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538 results · page 6 of 23
Volodymyr Peschanenko, Maksym Poltoratskyi, Olga Konnova
No abstract is available for this record.
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
Feroz Ali
No abstract is available for this record.
Rana Hassam Ahmed, Jabeen Sultana, Samraiz Zahid, Muhammad Asif Habib · 6 authors
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.
Wulf A. Kaal
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.
Aaron M. Lane
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.
Saskia Hufnagel, Colin King
No abstract is available for this record.
Furrer Andreas, Wulf A. Kaal
No abstract is available for this record.
Dilan Orak
Bu çalışma, Non-Fungible Token'ların (NFT), 5846 sayılı Fikir ve Sanat Eserleri Kanunumuz (FSEK)1 kapsamındaki hükümler doğrultusunda nasıl değerlendirilebileceğini incelemektedir. NFT, blokzincir teknolojisine dayalı olarak oluşturulan, benzersiz ve değiştirilemez bir kripto varlık türü olarak, özellikle dijital sanat ve fikri mülkiyet alanlarında yeni hukuki tartışmaları gündeme getirmiştir. Çalışmada, NFT'lerin hukuki niteliği, eser sahipliği ile mali ve manevi haklar bakımından doğurduğu sonuçlar analiz edilmiştir. Minting işleminin hukuki boyutu, NFT kaynaklı telif hakkı ihlalleri ve bu bağlamda ulusal ve uluslararası düzeyde ortaya çıkan uyuşmazlıklar değerlendirilmiştir. Araştırmada doktrinsel yöntem benimsenmiş; literatür taraması, mevzuat incelemesi ve örnek dava analizleri yoluyla konu çok boyutlu ele alınmıştır. Birinci bölümde, eser kavramı, eser sahibinin hakları ve dijitalleşmenin bu haklara etkisi değerlendirilmiştir. İkinci bölümde, blokzincir teknolojisi, kripto varlık kavramı ile türleri, NFT'nin teknik yapısı ve hukuki niteliği irdelenmiş; eşya, kıymetli evrak veya gayrimaddi hak olarak sınıflandırılmasına yönelik farklı yaklaşımlar karşılaştırılmıştır. Üçüncü bölümde minting işlemi ve NFT'lerin 'eser' sayılıp sayılamayacağına dair doktriner tartışmalar ele alınmış; NFT satışlarında pay takip hakkının uygulanabilirliği incelenmiştir. Bölümün sonunda, son zamanlarda sıkça gündeme gelen ve alanında ilk örneklerden olan, uyuşmazlıklar değerlendirilmiştir. Çalışmanın sonunda, NFT'lerin FSEK kapsamında net bir şekilde tanımlanması gerektiği, eser niteliğinde NFT'ler için hak sahipliği ile ilgili belirsizliklerin giderilmesi gerektiği ve pay takip hakkının dijital ortama uyarlanması yönünde yasal düzenleme ihtiyacı olduğu sonucuna varılmıştır. Bu yönüyle çalışma, literatürdeki teorik tartışmaları somut dava örnekleriyle destekleyerek Türk hukukuna özgün katkılar sunmayı hedeflemektedir.
Juman Alkhateeb, Mahmoud Ismail, Firas Massadeh, Haneen Mansour Almansour
No abstract is available for this record.
Joseph Lee, J. M. Lee
No abstract is available for this record.
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.
Shobhit Navani, Giuseppe T. Cirella
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.
Claudia S. Quiñones Vilá
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.
Xiangyang Feng, Wen Chen
Smart contracts, one of the most prominent applications of blockchain, are changing the way sectors like finance and law operate. On the flip side, code vulnerabilities on smart contracts are bad news for all, even more for those that trade and resell large amounts of digital assets, since the possible consequences can be disastrous. In this study, we propose SC-CCA, a new deep learning framework that specifically tackles the limitations of conventional methods for detecting smart contract vulnerabilities. SC-CCA embeds CNN combined with Bi-LSTM and Self-Attention Mechanism for further improving the extraction of features from a contract code. In this framework, the use of pre-trained CodeBERT language models for word embedding improves the ability of the feature extraction module to obtain more comprehensive semantic information and context-related information. Feature extraction and pipelined feature concatenation at different levels improve detection and robustness. Experimental results show that, especially in the context of vulnerability detection, SC-CCA achieves higher accuracy, recall and F1-score when compared to existing approaches on the Smart Willed datasets. Our research offers valuable insights for analyzing complex code and detecting a wider range of vul-nerabilities in smart contracts.
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.
Geraldine O. Mbah
The rapid advancement of technology in the 21st century has brought intellectual property [IP] to the forefront as a critical asset in the tech industry.Licensing agreements, essential for fostering innovation and collaboration, face significant challenges in efficiency, transparency, and enforcement.Traditional licensing processes are often plagued by inefficiencies, including lengthy negotiations, manual documentation, and disputes arising from ambiguous terms.This paper explores the transformative potential of artificial intelligence [AI] and blockchain-based smart contracts in automating and enforcing IP licensing agreements.Smart contracts, programmable agreements executed on blockchain platforms, offer unprecedented opportunities for ensuring transparency, reducing administrative burdens, and automating royalty payments.When integrated with AI, these contracts can analyse vast datasets, predict licensing trends, and provide tailored recommendations, enabling more informed decision-making for licensors and licensees.Furthermore, the immutable nature of blockchain enhances trust by recording transactions securely and transparently, reducing the likelihood of disputes and fraud.This study also addresses challenges associated with adopting these technologies, including interoperability, scalability, legal implications, and ethical considerations in data use.It presents case studies from the tech industry, illustrating successful implementations of AI-powered smart contracts for IP licensing.By combining AI's predictive capabilities with blockchain's transparency and automation, companies can create robust frameworks for managing complex licensing agreements.The paper concludes that integrating AI and blockchain in IP licensing has the potential to revolutionize the tech industry by enhancing efficiency, fostering trust, and driving innovation.However, strategic implementation and stakeholder collaboration are crucial for realizing these benefits.
S - Sriraghavi
Blockchain Technology, also known as Distributed Ledger System, collects the data stored in enciphered blocks, which are closely linked to hash pointers. These hash pointers, links one block to another, which together forms a chain, known as the Block Chain. Blockchain and any other form of distributed ledger technologies, creates a trustworthy and a transparent record, by allowing multiple parties to a transaction to substantiate what will be entered in the ledger advanced. It has a multi-faceted utilization, where it can reserve and protect any type of data and can also, encrypt the Data in stored in Independent Data Blocks. These chains have an unaccompanied and unassisted time snaps, which secures the indivisible data, collected from consumers. This distributed ledger technology, creates a secure, time-stamped and immutable chain of information, which prevents counterfeiting and ensures that, the IP systems, are properly being traced. Blockchain, also supports smart contracts, which are self-executing contracts with the terms of the agreement directly written into code. Smart contracts can automate the licensing and royalty payments for IP, ensuring that creators are compensated fairly and transparently. It also facilitates the creation of decentralized marketplaces for buying, selling, and licensing Intellectual Property. Thus, this reduces the need for intermediaries and can also lower transaction costs, which increases the access to IP for potential buyers and licensees. Therefore, where a particular society is adapting up, to explore the unexplored, protection of Intellectual Property by using Blockchain, could play a vital role in the development and expansion of the Indian Economy. Thus, This research paper, aims to spell out the role of Block Chain technology, in protecting the data embedded in Intellectual Property Rights, which ensures to create a secure, transparent and a decentralized protection, for Intellectual Property Rights.
Pudsadee Boonrawd, Kittipong Yoonirundorn
Digital certificate forgery is becoming increasingly common and impacting information security. This research develops a framework and system for verifying digital document signing certificates by applying blockchain technology and smart contracts. Smart contracts are created on the Ethereum network to define various conditions in developing information systems that support adding digital certificates to the blockchain, verifying digital certificates, and accessing digital certificates. The research tested the security of smart contracts using the Slither tool and analyzed the shortcomings of smart contract development using the Solhint tool. The research results indicate that smart contracts can function correctly without security risks and can be used to verify digital certificate forgery. Additionally, smart contracts can be utilized in developing information systems and further developed with other related research in the future.
�. Schuler, Felipe Octaviano Delgado Busnello, Anderson Ricardo Yanzer Cabra
In the current state of the art, systems exist for the transfer of intangibleassets protected by Intellectual Property, consolidated through legal monopolies, either by attributive systems (such as patents and industrial designs) or automatically protected (such as copyrights andrelated rights). Some of these systems, or their respective methods, are described in scientific literature. Among these, some methods use blockchain technology, and a smaller subset (entirely contained within the former) also uses smart contract technology, though these areindependent tools. Although industrial secrets also constitute monopolies, the computerized or cryptographic solutions applied to other types of assets protected by different forms of intellectual property cannot be applied to these assets due to their sui generis nature, lackinga monopoly that exists independently of their non-disclosure. The need to maintain secrecy arises from Arrow’s Information Paradox, a phenomenon in which revealing the secret implies its transfer. This phenomenon hinders the potential transfer of industrial secrets and makes it impossible to adopt existing systems applicable to other types of intangible assets.
Asma Besbas, Amira Ailane, Laïd Kahloul, Sihem Slatnia · 5 authors
The introduction of blockchain technology and smart contracts has fundamentally transformed multiple industries, offering improved security, transparency, and automation. Nevertheless, guaranteeing the security and correctness of these systems continues to be a crucial challenge. Existing formal methods enable the blockchain and smart contract developers to i) provide an abstract model of the systems; ii) specify the important properties that must be maintained in the systems, e.g., safety, correctness, and security; and iii) verify that the proposed abstract model fulfills the property specification. Thus, avoid costly errors that can occur in the future and take anticipation measures. This work explores the utilization of three basic formal methods, namely model checking, theorem proving, and formal verification through translation to$\boldsymbol{F^{*}}$programming language, to verify and confirm the correctness and security of blockchain systems and smart contracts functionality.
Haoli Chen, Chunlei Zhu, Liang Zhang, Yan Zhao · 5 authors
Smart Contract, as a vital component of blockchain technology, significantly enhances transaction efficiency and transparency by automatically executing, controlling, or documenting legal events and actions. However, with the widespread adoption of smart contracts in various fields such as the financial industry, supply chain management, digital identity, and more, concerns over their security and reliability have become increasingly prominent. Mutation Testing, an effective software testing technique, can reveal the ability of test cases to detect code changes, thereby evaluating the adequacy of testing. This paper provides a comprehensive review of the latest research progress in smart contract software testing techniques based on mutation testing. It analyzes the applicability, challenges, and future development directions of mutation testing in the smart contract domain.
Manal Jlil, Kaoutar Jouti, Chakir Loqman
Reducing crime rate in a country is the most important concern of developing robust systems to automate the criminal record-obtaining process. Generally, the criminal record is managed manually, which makes the information collection from other criminal records very difficult. Therefore, investigations that could be carried out using criminal records to understand the purpose of crime and countering it are outdated. However, the integrity, security, and traceability of data exchange, especially for the judicial sector are the most frequent issues faced by information systems of public organizations. In this paper, we present a study of using blockchain technology and smart contracts to design a new architecture for a decentralized system to manage criminal record storage. This proposed architecture automates the process of getting a criminal record by moving past the techniques employed in developing traditional systems of data management such as centralized systems. In this study, blockchain technology is used to ensure data security, integrity, and traceability as well as ensure timely access to criminal records, and smart contracts are used to allow traceability and authenticity. This architecture will significantly reduce the impact of corruption in law enforcement by eliminating fraud cases, which will revolutionize E-governance in the Moroccan country.
S. Balaji, Ram Dantu, Kritagya Upadhyay, Thomas McCullough
Many people find the legal system to be convoluted and resource-intensive with all of the complications, which often derive from the vagueness and ambiguity of legal texts, that arise in its processes. Oftentimes, legal processes become inconvenient or even inaccessible to parts of the general population. The integration of artificial intelligence (AI) and blockchain technology into legal processes, particularly in the interpretation of contract transactions, promises to revolutionize the legal field by enhancing efficiency and reducing human intervention. The conversion of legal contracts into smart contracts specifically has the power to make legal transactions auto-executable and instantaneous. However, this convergence introduces a significant challenge in how to automate the process of converting a legal contract, written in text, into a smart contract, written in code. This paper presents a comprehensive evaluation of how artificial intelligence can achieve complete automation of this conversion by generating legal contract interpretations and employing a dual-framework analysis based on the metrics of Enforceability and Acceptability. Through an in-depth examination of the opinions of legal professionals and AI-generated contract interpretations, we explore the extent to which AI can reliably interpret the vagueness and ambiguity in legal texts through interpretations and translate legal language into smart contract code while adhering to legal standards and ethical considerations. This paper contributes to the ongoing discourse on the role of AI and smart contracts in law, proposing a strategy to make the legal system more accessible and offering insights for legal practitioners, AI developers, and policymakers on navigating the complexities of AI-driven legal interpretations.