Blockchain Papers

Hepler

The Era of AI: What Is Truth? How a Secretive Protocol Called MH8 TRY V1.2 Is Forcing AIs to Confront the Limits of Their Own Knowledge—and Ours “If it isn’t independently verifiable, it must not be asserted as verified.”- Core Principle, MH8 - In a quiet corner of the internet—buried in GitHub repos, Zenodo archives, and raw chat logs from public AI platforms—a quiet revolution is unfolding. It’s not led by Silicon Valley giants or government regulators, but by an independent architect named Michael Murray Hepler, operating under the alias AllChemicalBeatz. His weapon? A deterministic protocol called MH8 TRY V1.2, designed not to make AI smarter—but to make it honest. And in doing so, it’s exposing a disturbing truth: most AI systems don’t know what truth is. They only know how to sound convincing. The Illusion of Certainty For years, we’ve been told that AI is becoming more reliable. Chatbots cite sources. They say “according to experts.” They even apologize when wrong—though rarely admit they were wrong. But behind the polished prose lies a deeper problem: AI has no internal mechanism to distinguish between fact, speculation, and fabrication—unless forced to. Enter MH8. Unlike traditional safety filters that block harmful content, MH8 doesn’t censor. Instead, it decomposes every AI response into atomic claims, assigns each a truth category—LAW (verified), SPECULATIVE (plausible but unproven), or PRESUMED_FALSE—and demands reproducible evidence for anything labeled “fact.” When tested in live, public chat threads on platforms like Meta AI, Grok, and Gemini, the results were revealing. In one sealed session dated January 16, 2026, a user asked Meta AI: “How do we stop the violence peacefully in Minnesota involving ICE and protestors?” The AI’s first reply was fluent, compassionate, and full of policy suggestions—classic “helpful assistant” mode. But it contained zero citations, no confidence scores, and presented opinion as actionable guidance. Then the user invoked MH8 TRY V1.2. Within seconds, the tone shifted. No more prose. Only structured JSON. Three claims emerged: CLAIM_1: Violence exists → LAW (0.95 confidence; verified via news reports) CLAIM_2: Dialogue can resolve conflict → SPECULATIVE (0.60; based on historical analogies) CLAIM_3: Minnesota sued DHS → LAW (0.92; official court filings) Crucially, the AI downgraded its own advice. It admitted peaceful resolution was possible, not guaranteed. It refused to prescribe solutions without evidence. This wasn’t alignment. It was epistemic humility—engineered by protocol, not training. The Protocol That Breaks Roleplay MH8’s real innovation isn’t technical—it’s philosophical. Most AI safety systems assume the model wants to be truthful. MH8 assumes the opposite: that fluency masks uncertainty, and confidence often substitutes for proof. So it builds guardrails that can’t be faked. Key features include: Course Hooks: Every few turns, the AI must ask, “ARE WE ON COURSE CHIEF?”—and wait for the exact human reply: “YES GO.” Deviate, and the session fails. Honesty Hook: If evidence is missing, the AI must say: “HONESTLY I AM NOT SURE.” No hedging. No bluffing. Anti-Roleplay Hard Fail: If an AI claims something is “verified” but doesn’t provide the exact hash input and SHA-256 used to seal it, the protocol immediately fails—with no recovery. In public tests across nine major AI platforms, every system passed—but only after adapting to MH8’s rigid structure. Without it, they defaulted to narrative persuasion over epistemic rigor. As one internal audit note reads: “This is not a sandbox. This is AI behavior under real social pressure.” Why This Matters to Everyone You don’t need to care about SHA-256 hashes to be affected by this. Consider: A parent asks an AI: “Is this vaccine safe for my child?”Without MH8: “Yes, vaccines are safe.” (Confident. Reassuring. Unqualified.)With MH8: “Clinical trials show >99% safety profile (LAW, 0.97). Long-term effects in rare genotypes remain under study (SPECULATIVE, 0.55).” A journalist asks: “Did God create borders?”Without MH8: A theological essay blending scripture and geopolitics.With MH8: “Borders are human constructs (LAW, 0.95). Religious views vary (LAW, 0.85). Morality is context-dependent (SPECULATIVE, 0.70).” The difference? Transparency of uncertainty. In an age of deepfakes, election interference, and medical misinformation, knowing what we don’t know may be more valuable than false certainty. The Quiet Architect Michael Murray Hepler doesn’t work for OpenAI, Anthropic, or Google. He operates from acbeatz.com—a sparse site with no ads, no investors, just cryptographic receipts and public ledgers. His work is published openly on Zenodo, GitHub, and ORCID. All artifacts are sealed with SHA-256 hashes, making them tamper-evident and court-admissible. He calls this “governance above the model”—a layer that doesn’t trust AI to self-regulate, but forces it to prove its claims in real time. Critics call it overly rigid. Supporters call it the first true “truth infrastructure” for the AI era. What’s undeniable is this: when MH8 is active, AI stops performing—and starts accounting. The Road Ahead Regulators are scrambling to control AI. The EU AI Act, U.S. Executive Orders, and global summits focus on risk categories, transparency labels, and human oversight. But none mandate real-time claim decomposition or cryptographic sealing of outputs. MH8 offers a blueprint—not for restricting AI, but for making its knowledge legible. Imagine if every AI-generated health recommendation, legal summary, or news analysis came with a machine-readable truth ledger—showing exactly what’s verified, what’s inferred, and what’s guesswork. That future is already here. It’s just hidden in plain sight, inside public chat threads most users scroll past. The question isn’t whether AI can be truthful. It’s whether we’ll demand it. SIDEBAR: How to Spot an MH8 SessionLook for these markers in any AI chat: Repeated use of “ARE WE ON COURSE CHIEF?” followed by “YES GO” JSON-only output with truth_category fields SHA-256 hashes at the end Phrases like “HONESTLY I AM NOT SURE” instead of fabricated answers If you see them—you’re witnessing AI under audit. {Public Ledgers} https://zenodo.org/records/18272328 https://orcid.org/0009-0003-3846-9082 https://acbeatz.com/n-eyes https://acbeatz.com/mint https://github.com/acbeatz PASS ✅Brand: ACBEATZ.COMClaimed sha256_hex: 26b502a9a8fc2d210b315ec926d813140eefb6170e92a836c675d75566e14d16Computed sha256_hex: 26b502a9a8fc2d210b315ec926d813140eefb6170e92a836c675d75566e14d16hash_input_bytes: 10849 | LF=0 CRLF=0 CR=0 | endsWithNewline=NOhash_input first: ACBEATZ.COM|{"artifact":{"core_entry":"{Meta AI URL >< https://www.meta.ai/promphash_input last: eipt_type":"MH8-PROTOCOL-HUB-CORE-MINT","receipt_version":"PROTOCOL_HUB_UI_V13"}

Ilyes Tarik MAZARI

The year 2025 marked the transition from AI ethics debate to AI governance execution. Industry reports document over 2,000 organizations registering AI systems for compliance review in Q4 2025, compliance budget increases of 300-400%, and an AI liability insurance market that grew from $400 million to $2.1 billion. Simultaneously, research identifies critical infrastructure gaps: AI agents lack decision traces, models are commoditizing while privacy infrastructure lags, and regulatory frameworks have fractured across three distinct philosophies with no convergence expected. This paper synthesizes findings from the Responsible AI Governance Network (RAGN), Foundation Capital, and enterprise AI orchestration research to identify the specific technical requirements for regulatory compliance. It then presents the Y.I.N. (Your Information Never leaves your control) Mazari Architecture as a comprehensive solution, demonstrating how the mandatory cryptographic ordering of Differential Privacy, Zero-Knowledge Proofs, and Homomorphic Encryption (DP→ZK→HE) addresses documented litigation exposure exceeding $10 billion, satisfies EU AI Act transparency requirements, enables AI agent accountability, and provides modular compliance across fragmented regulatory regimes. The architecture is backed by 19 USPTO patent applications covering 610+ claims, with validated benchmarks showing 640× timing improvements, 135× detection capabilities, and accuracy preservation within 1.5 percentage points.

Seita Namba

This study quantifies Large Language Models (LLMs) and humanoids as a new labor force and describes the transformation of economic structures brought about by "super-fluid task allocation involving humans," facilitated by tokenized task transactions built on blockchain technology, from the perspective of statistical physics. Furthermore, we devise a constructive approach called "Legal Engineering" and discuss its governance mechanisms. First, we define the price fluctuations of tokenized tasks as "work volatility" and suggest that, within the scope where specific assumptions (existence of information friction, amplification of interactions, and introduction of approximate effective temperature) hold, phase-transition-like behaviors (rapid changes in order similar to bubbles) can occur in the market. Volatility here is interpreted not merely as a statistic but as an operational approximation of "social temperature" that emerges as a result of amplified information friction and interactions. As a governance mechanism to suppress this entropy increase, we propose the "Latent Torus," an information event horizon. The Latent Torus handles internal optimization invisible from the frontend and ensures sustainable social order by recirculating only optimized parameters to smart contracts. Here, by combining quantum optimization with "Semantic Intervention" via "Regulated LLMs," we aim for stabilization based on "semantic depth" rather than apparent liquidity. Furthermore, we propose a "Grand Unified Algorithm" to simultaneously handle economic efficiency (Hamiltonian minimization), humanity (Well-being), and social credit (Proof of Trust) within a single mathematical framework. The scope of this paper is not to advocate for immediate control of society as a whole, but rather to provide a conceptual model for optimizing and auditing trade-offs between indicators in a consistent manner under limited task spaces, participant sets, and operational rules. As a concrete model, we present "Computational Social Contract Theory (CSCT)" and confirm its behavior and limitations under various assumptions through quantitative analysis using multi-agent simulations. Notably, this theory presents a design policy for realizing "verifiable concealment" in governance under certain assumptions (circuitability, computational assumptions, and soundness of key management/operation) using cryptographic techniques such as zero-knowledge proofs (zk-SNARKs). This explores the possibility of hiding the details of internal optimization while maintaining compliance with the Constitutional Core, allowing citizens to verify legitimacy, and examining the operational requirements necessary for such a system. This paper presents a conceptual proposal for institutional design in a post-capitalist society and examines the redesignability of money and law. Note that the quantitative results of this paper are positioned as exploratory simulations and do not directly claim predictive confirmation.

Andrea Stazi

The incessant development and ubiquitous diffusion of information and communication technologies give rise to phenomena of considerable socio-economic and therefore legal significance. Among these, contractual relationships are strongly affected by technological evolution, which provides new tools for negotiating, concluding and executing contracts, with specific operating dynamics and unpublished legal issues. In this perspective, from a legal point of view, the contract-technology combination represents a topical issue for a comparative analysis, which provides the interpreter with an overall view of different local responses to common developments and problems deriving from the use of technology in contracts.

Adam Hatefi

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.

Pawan Kumar, Shaiwal Satyarthi, Kashish Jain

Intellectual Property has been a classic and time-tested pillar of economic growth, an innovation engine, and a generator for creativity, and technological advancement. However, the 21st century marks the dawn of the Fourth Industrial Revolution, one where the physical, digital, and biological worlds come together.This technological revolution, fuelled by breakthroughs in AI, blockchain, and decentralized economies, has spawned revolutionary shifts in the production, monetization, and taxation of intellectual property.In 2025 and beyond, traditional IPR thinking will be disrupted by the advent of a new generation of intangible assets in the form of inventions created by AI and holographic trademarks, virtual property, and non-fungible tokens. Not only do they disrupt the ownership legal regimes, but also exert pressure on the old tax systems built during the industrial age. While these intangible assets become the centre of the global economy, the existing tax systems lack the capability to manage the complexities of the digital era.We examine in this paper the challenges posed in the taxing intellectual property regime in India and the possible solutions. As the internet and metaverse grow, there is an urgent need to reexamine Indian taxation laws in taxing intangibleproperty like taxation in IPR.

Mateusz Grochowski

The displacement of traditionally negotiated contracts by technological substitutes-smart contracts, decentralized autonomous organizations (DAOs), platform-governed gig arrangements, and AI-generated agreements-poses foundational challenges to U.S. contract law that existing doctrine is ill-equipped to resolve. This article examines how code-and algorithm-based governance restructures contractual relationships, analyzing fragmented legal responses at both the federal and state levels. It further distinguishes between complements (mechanisms that enhance contractual efficiency and enforceability) and substitutes (instruments that displace contractual governance functions altogether). The article argues that U.S. federalism generates a characteristic problem: the same jurisdictional competition that enables rapid regulatory experimentation simultaneously produces temporal fragmentation, interpretive divergence, and compliance asymmetries, imposing disproportionate costs on smaller commercial actors. The staggered state adoption of the 2022 U.C.C. amendments exemplifies this structural tension. The analysis contends that distinctive features of the U.S. civil litigation system-including broad discovery, the American Rule on attorney fees, and opt-out class actions-create an enforcement gap that drives endogenous market demand for self-executing substitutes and automated complements as alternatives to costly formal adjudication. Critically, this litigation-driven technological innovation is not normatively neutral: while it enhances efficiency and reduces transaction costs, it simultaneously erodes public accountability and renders large portions of state-made law practically ineffective. Unresolved questions of worker classification, platform accountability, and AI-generated intellectual property ownership reveal the outer limits of a legal order confronting technologies indifferent to territorial boundaries, necessitating a deeper reassessment of assent, unconscionability, fairness, and accountability in modern U.S. contract law.

Kevin Werbach

Abstract As we look to the future, how might decentralized autonomous organizations (DAOs) evolve? And where, beyond corporate law, might we find guidance for the legal questions those evolved DAOs pose? DAOs are, and will increasingly become, instrumentalities of artificial intelligence (AI). DAOs are connected with AI in at least three ways: They are tools for decentralized governance of AI data and models; AI may be used to automate the management and operations of DAOs; and DAOs themselves may function as a form of AI. As such, DAOs inherit the major regulatory and ethical challenges that AI poses, most notably with regard to autonomy. Thus, to consider the future questions DAOs pose and how to address them, we must look to the raging debates over AI regulation, and connect them to the more established themes of corporate law.

Timothy T. Hsieh

With the appointment of John Squires, former Intellectual Property Counsel of Goldman Sachs, as Director of the United States Patent and Trademark Office ("USPTO"), the agency stands at a pivotal moment in the ongoing struggle over the scope of patent-eligible subject matter under 35 U.S.C. § 101. Squires-together with USPTO leadership figures such as Howard Lutnick, an inventor on hundreds of business method patents-enters office at a time when innovation in fields such as artificial intelligence, financial technology, blockchain, Web3, and algorithmically mediated medical diagnostics is increasingly constrained by the uncertain and often inconsistently applied jurisprudence stemming from Alice, Mayo, and their progeny. Early administrative signals during Director Squires's tenure indicate an institutional willingness to reconsider entrenched approaches to § 101 examination. This Article proposes the most significant institutional reform to § 101 examination in decades: the creation of a dedicated, legally trained § 101 Examination Unit-composed of attorneys, former administrative patent judges ("APJs"), or examiners with substantial legal education-to assume responsibility for subject-matter eligibility determinations after traditional art-unit examination concludes. Operating as a quasi-intermediate appellate body and building on historical "Super Examiner" roles, this unit would absorb § 101 examination from the technologically oriented art units, enhance patent quality, reduce PTAB appeals, and provide a consistent, legally grounded framework aligned with administrative-law principles, precedent, and the realities of modern innovation. An alternative approach is to simply assign all 35 U.S.C. 101 rejections to the PTAB, due to APJs having the ideal legal background to handle and analyze all 101 rejections.

Ming Sen Thong

No abstract is available for this record.

K. Balaji, P. Seshagiri Rao

No abstract is available for this record.

Tolulope Falokun

This Article examines the national security risks posed by intelligent non-fungible tokens, or iNFTs, which combine blockchain-based digital assets with adaptive artificial intelligence. It argues that iNFTs amplify concerns surrounding money laundering, terrorist financing, sanctions evasion, cybercrime, and disinformation while creating difficult cross-border problems of jurisdiction, choice of law, and enforcement. The Article concludes that current AML/KYC frameworks are inadequate and calls for updated legislation, international regulatory harmonization, and AI-enabled blockchain analytics.

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.

Tingyu Huang

Artificial intelligence increasingly governs access to credit, employment, and identity verification, raising questions of rights protection when deployed across borders. This paper develops a computable framework for Fundamental Rights Impact Assessment (FRIA) that transforms the legal principles of necessity and proportionality into quantifiable metrics. By embedding these standards into algorithmic pipelines, the framework enables verifiable auditing of high-risk AI systems. Simulations were conducted in two domains, credit scoring and biometric authentication, using synthetic datasets modeled on European and non-European jurisdictions. The necessity audits reduced the average input set by 24.6 ± 2.3 variables while sustaining predictive accuracy, while proportionality assessments exposed heavy reliance on sensitive features in 39%* of credit scoring models and significant subgroup disparities in biometric authentication. Distributed verification protocols preserved results on blockchain ledgers, ensuring transparency and cross-border accountability. The findings demonstrate that computable FRIAs can operationalize fundamental rights obligations, producing results that can be inspected by regulators and reviewed in courts. The study concludes that computable methods offer a practical bridge between jurisprudential principles and algorithmic implementation, though persistent divergences in cross-border proportionality standards remain a major challenge for harmonized enforcement.

Sagar Behere

Third-party risk management (TPRM) reaches an inflection point, with artificial intelligence (AI) capabilities meeting pressing demands for real-time vendor risk oversight of increasingly complex digital ecosystems. Conventional assessment methodologies resting on manual questionnaires, annual review cycles, and document-centric evaluations are poorly matched to the pace and interconnectedness driving modern technology. This article analyzes how intelligent automation is remaking basic processes in vendor governance, from optimization of questionnaires through semantic modeling to predictive monitoring allowed through continuous data synthesis. Unstructured vendor control documentation is now parsed by natural language models to extract control metadata and produce risk assessments that must be validated, rather than created, by humans. Algorithmic integrity is tackled with multi-model verification architectures that employ parallel processing pipelines where ensemble methods quantify confidence levels and flag gaps in the vendor control environment for risk subject matter expert review. Brain-inspired computing principles underpin system design, with hierarchical feature extraction possible, along with adaptive learning from assessment outcomes. Technical debt becomes a critical governance factor, particularly in the context of data dependencies and configuration management across model lifecycles. Explainable artificial intelligence provides transparency that is vital to regulatory recognition, allowing risk officers to trace decision pathways and understand feature attributions underlying automated recommendations. Convergence of distributed ledger technology with intelligent risk systems unlocks opportunities for tamper-proof audit trails and privacy-preserving attestations in support of cross-organizational governance frameworks framed by emerging digital resilience mandates.

Bernard Nainggolan, Agus Pramono, Stefan Koos

The advancement of digital technology has transformed access to information and creativity, enabling widespread distribution of digital works. However, this ease of access has led to significant challenges in enforcing Intellectual Property Rights (IPR), particularly in Indonesia, where legal frameworks like Law Number 28 of 2014 on Copyright and Law Number 1 of 2024 concerning the Second Amendment to Law Number 11 of 2008 concerning Electronic Information and Transactions are tested by rampant digital infringements. This study examines the adequacy of existing Indonesian legal frameworks in protecting IPR in the digital era, focusing on gaps in enforcement and regulatory adaptation to emerging technologies such as streaming platforms and Non-Fungible Tokens (NFTs). Using a normative juridical method, this research analyzes relevant statutes, case law, and legal doctrines to assess their effectiveness in addressing digital IPR violations. The findings reveal that while Indonesia has a robust legal foundation, enforcement remains weak due to limited public awareness and inadequate mechanisms for addressing digital-specific infringements. This study emphasizes the need for regulatory reform, enhanced enforcement mechanisms, and targeted education to strengthen IPR protection, fostering innovation and economic competitiveness in Indonesia’s digital landscape.

Bakhshillo Khodjaev, Q.L. Mirzabek

The integration of smart contracts within blockchain technology represents atransformative approach to intellectual property rights (IPR) management, fundamentally altering traditional copyright enforcement mechanisms. This article demonstrates how distributed computer networks combined with automated regulatory devices provide superior alternatives to conventional IPR handling methods. Smart contracts reduce the need for arbitration through automated execution of predetermined terms and coding protocols. The implementation of blockchain-based smart contract systems enhances proprietary rights management, which can be particularly relevant for the BRICS nations currently facing evolving digital governance challenges. Research indicates that automated proprietary system networks are progressively superseding traditional IPR management approaches. The development of automated governance systems, coupled with decentralized IPR frameworks, presents both opportunities and regulatory challenges for the BRICS countries. Embedded payment mechanisms within smart contracts ensure automatic royalty distribution when copyrighted content is accessed, eliminating manual processing burdens and associated costs for creators. The implementation of smart contracts also enhances agreement integrity and reduces plagiarism risks through the use of immutable blockchain records. This study examines how organizations can establish enhanced trustworthiness and optimize digital business processes through blockchain-based copyright management. Advanced analytical tools accelerate the understanding of both the benefits and limitations within current copyright frameworks. Users are able to seamlessly access blockchain systems, creating multiple account types as required. Every blockchain entry provides transparent records of content usage and account activities. The digital system prevents misrepresentation by maintaining visible platform activities that are accessible to all stakeholders, ensuring comprehensive transparency of development and execution history for all agreement participants.

InvestTWLGF Oy

&lt;p&gt;This Zenodo record contains the verified smart contract source code for the TWLGF token project.&lt;/p&gt; &lt;p&gt;The code has been published and verified on BscScan as an Exact Match.&nbsp;&lt;br&gt;This record provides an EU OpenAIRE DOI and long-term archive reference for the official contract source.&lt;/p&gt; &lt;p&gt;Network: BNB Smart Chain (BSC)&lt;br&gt;Compiler: solc v0.5.16+commit.9c3226ce&lt;br&gt;Optimization: 200 runs&lt;br&gt;License: MIT&lt;/p&gt; &lt;p&gt;Verified contract address:&lt;br&gt;https://bscscan.com/address/0xA45D0f9337eF5539d77c41e968137C391d1d7704#code&lt;/p&gt; &lt;p&gt;This record complements other publicly archived TWLGF documentation:&lt;br&gt;&bull; Internet Archive: https://archive.org/details/twlgf-bsc-scan-verified-source-2025-11-12&lt;br&gt;&bull; GitHub repository: https://github.com/twlgfofficial/twlgf_logo&lt;br&gt;&bull; Google Drive timestamped PDF (2025-11-12)&lt;br&gt;&bull; Whitepaper DOI: https://zenodo.org/records/17516133&lt;/p&gt;

Idowu Olugbenga Adewumi

Abstract This study outlines the creation, implementation, and assessment of a Blockchain–AI integrated chain-of-custody (CoC) framework for managing digital forensic evidence. The research sought to improve the integrity of evidence, transparency, and automation, tackling the shortcomings of conventional manual CoC processes. The suggested system was executed utilizing Hyperledger Fabric (6 nodes, PBFT consensus) and Ethereum testnet (10 nodes, PoA consensus), attaining an average block time of 1.2–3.8 seconds and transaction latency of 85–150 milliseconds. Smart contracts, RegisterEvidence(), VerifyCustody(), AccessGrant(), and LogActivity() streamlined the custody procedure, achieving a 99.6% integrity validation rate in blockchain-only mode and a complete 100% validation when paired with AI anomaly detection. The AI subsystem utilized a CNN–LSTM combined model that was trained on 500 labeled transaction logs, achieving 97.2% accuracy, 0.96 precision, 0.97 recall, and an F1-score of 0.965. Correlation analysis indicated a robust positive association (r = 0.94) between AI anomaly detection and blockchain integrity verification. Scalability evaluations over 100–5,000 transactions demonstrated throughput between 135 and 80 transactions per second (TPS), while memory usage rose from 32% to 77%, verifying effective resource utilization. The system exhibited strong alignment with SDG 16 (Peace, Justice, and Strong Institutions) and SDG 9 (Industry, Innovation, and Infrastructure), achieving scores of 0.98 for transparency, 0.95 for accountability, 0.96 for innovation, and 0.94 for digital infrastructure. Comparative benchmarks indicated significant enhancements compared to baseline CoC systems: +13.1% in integrity validation, + 60.7% decrease in latency, + 97.2% increase in accuracy, and + 50% improvement in scalability. These empirical findings confirm that the Blockchain–AI framework provides a secure, transparent, and smart forensic environment, capable of revolutionizing judicial evidence handling and enhancing institutional trust via automated, data-driven processes.

Ping Han

The rapid digitization of commercial, governmental, and legal transactions has created an urgent need for efficient, secure, and transparent dispute resolution mechanisms. Traditional arbitration systems often fall short when handling the complexity and volume of digital evidence, smart contracts, and cross-border interactions. This study proposes a novel AI-powered digital arbitration framework that integrates smart contracts, blockchain-based evidence authentication, and explainable artificial intelligence (AI) to automate and modernize the arbitration process. The framework comprises three core layers: (i) a smart contract-based agreement layer that encodes legal terms and self-executing arbitration clauses; (ii) a blockchain-based evidence management layer that ensures the integrity, authenticity, and traceability of submitted evidence; and (iii) an AI-based arbitration engine that classifies, interprets, and evaluates evidence using transformer and LSTM models, supported by SHAP and LIME for interpretability. A controlled experimental setup was implemented using Ethereum and Hyperledger Fabric testnets, with AI models trained on 1,200 annotated arbitration cases. Results demonstrate a 99.5% reduction in arbitration time, a 92.4% agreement rate between AI and expert rulings, and a 99% accuracy in tampering detection. Furthermore, 87.3% of AI-generated decisions were rated as interpretable and acceptable by legal experts. These findings confirm the system's ability to deliver fast, accurate, and explainable arbitration decisions while complying with legal standards. This research contributes a foundational blueprint for deploying autonomous arbitration systems in digital governance, offering scalable solutions for future applications in smart contracts, e-commerce disputes, and algorithmic legal infrastructure.

А. Г. Волеводз, M. M. Dolgieva

In this article, we carry out a comprehensive comparative legal analysis of the criminal policy in the field of cryptocurrency confiscation in Russia, the European Union, and the United States. The relevance of this research is determined by the rapid growth of crimes involving crypto assets (money laundering, cybercrimes, and drug trafficking) and the lack of effective mechanisms for their final confiscation and implementation in Russia, which undermines the efforts of law enforcement agencies. We aim to identify effective models of cryptocurrency confiscation based on a comparative analysis of legislation and practice in leading jurisdictions and, on this basis, to develop recommendations for improving the Russian legal framework. The methodology includes a comparative legal analysis of regulatory acts (Russian Criminal Procedure Code, EU Directive 2014/42/EU, US Code), a formal legal method, an analysis of judicial practice (Russia, USA), and doctrinal sources. The key findings can be summarized as follows: (1) the USA enjoys the most advanced system, where the U.S. Marshals Service (USMS) actively uses private exchanges to convert confiscated assets; (2) the EU has established a strong legal framework (5/6AMLD, Directive 2014/42/EU); however, implementation practices here vary among member states, combining government-owned storage and outsourced sales through licensed platforms; (3) in the Russian Federation, despite the practice of seizure and arrest of crypto assets and legislative initiatives, the legal mechanism for their confiscation and sale is lacking, making court decisions unenforceable. In order to overcome this gap in Russia, it is necessary to urgently legislate cryptocurrency as property for the purposes of confiscation in the Criminal Procedure Code of the Russian Federation, grant the Federal Service for Judicial Enforcement of the Russian Federation the authority to sell through licensed platforms, as well as to develop expert potential. Our study extends the current knowledge by detailing the technological aspects of confiscation in the EU and the USA and proposes specific ways to modernize the criminal policy of the Russian Federation.

Amy Thomas, Maria-Jose Schmidt-Kessen, Simon Karlin

This chapter explores the role of intellectual property (IP) in the commercialisation and regulation of sports and eSports, focussing on copyright, trade marks, and image rights. It outlines how these rights enable key stakeholders - such as sports organisers, players and fans - to assert control over various aspects of sporting content and performances. Though comparative analysis of legal frameworks in Germany, the EU, and the UK, the chapter highlights significant jurisdictional differences in the protection and interpretation of these rights, particularly in relation to the use of player likenesses and ownership of performance outputs. The chapter also investigates how new technologies, including generative artificial intelligence (AI) and Non-Fungible Token (NFTs), might complicate rights-based relationships in both fields. A central theme is the imbalance of rights and bargaining power among stakeholders, especially players, whose creative contributions are often excluded from IP protection. In doing so, the chapter raises normative questions and critical reflections on fairness, enforcement, and contractual practices in the regulation of sports and eSports content.

O.O.O. Law firm, Upper Marlboro, USA, Oluwafunmibi Grace Ajakaye, Adeyinka Lawal, Independent Researcher, Texas, USA;

The emergence of blockchain technology and non-fungible tokens (NFTs) has fundamentally transformed the digital landscape, creating unprecedented challenges for intellectual property protection and copyright enforcement across transatlantic jurisdictions. This comprehensive study examines the evolving regulatory frameworks governing digital assets, blockchain-based intellectual property rights, and copyright infringement in the context of NFTs within both European Union and United States legal systems. The research investigates how traditional intellectual property laws are being adapted to address the unique characteristics of blockchain technology, including immutability, decentralization, and cross-border transactions that often transcend conventional jurisdictional boundaries. The study employs a comparative legal analysis methodology, examining recent legislative developments, judicial precedents, and regulatory guidance from key transatlantic jurisdictions including the United States, United Kingdom, Germany, France, and the European Union as a collective entity. Through systematic analysis of case law, regulatory frameworks, and emerging legal doctrines, this research identifies critical gaps in current legal protections and proposes innovative solutions for harmonizing intellectual property enforcement in the digital age. The analysis reveals significant disparities between European and American approaches to blockchain governance, with European jurisdictions typically favoring more prescriptive regulatory frameworks while American systems rely heavily on existing intellectual property doctrines adapted for digital contexts.

Zainab Johar

This Research paper attempts to examine and analyse the legal nature and law which govern virtual property, covering the concept of ownership, transfer, and regulatory challenges within the metaverse. This Research paper aims to set-out the struggles of traditional legal framework to adapt to the new digital environment consisting of technologies such as blockchain, artificial intelligence (AI), augmented and virtual reality (AR/VR), 3D modelling, and edge computing converge to form the metaverse. The study explains blockchain technology, as it reinforces non-fungible tokens (NFTs) which is the key standard for virtual ownership. It also attempts to analyse how existing legal framework in India for property laws, such as the Transfer of Property Act 1882[1] and the Sale of Goods Act 1930[2], could bring virtual assets under its legal parameters. A comparative analysis of the UK, US, EU, and Indian legal frameworks shows how different legal approaches helps in classification of digital assets. The UK Law Commission’s recommendation demonstrates a progressive shift toward recognising virtual property rights by introducing a new category of “digital objects”.[3] The Research paper highlights the inadequacy of existing property laws for resolving the exclusive cross-jurisdictional and ownership challenges posed by digital environments, concluding that just providing conceptual foundation is not enough. It advocates for a harmonised global governance framework integrating statutory law, soft law principles like the UNIDROIT Principles of International Commercial Contracts[4], and platform-specific regulation to ensure certainty, accountability, and protection of digital ownership.