Oscar M. Bedoya, Jeferson Arango‐López, Jorge Hochstetter
The management of intellectual property (IP) agreements in universities continues to rely on static legal documents that are signed, archived, and consulted when necessary, but whose content is rarely formalized to facilitate their operation and verification. Consequently, obligations, permissions, restrictions, deadlines, scopes, and exceptions often remain scattered across clauses drafted in natural language, annexes, emails, and different document versions, which hinders their monitoring and makes compliance review dependent on intensive legal and administrative work. In response to this limitation, this article proposes an ontology to formalize non-disclosure agreements (NDAs) at the University of Caldas, Colombia, understood as a specific case within the broader management of IP agreements. The proposal adopts a modular Semantic Web architecture composed of a reusable ontological core and a specialized profile for NDAs. Its construction followed the METHONTOLOGY methodology, and its specification was supported by Competency Questions (CQs), which were subsequently translated into SHACL constraints and SPARQL queries. In addition, a SKOS vocabulary is incorporated to normalize synonyms and terminological variants typical of legal drafting in Spanish, together with a lightweight weak supervision layer based on regular expressions, SKOS, and structural signals to support clause labeling and the batch generation of RDF instances. Thus, the proposal enables querying, traceability, and verification over NDA content, while offering a formal basis for progressing toward automatable controls and their eventual articulation with smart contracts.
Regulatory permissiveness is widely prescribed as the primary institutional lever for digital asset adoption. This study challenges that prescription. Analyzing NFT and DeFi adoption across 105 countries using Principal Component Analysis (PCA)-constructed composite indices and multivariate Ordinary Least Squares (OLS) regression, we find that the Frontier Technology Readiness Index (FTRI) is the dominant structural correlate across all specifications, consistently outperforming competing explanatory variables. Regulatory environments neither independently explain adoption nor are associated with it linearly: both permissive and restrictive environments outperform mostly prohibited jurisdictions, suggesting that regulatory clarity rather than permissiveness is the operative institutional dimension. NFT and DeFi markets follow empirically distinct pathways: NFT adoption shows stronger associations with digital marketplace maturity while DeFi is more closely associated with technological infrastructure, suggesting that treating Web3 as a homogeneous policy category is unwarranted. National income conditions how effectively technological readiness is associated with adoption gains, with structural determinants exhibiting considerably reduced explanatory power in lower-middle-income economies. For policymakers, these findings reframe the debate: the primary structural correlate of digital asset adoption is technological capacity, not regulatory stance, and below a development threshold, neither intervention is reliably associated with adoption gains.
System and Method for Reinforcement Learning‑Based Token Minting and Cross‑Chain Cryptographic Anchoring This archive contains the full non‑provisional patent submission for a unified digital‑asset lifecycle system integrating reinforcement‑learning‑based token minting, Merkle‑structured ledgering, and synchronized cross‑chain cryptographic anchoring. The invention establishes a deterministic, mathematically governed framework for creating, operating, and verifying digital asset states across heterogeneous blockchain networks including Bitcoin, Ethereum, and Solana. The system introduces a blueprint‑based binding mechanism, a formal kernel governed by a unified state equation, and a sovereign ledger enabling long‑term provenance and deterministic replay. A reversible 32‑byte commitment value is computed using a Sponge‑586 invariant and anchored to Bitcoin via Taproot tweaks and OP_RETURN payloads. Parallel anchoring events emit the authenticated Merkle Mountain Range (MMR) root on Ethereum and Solana, producing tamper‑evident, multi‑consensus proofs of state. A reinforcement‑learning engine dynamically adjusts minting rates based on real‑time market conditions, behavioral metrics, and system‑level variables. The system further supports gasless user interactions (EIP‑2771), zero‑knowledge compliance pathways, federated‑learning simulations, and deterministic state reconstruction through Kolmogorov integrity scoring and synthesis restoration. This archive includes the complete specification, mathematical formulations, alternative embodiments, and references to supporting research hosted on Zenodo. It documents the developmental lineage, reduction‑to‑practice demonstrations, and cross‑chain anchoring methodology associated with U.S. Patent Application No. 19/693,343.
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Blockchain Technology Applications and Security
Intellectual Property and Patents
Physical Unclonable Functions (PUFs) and Hardware Security
Victor Michelle, Natalie Michelle, Emilie Michelle, Elias Michelle
Abstract:Intellectual Property (IP) represents the largest class of assets in the global economy ($65–100 trillion) yet remains structurally absent from corporate balance sheets under GAAP and IFRS (IAS 38). Consequently, the market capitalisation of technology companies is artificially split only into Tangible Assets (TA) and a Speculative Premium (MP), with the real value of IP hidden inside MP. This technical specification outlines Version 1.0 of the IP Coin methodology, delivering a market-based spot utility token framework designed to materialize the hidden value of intellectual property into a liquid, visible asset layer (IP_visible). By purchasing IP Coin, investors directly capitalise the previously invisible IP of a public company. The platform displays three layers – TA, MP, and IP_visible – and automatically transfers purchase value from MP to IP_visible based on the strict capital conservation rule: MC = TA + IP_visible + MP. The Intangible Dominance Ratio (IDR = IP_visible / MC) updates automatically after every trade as a derived performance metric, rather than a price-setting oracle. This methodology creates the first market-based solution for IP tokenisation without altering accounting standards. Keywords: Fintech, Tokenization, Financial Engineering, Intangible Assets, AI Valuation, Copyright, Capital Markets, Web3 Architecture, Market Decomposition.
The rapid advancement of digital technologies has significantly transformed the landscape of commerce, leading to new challenges in the protection and enforcement of trademark rights. Traditionally, trademarks functioned within territorial boundaries and were primarily associated with physical goods and services. However, the emergence of digital platforms such as e-commerce websites, social media, domain name systems, blockchain technologies, Non-Fungible Tokens (NFTs), and the metaverse has expanded the scope of trademark usage into virtual environments. This Paper examines the evolving nature of trademark protection in the digital and virtual world, with particular emphasis on the adequacy of existing legal frameworks in addressing contemporary challenges. It analyzes key issues such as cybersquatting, keyword advertising, social media infringement, unauthorized use of trademarks in NFTs, and the complexities of trademark use in the metaverse. The study also highlights jurisdictional challenges arising from the borderless nature of the internet, which complicate enforcement mechanisms and legal remedies.
Intellectual Property (IP) transactions play a vital role in the contemporary global economy, encompassing the exchange of intangible assets such as patents, copyrights, trademarks, and trade secrets. These assets are fundamental drivers of innovation and economic development across diverse industries. However, conventional methods of managing IP transactions are often characterized by inefficiency, high transaction costs, lack of transparency, and frequent disputes arising from ambiguities in enforcement and contractual obligations. This study examines the potential of blockchain-based smart contracts to address these challenges by enhancing efficiency, fairness, and transparency in IP transactions. Smart contracts, which are self-executing agreements encoded in computer-readable protocols, facilitate automated execution of predetermined contractual terms without requiring intermediary intervention. The integration of blockchain technology with decentralized and secure ledger systems minimizes errors, reduces dependency on intermediaries, and mitigates disputes resulting from cumbersome and unclear procedural mechanisms in conventional IP transactions. Additionally, smart contracts streamline licensing, royalty distribution, and contract enforcement, thereby accelerating transaction processes while ensuring improved security and accountability. Blockchain decentralization further strengthens the protection of intellectual property transactions against unauthorized alterations. Smart contracts also support automated royalty allocation, enabling equitable payment distribution among creators, rights holders, and intellectual property owners. Transparency is enhanced through shared access to accurate transactional information, fostering trust among stakeholders and reducing the likelihood of legal conflicts. Despite these advantages, the adoption of smart contracts in IP transactions faces several practical and legal challenges, including regulatory recognition, enforceability across jurisdictions, compatibility with existing intellectual property frameworks, and privacy concerns associated with confidential transactional data. This article investigates how blockchain-integrated smart contracts can transform intellectual property transactions, with particular focus on improving efficiency, strengthening security, ensuring fair compensation, and promoting transparency. By examining relevant theoretical perspectives, case studies, and practical applications, the study offers insights into the broader implications of adopting blockchain technology for intellectual property management.
<b>【Description】</b>[EN]:<i>Relocation Notice:</i><br>Due to an unavoidable structural incompatibility between the mandatory data-parsing frameworks of conventional academic repositories and the strict zero-knowledge proof requirements of this archive, this item has been relocated to this environment. To protect its integrity from automated systemic interference, it is currently placed under a Permanent Embargo, functioning exclusively as a cryptographic spatial anchor.<i>Strategic Ambiguity Regarding Future Disclosure:</i><br>While this archive is strictly restricted to preserve its current integrity and trade secret classification, this status does not definitively preclude the possibility of partial or full disclosure in the future. The management of this intellectual property remains entirely under strategic discretion. Furthermore, regardless of any future discoveries or the accumulation of operational insights, I assume no obligation to update this document, provide continuous reporting, or issue prior notification regarding any changes in disclosure status, scope, or conditions.This data archive contains the restricted documentation for the "Persona-Native Principle (PNP) - Final Form."<br>The existence and integrity of this document have been legally established and secured by an electronic certified date (timestamp) issued by a Notary Public in Japan.Cryptographic Proof of Existence (SHA-256 Hash):<br>5ec4637def8bc7a45b113d6dee25e4d88672865ebd37def1c9c30c95de581145[JP]:<i>移設記録:</i><br>従来の学術リポジトリが前提とする「データ開示と自動解析の強制力」と、本アーカイブが要求する「完全なアクセス拒絶による存在証明（ゼロ知識証明）」の間に、不可避の構造的非互換性（Structural Incompatibility）が確認されました。そのため、予期せぬシステム的干渉から完全性を保護するべく、本アーカイブは独自の暗号学的アンカーとして、本環境にて恒久的なエンバーゴ（封印）下に置かれています。<i>将来の開示に関する戦略的曖昧性:</i><br>現在の完全性および営業秘密としての分類を保持するために本アーカイブは厳格に制限されていますが、この状態は、将来においてその一部または全部を公開する可能性を断言して否定するものではありません。本知的財産の管理は、完全に戦略的裁量の下にあります。さらに、今後新たな発見や運用知見が蓄積された場合であっても、私は本文書の更新、継続的な報告、および開示状況や条件の変更に関する事前通知を行ういかなる義務も一切負いません。本データアーカイブは、『Persona-Native Principle (PNP) - Final Form』に関するアクセス制限付きドキュメントを格納しています。<br>本文書の存在および完全性は、日本国公証人による電子確定日付（タイムスタンプ）により法的に保全されています。存在証明ハッシュ値 (SHA-256):<br>5ec4637def8bc7a45b113d6dee25e4d88672865ebd37def1c9c30c95de581145<br><b>[Patent Status & Strategic Protection]</b><br>[EN]:The core architecture and methodologies documented within this archive are subject to pending patent applications in Japan (e.g., Application No. 2026-000032). In accordance with our Strategic Non-Disclosure Policy, the disclosure of this specific jurisdiction and application number does not constitute a comprehensive representation of our global intellectual property portfolio. We reserve all rights to pursue, expand, or maintain provisional and formal protections across international jurisdictions without prior public notification.<br>[JP]:本アーカイブに記録された中核的なアーキテクチャおよび方法論は、日本国において特許出願中（例：特願2026-000032）です。当方の「戦略的非開示ポリシー」に基づき、この特定の管轄と出願番号の開示は、当方のグローバルな知的財産ポートフォリオの全容を示すものではありません。当方は、事前の公的通知なしに、国際的な管轄区域において仮出願および本出願による保護を追求、拡大、または維持するすべての権利を留保します。<b>【Terms of Access & Confidentiality】</b>[EN]:<b>Restriction of Access & Confidentiality:</b> The contents of this archive contain highly sensitive proprietary assets of Persona Foundry Aoi Design. All files are secured under restricted access. Any unauthorized access, disclosure, or attempt to bypass these restrictions is not permitted under applicable intellectual property guidelines.[JP]:<b>アクセス制限と守秘義務:</b> 本アーカイブの内容は、Persona Foundry Aoi Designの機密性の高い独自資産として厳格に管理されています。すべてのファイルはアクセス制限下で保護されており、不正アクセス、開示、または制限を迂回するいかなる試みも、適用される知的財産保護の観点から許可されていません。<b>【Terms of Use】</b>[EN]:<b>Disclaimer of Warranties:</b> The materials are provided "AS IS." The author makes no representations and extends no warranties of any kind, express or implied.<b>Limitation of Liability:</b> In no event shall the author be liable for any direct, indirect, or consequential damages arising from any unauthorized access, use, or inability to use the materials.<b>Governing Law and Dispute Resolution:</b> This Agreement and any disputes arising out of it shall be governed by and interpreted in accordance with the laws of Japan. Any concerns will be resolved within the appropriate legal venues in Japan designated by the author.[JP]:<b>無保証 (AS IS):</b> 本データは「現状有姿」で提供されます。著者は、明示的か黙示的かを問わず、いかなる種類の保証も行いません。<b>責任の制限:</b> 著者は、本データへの不正アクセス、使用、または使用不能から生じるいかなる直接的、間接的、または結果的な損害についても責任を負いません。<b>準拠法および紛争解決:</b> 本規約およびそこから生じるいかなる紛争も、日本国法に準拠し、解釈されるものとします。懸念事項が生じた場合、日本国内における著者が指定する適切な法的手続きに従って解決されるものとします。<b>[ License ]</b>CC BY-NC-ND 4.0 InternationalThe statements within the document take precedence over any platform terms.<br>※投稿および掲載プラットフォームの規定にかかわらず、本文内の記載を優先します。<b>[ Files & Integrity ]</b>File: PNP FINAL FORM - BILINGUAL_v1.0.pdfHash: 5ec4637def8bc7a45b113d6dee25e4d88672865ebd37def1c9c30c95de581145
We present the Creation Ledger, a protocol for token economics grounded in verified creative process rather than computational expenditure, staked capital, or attention signals. The protocol introduces Proof of Provenance (PoP) — a consensus primitive where tokens are minted exclusively through verified human-directed creative work, as validated by Cognitive Rhythm Analysis (CRA) of embedded decision trees. The protocol addresses three structural failures that have destroyed every prior creator token platform: (1) speculation crowding out utility at launch, (2) verification systems that are cheaper to forge than to use honestly, and (3) regulatory classification as securities due to revenue-sharing mechanics. The system is protected by nine provisional patent applications (193 claims across four patent families) filed with the United States Patent and Trademark Office. Patent Support: Patents 1-9 filed March 30, 2026. 193 total claims across Dense Notation, Proxy Provenance, Self-Proving Documents, Decision-Chain Provenance, Schema Registry, Delivery Protocol, Code Closure, Format-Provenance Fusion, and Document-Directed Computation.
Abstract To address issues in traditional patent valuation—such as subjective selection of dimensional metrics, weak sensitivity to high-dimensional transaction data noise, and insufficient correlation between evaluation indicators and dimensions—this study proposes a smart contract-based patent value assessment model. Firstly, existing patent valuation theories and techniques undergo systematic deconstruction and multidimensional efficacy assessment. Leveraging big data technology, a four-dimensional optimal framework integrating "technology-market-legal-risk" dimensions is constructed. Secondly, an enhanced non-negative matrix factorization algorithm (S-NMF) is designed. By incorporating diagonal matrices and fused regularization parameters, this algorithm maps the four-dimensional optimal framework into 14 quantifiable metrics using Hyperledger Fabric consortium blockchain transaction data. This addresses the core limitation of classical NMF algorithms—the inability to adjust dimension weights—enabling flexible weighting control to meet differentiated valuation needs across diverse patent application scenarios. Finally, performance analysis and simulation experiments were conducted on the patent value assessment model, comparing it with the traditional NMF algorithm. Results demonstrate that this model outperforms traditional models in both noise robustness and dimensional correlation, effectively supporting patent value assessment needs across multiple scenarios.
Objectives: The authors explore how large pharmaceutical corporations may integrate emerging decentralized technologies-such as blockchain and decentralized autonomous organizations (DAOs)-within their merger, acquisition and partnership frameworks, and how these strategies intersect with broader innovation and external sourcing models. In this context, blockchain is considered primarily as an enabling infrastructure for decentralized governance and programmable coordination-supporting mechanisms such as tokenized incentives, auditable decision trails, and new forms of intellectual property (IP) and collaboration structures. Methods: This study employed a qualitative case study methodology, combining document analysis and semi-structured interviews with internal stakeholders from a leading large-cap pharmaceutical company (herein after "Company"). Participants included executives and professionals from corporate development, scientific research, external innovation, and digital strategy units.The analysis examined how a large-cap "Company" approaches mergers, acquisitions, and partnerships, and how emerging technologies may influence these frameworks. The study focused on strategy alignment, organisational attitudes towards decentralisation, integration constraints, and perceptions of innovation value along the external sourcing continuum. Results: Acquisition and innovation strategy by the "Company" is driven by long-term alignment between external opportunities and internal priorities. Over time, the "Company" increasingly turned to external sources of innovation, leveraging technologies to improve innovation scouting, target identification, and operational forecasting. While decentralisation technologies such as DAOs are viewed as promising for early-stage innovation and collaboration, their integration is hindered by legal ambiguity, internal governance rigidity, and unfamiliarity with token-based economics. The "Company" views mergers and acquisitions (M&As) and licensing as critical to sustaining its pipeline, and sees potential for emerging technologies to accelerate preclinical decision-making and improve visibility into academic and biotech ecosystems. Conclusions: This study contributes insights into how large-cap pharmaceutical firms might adapt their innovation models in response to technological change and external pressures. While established mechanisms such as M&A and partnerships remain dominant, digital and decentralized technologies offer complementary tools for scouting, collaboration, and portfolio expansion.
Walter Hernandez Cruz, Peter Devine, Nikhil Vadgama, Paolo Tasca · 5 authors
We introduce DLT-Corpus, the largest domain-specific text collection for Distributed Ledger Technology (DLT) research to date: 2.98 billion tokens from 22.12 million documents spanning scientific literature (37,440 publications), United States Patent and Trademark Office (USPTO) patents (49,023 filings), and social media (22 million posts). Existing Natural Language Processing (NLP) resources for DLT focus narrowly on cryptocurrency price prediction and smart contracts, leaving domain-specific language underexplored despite the sector's ~$3 trillion market capitalization and rapid technological evolution. We demonstrate DLT-Corpus' utility by analyzing patterns of technology emergence and market-innovation correlations. Findings reveal that technologies first appear in our scientific literature subset before reaching patents and social media, following traditional technology transfer patterns. While social media sentiment remains overwhelmingly bullish even during crypto winters, scientific and patent activity grows less tied to short-term sentiment, tracking overall market expansion in a virtuous cycle in which research precedes and enables economic growth that, in turn, funds further innovation. We release the DLT-Corpus and companion artifacts: LedgerBERT (+23% over BERT-base on DLT-specific Named Entity Recognition (NER) task), a sentiment analysis dataset of 23,301 crypto news headlines and descriptions, tools, and code.
We present an end-to-end framework for systematic evaluation of LLM-generated smart contracts from natural-language specifications. The system parses contractual text into structured schemas, generates Solidity code, and performs automated quality assessment through compilation and security checks. Using CrewAI-style agent teams with iterative refinement, the pipeline produces structured artifacts with full provenance metadata. Quality is measured across five dimensions, including functional completeness, variable fidelity, state-machine correctness, business-logic fidelity, and code quality aggregated into composite scores. The framework supports paired evaluation against ground-truth implementations, quantifying alignment and identifying systematic error modes such as logic omissions and state transition inconsistencies. This provides a reproducible benchmark for empirical research on smart contract synthesis quality and supports extensions to formal verification and compliance checking.
The current scientific system faces systemic challenges. Decentralized Science (DeSci) has emerged as a technological extension of the Open Science (OS) movement, aiming to improve transparency, accessibility, and equity in research through blockchain and Web3 technologies. While DeSci has gained traction in Western countries, little is known about its adoption in non-Western contexts. Here, we surveyed 37 researchers and technologists active in Japan’s emerging decentralized‑science (DeSci) during spring 2024 to assess how far the movement has progressed and what impedes its progress. Roughly 60% of respondents had already worked on blockchain projects and more than 80% owned crypto assets, yet almost 90% had discovered DeSci only in the past two years. Respondents largely embraced DeSci’s five core ideals: shared governance, transparent funding, open access, shared ownership, and equitable incentives. Meanwhile, four obstacles to growth were highlighted: low public awareness, difficulty sustaining engagement, limited talent diversity, and regulatory uncertainty. Taken together, the findings suggest that Japan’s DeSci community should also invest not only in further technical changes, but also in training, in broadening its talent base, and in setting clear guidelines. This study provides a comprehensive overview of the DeSci landscape in Japan and offers recommendations for its future development.
Large language models have intensified a growing property-rights challenge in digital markets: protected works can be copied, retrieved, transformed, and recombined at low marginal cost, while ownership, licensing authority, attribution, and remuneration remain costly to verify. First, I introduce the Model Context Protocol (MCP) as an interoperability layer between AI agents and intellectual-property institutions. MCP does not define rights or settle disputes; it gives agents a standardized way to query registries, invoke licensing tools, execute payments, record usage, and preserve audit trails. Second, I develop a stylized transaction-cost model of agentic licensing and derive comparative statics for when lawful exchange expands. Lower search, verification, contracting, payment, and monitoring costs can move marginal uses from avoidance, substitution, or unauthorized use into licensed exchange, especially when rights records are reliable, license terms are standardized, and interface costs are large relative to the price of the license. Third, I explain how non-fungible tokens (NFTs) can complement MCP when they operate not as collectibles, but as machine-readable rights objects linked to work identifiers, ownership claims, license scope, payment rules, provenance records, audit obligations, and dispute forums. Music licensing is illustrative because rights are fragmented across compositions, recordings, labels, publishers, performers, territories, and use types. MCP and NFT-linked rights records can support ex ante licensing when paired with verified title, enforceable contracts, bounded delegation, human review, and off-chain legal remedies.
This Article proposes a tripartite technical and legal framework designed to restore meaningful copyright enforcement in an era of large-scale generative artificial intelligence. The framework rests on three interlocking pillars. First, it mandates embedding of non-fungible token (NFT) provenance markers in all digitally published creative works, enabling immutable registration of every instance in which data is scraped or ingested by an AI system. Second, it establishes a compulsory labeling regime requiring that all AI-generated outputs carry a blockchain-anchored attestation of their machine origin and the training-data lineage that produced them. Third, it creates a royalty-settlement layer built on a purpose-designed stablecoin that triggers instantaneous, frictionless micropayments to rights holders whenever their content is used in AI training, inference, or downstream reproduction. The Article situates this proposal within the existing doctrinal architecture of U.S. copyright law, international treaty obligations, and emerging AI-governance legislation. It then subjects each pillar to rigorous technical scrutiny—examining blockchain throughput constraints, metadata-embedding standards, privacy-preserving attribution methods, and stablecoin monetary-policy design—before offering a unified statutory and regulatory roadmap for implementation.
Classical political economy treats private property as foundational to economic coordination and individual autonomy. This paper argues that while private property remains formally intact, it has been substantively hollowed out by the erosion of privacy in the information age. The central claim is that private information—defined as the owner's privileged epistemic access to knowledge relevant to her assets—is a necessary condition for meaningful private property. When such information is no longer privately controlled, ownership persists only as legal fiction rather than effective sovereignty. Through analysis of software licensing, smart property, and decentralized finance, the paper shows how contemporary property increasingly functions as conditional, reversible, access-based arrangements dependent on informational infrastructures governed by others. Revisiting Hayek's epistemological defense of property, the analysis demonstrates that the loss of informational privacy undermines the assumptions that allowed private property to sustain an extended order. The paper engages with objections from information economics and cryptographic privacy, examines systemic risks to economic stability, innovation, and political order, and concludes that the defining challenge of our time is not the abolition of private property, but the disappearance of the private itself.
C Komalavalli, Rinki Bhati, Akhilesh Kumar Khan, Arun Kumar Tripathi · 7 authors
The swift AI-generated art development has further fueled the discussion on both authorship and ownership, as well as on whether digital rights can be enforced. The existing intellectual property paradigms lack the ability to recognise works produced by autonomous systems fully or in part, which presents proxies in the maintenance of copyright, derivatives and cross-jurisdictional identification of AI-related rights. With more and more creative outputs based on algorithmic processes, there is an urgent requirement to have transparent, tamper-resistant processes that would be able to define, assign and protect right at scale. One of the promising infrastructures to facilitate legal and economic aspects of AI-generated art is the use of smart contracts, which are the self-executable agreements that run on blockchain networks. This paper discusses how authorship claims can be encoded in smart contracts, how royalty payments can be automated, and how programmable access controls can be offered, at the same time, offering verifiable provenance by tokenizing the provenance. We analyze technical specifications of creating powerful metadata standards to cover creation parameters, level of contributions, and model lineage. Moreover, we discuss interoperability issues in the heterogeneous blockchains and digital marketplaces, which are limited to the immutability, upgradability, and long-term security. In addition to the technical design, the paper evaluates the ethical impact, such as the fairness to human designers, responsible design of AI innovators, and risks to society in general of bias, exploitation, and its unequal distribution of rights-management systems.
A. J. M. OlIVEIRA, Raimundo Corrêa de Oliveira, Vanessa Coelho da Silva, Ricardo da Silva Barboza
The increasing digitization of creative assets poses significant challenges to the protection of intellectual property. In this context, blockchain and Non-Fungible Token (NFT) technologies emerge as promising solutions to ensure the authenticity, traceability, and monetization of digital assets. This study aims to explore the landscape of technological innovation at this intersection through a systematic search in patent databases. The methodology consisted of a search on the Orbit Intelligence database, followed by a rigorous dual validation process that combined manual screening and analysis by Artificial Intelligence (DeepSeek), resulting in a final portfolio of 119 patent families. The results reveal a sharp increase in the number of filings from 2018 onwards, with a peak in 2022, and a strong geographical concentration in China. The analysis of technological domains indicates that innovations are focused on "IT methods for management" and "Digital communication," highlighting the use of the technology as a governance infrastructure. The qualitative analysis of selected patents demonstrates the sophistication of the solutions, which address issues ranging from registration efficiency to rights management for AI-generated content. It is concluded that the field is rapidly maturing, moving beyond proof-of-concept to develop specialized solutions that address complex challenges in the intellectual property ecosystem, thereby redefining protection paradigms in the digital economy.
Non Fungible Tokens have changed digital ownership and how creators earn money. Between 2021 and 2024, the market value exceeded 40 billion. However, the fast growth of the NFT ecosystem has revealed serious issues in managing intellectual property rights. There is a lot of confusion about the difference between owning an NFT and owning the copyright for the underlying content. This research looks at the gap between traditional copyright laws and blockchain-based transactions. We use a mixed methods approach to analyze this disconnect. We create a new IP rights matrix that clearly shows how copyright law relates to NFT ownership structures. Additionally, we include a business model taxonomy that sorts new commercial applications by their IP risk and sustainability factors. By examining important legal cases, smart contracts, and interviews with stakeholders, we find key problems in enforcing laws across different regions, standardizing licenses, and assessing business opportunities.
Atomic swaps represent a groundbreaking advancement in decentralized asset exchange, enabling peer-to-peer trading of cryptocurrencies across different blockchains without the need for intermediaries. By utilizing smart contract technology, these swaps allow users to securely trade assets in a trustless environment, removing the need for centralized exchanges. This paper explores the technical underpinnings of atomic swaps, the benefits they offer over traditional exchange models, and their potential to shape the future of cross-chain transactions. We examine the core mechanisms of hash time-locked contracts (HTLCs), the role of liquidity pools, and the scalability challenges inherent in atomic swap technology. Furthermore, the paper discusses the broader implications of atomic swaps for decentralized finance (DeFi), financial sovereignty, and the global cryptocurrency ecosystem. As the market for decentralized exchanges continues to expand, atomic swaps may emerge as a vital tool for enhancing the efficiency, security, and inclusivity of digital asset trading.
У статті досліджено виклики та перспективи, які несе із собою впровадження технології NFT (невзаємозамінних токенів) у сферу інтелектуальної власності. Автор аналізує вплив Четвертої індустріальної революції на актуалізацію потреби в оновленні правового регулювання у цифровому середовищі. Приділена певна увага проблемам піратства, контрафакції, а також труднощам у доведенні авторства у кіберпросторі. У цьому контексті NFT розглядається як [...]Читати далі... from Non-fungible token (NFT): Виклики та перспективи для інтелектуальної власності
Non-Fungible Tokens(NFTS) and innovative technology for representing ownership and authenticity of digital assets.This abstract explores the concept of utilizing NFTs for patenting one's own products, providing a secure and decentralized method of establishing intellectual property rights.NFTs are stored on the blockchain, which is a secure and decentralized database.This means that NFTs are tamper-proof and cannot be copied or duplicated.Patenting your own product ideas using NFTs is a great way to protect your intellectual property.By creating an NFT for your product idea, you are creating a digital record of your ownership.Additionally, NFTs can be used to track the history of your product idea, which can be helpful for marketing and sales purposes.If you are interested in patenting your own product ideas using NFTs, there are a few things you need to do.First, you need to create an NFT.This can be done through a variety of platforms, Once you have created an NFT, you need to register it with the United States Patent and Trademark Office (USPTO).The proposed approach involves creating NFTs that represent the patent documentation including descriptions, diagrams, and claims, of a particular product or invention.These NFTs can be stored on a ensuring, the immutability, transparency, and traceability of the patent information.
The rapid expansion of the digital economy heightens the need for privacy and trust in intellectual property transactions. Traditional centralised approaches to identifying legal conflicts in intellectual property contracts are prone to data leakage and fail to balance transparency with confidentiality. This paper proposes a self-identification method for legal conflicts in intellectual property contracts using zero-knowledge proofs. By combining a light gradient boosting machine learning model with the zero-knowledge succinct non-interactive argument of knowledge protocol, our approach allows verifiable detection of potential legal conflicts without revealing sensitive information. Experiments on the US patent and trademark office patent dataset demonstrate that the method achieves high performance in conflict prediction (area under the receiver operating characteristic curve = 0.872) and verification efficiency (<10 ms), providing a novel and practical framework for privacy-aware legal technology.