposed neuron distillation accelerate this semantic filling by turning the knowledge transition into a regression task. We conduct experiments on 229,178 real-world smart contracts that concerns four types of common vulnerabilities. Extensive experiments show MTVHunter achieves significantly performance gains over state-of-the-art approaches.
The urgency of this research is to increase efficiency, transparency and sustainability in increasingly complex and challenging agribusiness supply chains. The aim of this research is to develop an integrated system that combines IoT capabilities in collecting agricultural data in real-time, AI to analyze data and provide recommendations for action, as well as security and transparency guaranteed by blockchain technology. The method used is a mixed methods approach, this approach combines qualitative and quantitative elements to obtain a deeper understanding. A qualitative approach is used to gain a contextual perspective, while a quantitative approach is used to measure performance empirically. This research uses a case study design on a sensor-based agricultural monitoring system because of its ability to provide in-depth and holistic insights. The research population consists of users and stakeholders in sensor-based agricultural monitoring systems. The sample was selected purposively to cover various aspects of the supply chain. Data was collected through in-depth interviews, direct observation, surveys of system users and collection of sensor and transaction data from agricultural monitoring systems. The research results show that the integration of IoT, AI, and blockchain significantly improves operational efficiency in agribusiness supply chains. Implementation of this integrated system resulted in an increase in productivity of up to 22%, a reduction in pesticide use by 35%, an increase in water use efficiency by 30%, and a reduction in operational costs by 18%. Statistical analysis confirmed a strong positive correlation between the use of integrated technology and increased operational efficiency (R=0.85, p<0.01).
Трансформација од економије која је била заснована на радно интензивним инвестицијама, до економије засноване на знању и иновацијама, створила је конкурентније друштво. Међутим, трансформација економије и друштва није могућа без развијене интелектуалне својине. Неопходно је да право интелектуалне својине прати развој технологије, а то је веома тежак задатак. Данас аутори и носиоци ауторског и сродних права све више користе тзв. незаменљиве токене (non-fungible-tokens) као власничке сертификате за виртуелну имовину,у циљу уновчавања својих духовних творевина. Незаменљиви токен се зове тако јер је јединствен, односно, не постоје два иста токена. NFT је најлакше схватити као дигитални „водени жиг“ који може непобитно да утврди аутентичност дигиталне датотеке – слике, видео клипа, аудио датотеке, криптовалуте. Заправо, било која компјутерски генерисана датотека може бити потписана NFT токеном. С обзиром да се Закон о дигиталној имовини примењује у Србији од 2021. године, неопходне су и измене правила интелектуалне својине, којима ће се регулисати однос између три категорије лица, аутора оригиналног дела (онај који поседује права интелектуалне својине над делом), аутора NFT(оног који је минирао токен) и власника NFT-а (онај који је купио токен). Дигитална својина је годинама актуелна тема у Србији, а сва је прилика да ће постати још значајнија сада када је усвојен правни оквир који настоји да омогући њену даљу примену и развој.
The integration of artificial intelligence (AI) into smart contracts holds the potential to both enhance and exacerbate consumer protection challenges. Since the AI system embedded within the contract’s code enables a high degree of contractual personalisation – by tailoring the legal agreement to the unique characteristics of the targeted individual consumer, thanks to its capacity to process large amounts of personal and behavioural data in real time – it opens the door not only to scenarios of AI-powered consumer manipulation, but also to the promising opportunity of a consumer-centric AI. Such an AI would serve the consumer’s best interests by adapting the contract to their specific needs and preferences, while protecting them from – rather than exploiting – their information, cognitive, and digital vulnerabilities. This research aims to assess whether the EU legal framework – particularly the UCPD, UCTD, AI Act, GDPR, and DSA – adequately ensures that these technologies are designed and deployed with the consumer’s well-being at their core. The paper explores AI-related risks such as digital manipulation, personal data exploitation, and the black-box problem inherent in algorithmic opacity, while also addressing the liability challenge in cases of consumer harm. Ultimately, it seeks to answer whether AI-driven smart contracts can truly foster a high level of consumer protection in the AI era, by offering novel interpretations of the existing legal framework and advancing proposals for reform aligned with the fairness-by-design approach and informed by behavioural science insights.
Modern financial technologies (Financial Technologies, FinTech) have improved traditional finance, while concurrently building a fundamentally new financial alternative. The application of FinTech has created digital financial products that are legally regulated but many crypto products still remain outside the law. The cryptocurrency market is a digital decentralized system that operates according to its own rules that users voluntarily accept, using personalized digital transactions. The application of FinTech in banking is a legal activity of banks aimed at strengthening competitive advantages in providing financial services, whereas central banks may require from commercial banks to upgrade or improve part of their digital technologies. In contrast, Blockchain technology has created a digital financial alternative which allows individuals to directly manage their digital wallets via phones and computers, without centralized control and outside of banking systems, by using the Internet and sharing original digital records among networked users worldwide. In the initial period, Blockchain technology generated resistance and was ignored by state regulatory bodies. The process of legal regulation of digital products and markets which were created on the basis of Blockchain and other digital technologies began after several years of actual Blockchain technology application. The subject matter of analysis in this paper is the legal regulation of already developed and widely used digital markets and assets, with specific reference to the legal solutions in the USA, the EU, and Serbia. The challenges of legal regulation of digital assets are numerous, ranging from insufficient knowledge of digital technologies to the unfeasibility of norming the decentralized digital segments. Thus, it is essential for the creators of law and the persons who apply the law to have the basic knowledge of modern digital technologies.
Abstract The Internet has significantly transformed society, fostering technological literacy and reshaping business transactions through advancements like blockchain and distributed ledger technologies (DLT). Traditional business concepts are evolving as users increasingly engage with digital identities and smart contracts. This introductory chapter outlines the legal frameworks for emerging digital assets, identities, and the Internet of Value, with a focus on the European context, particularly Spain. Despite the rise of Big Tech, which centralises data, there are persistent trends towards decentralisation, exemplified by peer-to-peer networks and blockchain. These developments raise concerns about the monopolisation of digital infrastructure and the potential need for a “new social contract” regarding digital identity and ownership. Regulatory frameworks must adapt to address the unique legal and security challenges posed by cryptocurrencies and digital assets. As Europe navigates this transformation, initiatives like the Markets in Crypto-assets Regulation (MiCA) and the Digital Euro Package aim to create coherent legal structures. This work emphasises the importance of securing trust in the digital economy while considering the implications of emerging technologies and the evolving landscape of digital finance.
Blockchain technology is reshaping a wide range of sectors, from finance and law to art. The rise of blockchain platforms offering "blockchain arbitration" suggests a shift toward faster, cheaper and decentralized dispute resolution. A key advantage often highlighted is the potential for automatic enforcement of decisions using smart contracts. However, since this is only a possibility, many decisions will be enforced through traditional means. Given the inherently global nature of blockchain arbitration disputes, an important consideration is whether their decisions can be recognized and enforced under the New York Convention. This paper explores whether blockchain arbitration decisions qualify as awards enforceable under the New York Convention and whether their decision-making process meets the Convention's enforcement criteria. The author recognizes that the procedural aspect of public policy may be undermined by the way decisions are rendered in blockchain arbitrations.
Leandro Loffi, Gerson Luiz Camillo, Cristiano Antonio de Souza, Carla Merkle Westphall · 5 authors
Digital evidence plays an increasingly crucial role in judicial proceedings due to the exponential growth in the creation, storage, and transmission of digital data. However, its inherent volatility and susceptibility to tampering necessitate robust mechanisms to ensure integrity and authenticity, making an effective chain of custody (CoC) a fundamental requirement. While state-of-the-art reviews identify various aspects, it is necessary to include the use of Self-Sovereign Identity (SSI) systems within the scope of research. To address this challenge, this article conducts a systematic review of the literature on the use of blockchain and SSI in managing the chain of custody of digital evidence. The review began with 9,178 studies, which, after a rigorous process applying inclusion and exclusion criteria, resulted in 39 studies directly related to the research topic. The study maps and reviews techniques, tools, methods, approaches, and security components for managing the chain of custody of digital evidence. The findings confirm the widespread adoption of blockchain for preserving digital evidence while indicating that SSI remains an emerging and underexplored concept in forensic applications. The results highlight the need for further research on off-chain storage mechanisms, privacy-preserving techniques such as Zero-Knowledge Proofs (ZKPs) to enhance security, auditability, and interoperability when combined with Verifiable Credentials (VCs). By mapping the current state of research, this study provides valuable insights into CoC, Blockchain, and SSI in forensic-based proposals, identifying research gaps, limitations, and opportunities for developing more robust and scalable evidence management systems.
The paper delves into the impact of non-fungible tokens on trademark in the fashion industry. NFTs are digital assets that offer evidence of ownership and authenticity and are stored in blockchain technology. In the emerging scenario, fashion brands are using NFTs to offer new opportunities to attract consumer attention, thereby enhancing marketing techniques in the digital space. New techniques have been introduced by NFTs to deal with fashion brands leveraging blockchain technology and providing an effective marketplace. Nonetheless, NFTs are also posing danger to trademark infringement, counterfeiting goods, and brand identity in the digital space. The lack of specific legislation regulating NFTs throughout the world has caused challenges for trademark laws and the fashion industry to safeguard their intellectual property.The research in this field suggests that even though there are limitations in the ever-growing sphere of NFTs, there are immense opportunities as well if regulated well. The paper analyses the prospects of the blockchain technology in securing fashion brands in the digital space. The paper also delves into ethical dilemma including artistic attribution and provides valuable insights for law students, professionals, and policymakers to explore the emerging field of digital ownership and trademark protection. Ultimately, the paper provides recommendations for better incorporation of effective legislation on NFTs in the Indian marketplace.
Frontier AI systems, including large-scale machine learning models and autonomous decision-making technologies, are deployed across critical sectors such as finance, healthcare, and national security. These present new cyber-risks, including adversarial exploitation, data integrity threats, and legal ambiguities in accountability. The absence of a unified regulatory framework has led to inconsistencies in oversight, creating vulnerabilities that can be exploited at scale. By integrating perspectives from cybersecurity, legal studies, and computational risk assessment, this research evaluates regulatory strategies for addressing AI-specific threats, such as model inversion attacks, data poisoning, and adversarial manipulations that undermine system reliability. The methodology involves a comparative analysis of domestic and international AI policies, assessing their effectiveness in managing emerging threats. Additionally, the study explores the role of cryptographic techniques, such as homomorphic encryption and zero-knowledge proofs, in enhancing compliance, protecting sensitive data, and ensuring algorithmic accountability. Findings indicate that current regulatory efforts are fragmented and reactive, lacking the necessary provisions to address the evolving risks associated with frontier AI. The study advocates for a structured regulatory framework that integrates security-first governance models, proactive compliance mechanisms, and coordinated global oversight to mitigate AI-driven threats. The investigation considers that we do not live in a world where most countries seem to be wishing to follow European Union ideals, and in the wake of this particular trend, this research presents a regulatory blueprint that balances technological advancement with decentralised security enforcement.
Open access
2 source records
Ethics and Social Impacts of AI
Artificial Intelligence in Healthcare and Education
Amal Al‐Rasheed, Hashim Ali, Rahim Khan, Aamir Saeed
In the domain of Electronic Medical Records (EMRs), emerging technologies are crucial to addressing longstanding concerns surrounding transaction security and patient privacy. This paper explores the integration of smart cont... | Find, read and cite all the research you need on Tech Science Press
The convergence of Artificial Intelligence (AI) and Large Language Models (LLMs) with blockchain technology is transforming information systems by enhancing their efficiency, security, and decision-making capabilities. This research explores the integration of AI and LLMs, such as GPT and BERT, into blockchain-based information systems to address challenges related to data integrity, transaction processing, and smart contract automation. A layered architecture is proposed, comprising an AI-powered query engine, an LLM-enhanced decision-making layer, and a data synchronisation module bridging on-chain and off-chain environments. The system evaluation highlights significant improvements in transaction efficiency, query accuracy, energy savings, and security threat detection rates. Experimental results demonstrate a 32% reduction in transaction latency, a 20.5% increase in fraud detection accuracy, and a 23% reduction in energy consumption. These findings underscore the viability of integrating AI and LLMs with blockchain technology for developing intelligent, secure, and scalable information systems.
Contemporary Artificial Intelligence ("AI") systems, particularly Large Language Models ("LLMs"), face an imminent shortage of high-quality, humangenerated textual data, a phenomenon often termed "data exhaustion".This article examines the limitations of existing centralized data-annotation frameworks, highlighting critical issues such as bias, high computational overhead, and insufficiently adaptive infrastructures.Current market participants-including Scale AI, Appen, CloudFactory, and others-excel at rapidly scaling annotation services yet struggle with ethical sourcing, privacy compliance, and equitable compensation.In addition, legal and regulatory concerns, exemplified by stringent mandates such as the General Data Protection Regulation ("GDPR"), constrain the free flow of data essential for advanced AI research.As a corrective measure, decentralized data production paradigms are proposed, including the adoption of smart contracts, token-based incentives, and participatory governance through Decentralized Autonomous Organizations ("DAOs").While existing decentralized initiatives-SingularityNET, Fetch.ai,Ocean Protocol, Numeraire, and DcentAI-offer incremental innovations in reputation management and stakeholder engagement, they fail to fully address the nuanced requirements of large-scale "Mechanical Turk"-style data creation.In contrast, the author proposes a Weighted Directed Acyclic Graph ("WDAG") governance model which provides a multi-dimensional reputation framework, facilitating real-time validation of data contributions, adaptive ethical and legal compliance, and collaborative oversight by diverse community members.Findings suggest that such WDAGcentric systems can more effectively maintain data quality, ensure ethical alignment, and incentivize broad participation, thereby mitigating the looming data shortage and expanding AI's societal benefits.Ultimately, successful implementation requires coordinated efforts among policymakers, industry practitioners, and civil society actors to sustain both the technological and ethical integrity of AI research.By integrating WDAG-based governance with emerging decentralized solutions, the AI community may realize a more equitable, scalable, and future-ready paradigm for data provisioning.
Open access
2 source records
Ethics and Social Impacts of AI
Artificial Intelligence in Healthcare and Education
This chapter provides an analysis of legal mechanisms to addressing fraud and scams involving cryptocurrency, drawing on both practical legal experience and the new comparative economics. Although illicit transactions account for a small portion of total cryptocurrency transaction volumes, individuals incur significant private losses and there are unique enforcement challenges in the Web3 ecosystem. The prevalent legal approach to addressing cryptocurrency-based fraud is though public enforcement mechanisms. This chapter argues that in some circumstances private law and civil litigation mechanisms can offer a more efficient mechanism for addressing cryptocurrency-based fraud with tools to identify perpetrators, tailored legal claims, and secure assets. The chapter concludes by making recommendations to enhance these private law remedies.
Pranauv Kessavan -, S. Hendry Leo Kanickam, Veeramraju Lakshmi Ajay, Amala Margret -
Digital copyright protection systems aim to secure creators’ rights and ensure they’re fairly compensated, but traditional methods struggle with data verification and tamper-resistance. The proposed solution enhances these protections by integrating proof-of-stake (PoS) algorithms and smart contracts into the blockchain framework. PoS, a consensus mechanism in blockchain, requires participants to stake tokens, ensuring that they have a stake in maintaining the integrity of the system. This approach secures the network and safeguards against tampering. Smart contracts—self-executing, tamper-proof agreements stored on the blockchain—automate copyright enforcement, making it impossible to alter ownership records once added to the blockchain. This automation reduces manipulation risks and improves efficiency. Additionally, the decentralized structure of blockchain distributes data across multiple nodes, preventing any single entity from altering or compromising the information. This guarantees the immutability and transparency of digital content and ownership records. Together, these technologies offer a robust, efficient solution for digital copyright protection. Blockchain’s decentralized, tamper-resistant nature, combined with PoS’s secure verification and smart contracts’ automated enforcement, provides a trustworthy framework that better secures ownership and prevents unauthorized manipulation.
Cryptocurrency has emerged as a lucrative yet volatile landscape for cybercriminal activity, presenting novel challenges for law enforcement and policymakers alike. This review seeks to explore the diverse array of cybercrimes occurring within the cryptocurrency domain, examining their types, motives, techniques, and the regulatory responses shaping this complex ecosystem. Utilizing a scoping literature search methodology, this study analyzes 228 pertinent sources drawn from a pool of over 4,000 reviewed publications. The findings elucidate the intricate interplay between cryptocurrencies and illicit activities, revealing the multifaceted nature of cybercrimes within this realm. From the exploitation of the dark web for illicit transactions to the pervasive threat of crypto ransomware targeting entities globally, the review underscores the diverse methods and motivations driving such nefarious endeavors. By shedding light on the evolving tactics employed by cybercriminals and exploring future directions for technological and regulatory measures adopted by governments, this paper offers valuable insights to navigate this dynamic landscape effectively.
This article examines recent developments in United States (US) intellectual property (IP) law that directly affect the art market, namely: 1) the judicial interpretation of fair use and the use of copyrighted material to train AI systems; 2) the US Copyright Office’s refusal to register certain AI-generated works; and 3) the application of trademark law to NFTs (Non-fungible tokens). The aim of this article is to provide an overview of the constantly evolving legal landscape in this field while highlighting controversies that will likely continue to arise in the near future. As a jurisdiction where new technologies, the art market, and IP case law overlap, the US is in a unique position to reflect ongoing changes as well as in-depth interpretations of existing provisions.
Zhuo Zhang, Donghui Li, Kun Jiang, Ya Li · 6 authors
Smart contracts are self-executing programs that operate on a blockchain. Once deployed, they cannot be altered, which introduces distinct maintenance challenges unlike those found in traditional software systems. Bugs and vulnerabilities in smart contracts have led to significant economic losses, drawing increased attention to their security. The immutability of smart contracts has made thorough security checks prior to deployment a priority. In this paper, we introduce a smart contract timestamp vulnerability detection technique PropaDT with propagation-based code clone analysis. The core idea of this technique involves using dataflow analysis based on an Abstract Syntax Tree (AST) to extract propagation chains that reveal how variables interact, potentially leading to vulnerabilities. Next, we extract code snippets based on the propagation chains and compare them with known vulnerability patterns in a database. This allows us to determine whether the tested smart contract contains a timestamp vulnerability, facilitating the detection of potential timestamp vulnerabilities in the code.