Blockchain Papers

Ermanno Francesco Sannini, Francesco Salzano, Simone Scalabrino, Rocco Oliveto · 7 authors

Smart Contracts are essential blockchain components, mainly written in Solidity. The high availability of public Solidity code leads to frequent reuse and high clone ratios. Since cloning can propagate vulnerabilities and flaws, effective detection is crucial. Although existing techniques work well in detecting syntactic clones, the identification of semantic clones is an open problem. To address this challenge, in this paper, we present and empirically assess a scalable methodology, based on analyzing code and comments, to spot semantically equivalent Solidity functions. We first collected an up-to-date dataset of about 300,000 Ethereum smart contracts, 82.07% of which are compliant with modern Solidity version 0.8. Manual validation of a statistically significant sample comprising 1,155 function pairs confirms the effectiveness of our solution, achieving an overall precision of 59% (rising to 84% for homonymous functions) and a recall of 97%. Besides, we explore the structural differences occurring on semantically equivalent Solidity functions, demonstrating that they often represent design alternatives focused on security choices, modularization, and gas optimization. Finally, we investigate the use of Large Language Models (LLMs) as documentation engines in scenarios where code comments are poor or absent. Our results show that LLM-generated summaries, combined with sentence transformers like BERT, can bridge the documentation gap, enabling the identification of semantic clones in uncommented code with 75% precision. This work establishes a modern benchmark for Solidity clone detection and provides a foundation for the automated discovery of secure and efficient code alternatives.

Masato Kamba, Hirotake Murakami, Akiyoshi Sannai

Code-driven auditing fails when correctness depends on what the specification requires rather than how the code is written. Production blockchain networks expose this directly: byzantine consensus runs many independent clients of a shared specification, so a specification-divergence defect in one client can fork the network or halt finality. Existing tools reason one repository at a time, with no shared baseline held constant across implementations. We present SPECA, an LLM-driven audit framework that derives explicit, categorized security properties (invariants, pre/postconditions, trust assumptions) from natural-language specifications and reuses them across implementations. SPECA enables controlled cross-implementation comparison, detections grounded in specification invariants no code pattern encodes, and false positives traceable to a specific pipeline phase rather than opaque model errors. On the Sherlock Ethereum Fusaka Audit Contest (10 targets, 366 submissions), SPECA recovers all 15 in-scope H/M/L vulnerabilities expert-augmented (8/15 automated-only) and surfaces 4 fix-confirmed bugs, including a cryptographic-invariant violation missed by every adjudicated finding. On the RepoAudit C/C++ benchmark, SPECA reaches 88.9% precision at 100% recall (F1=0.94) and surfaces 12 author-validated bugs beyond ground truth, two externally validated. SPECA also flags 5 of RepoAudit's 40 published bugs as defensive-coding fixes with no reachable exploit path. False positives trace to three pipeline-pinned root causes; a multi-model study identifies property-generation quality as the binding constraint. End-to-end cost is ~$30 per H/M/L bug (~42 min wall-clock under parallel execution).

Locke Dauch (David Humble)

This paper presents a critical interpretation of modern monetary systems, arguing that centralized banking structures and debt-based finance concentrate economic power through mechanisms of money creation, interest, and inflation.It traces the historical evolution of money from commodity exchange and gold-backed systems to contemporary fiat currency regimes, emphasizing the role of fractional reserve banking and central bank monetary policy.The framework examines the creation of the U.S. Federal Reserve and the concentration of financial influence among banking and political elites, interpreting these developments as components of a broader “extraction architecture” embedded within global finance.It analyzes inflation, debt issuance, and wage dependency as systemic mechanisms that transfer value through interest-bearing monetary systems, while also discussing alternative economic models such as local currencies, cooperative economies, and decentralized finance.Positioned as a political economy critique and systems-level analysis, the work frames modern debt structures as socially constructed and institutionally reinforced systems of dependency, advocating documentation, decentralization, and reduced financial dependence as pathways toward greater sovereignty and resilience.

Aishwary singh

We describe a protocol that produces byte-identical outputs from frontier-scale language model inferenceand binds each output to a portable, offline-verifiable signed receipt. The construction has three parts.First, an inference substrate that runs models up to seventy-two billion dense parameters and forty-sevenbillion mixture-of-experts active parameters on NVIDIA H100, with cross-vendor extension to AMDInstinct MI300X. Output hashes match byte-for-byte across fresh process launches in every configurationmeasured; at single-GPU bf16 with eager attention the AMD and NVIDIA hashes are themselves byte-identical, including over fifty-one tokens of compounding frontier-scale generation, and at two-GPUtensor-parallel they differ as predicted by the underlying NCCL-ring versus RCCL-fabric all-reducetopology. Both are individually deterministic. Second, a canonical CBOR receipt schema with an Ed25519signature over a domain-separated message, implemented in Go, Python, and Rust, with cross-languagebyte-identity verified end-to-end and AMD-produced receipts verifying byte-for-byte through a Rustverifier built on x86 NVIDIA hardware. Third, a probabilistic spot-check verifier that re-executes asmall sample of receipts and rejects on mismatch; we prove a soundness lemma of the form 1−(1−f )kand validate it empirically across seventy adversary-verifier configurations with seven hundred thousandMonte Carlo trials. Verification costs about eighty microseconds per receipt on a single core. Eleventhousand sequential warm-model inferences ran without a single byte-identity failure. The contribution isthe construction itself: a primitive that gives issuer-independent fabrication soundness for AI inference atproduction cost, without a hardware-vendor dependency and without zero-knowledge proofs.

Monica T. Whitty, Amin Sakzad

No abstract is available for this record.

Ntebogang Dinah Moroke, Lebotsa Daniel Metsileng

The distributional specification in Markov-switching GARCH models has historically been driven by empirical convention rather than statistical theory. This paper derives the two-regime MS-GARCH specification from the Maximum Entropy Principle, providing an information-theoretic motivation for Student-t regime-conditional innovations in cryptocurrency volatility modelling. The framework is applied to five major cryptocurrencies, Bitcoin, Ethereum, Ripple, Litecoin, and Bitcoin Cash, over the period January 2017 to March 2026, comprising 15,834 daily observations spanning six complete market cycles. Three principal findings emerge. First, a Calm-Phase Fragility pattern is identified: four of five assets exhibit calm-regime half-lives below one trading day (0.48 to 1.16 days), with turbulence the dominant long-run state (stationary turbulent probability in [0.451, 0.771] across all assets), establishing turbulence rather than calm as the structural baseline of the cryptocurrency ecosystem. Second, the Maximum Entropy derivation yields endogenous Student-t degrees of freedom, with heavy-tailed turbulent innovations (degrees of freedom approximately 4.5) confirmed across all assets, validating the MaxEnt constraint framework empirically. Third, near-unity turbulent GARCH persistence drives MS-GARCH point forecasts toward the persistence ceiling, consistent with an information-theoretic bound on predictability when the calm half-life collapses below one trading day; HAR-RV achieves the lowest QLIKE loss for three of five assets under these near-critical conditions. Cross-asset consistency is confirmed across seven statistical indicators including Hill tail exponents in [2.31, 3.26], Hurst exponents in [0.543, 0.577], and Wald tests rejecting parameter homogeneity at p < 0.001 for all assets. The framework is formalised as a deployable expert system for real-time regime monitoring and risk management.

Siddharth Narela, Ranjana Sharma

This research paper explores the critical challenge of verifiable execution integrity in modern cloud and serverless computing platforms. While services like Amazon Web Services Lambda and Google Cloud Functions provide scalable and efficient execution environments, they operate as opaque systems where users cannot verify whether their code is executed correctly or securely. The paper identifies a fundamental trust gap in current cloud architectures and presents a comprehensive threat model covering risks such as hypervisor compromise, malicious insiders, supply chain attacks, and output manipulation. It highlights how existing security certifications and auditing mechanisms fail to provide cryptographic guarantees of correctness. To address this problem, the paper proposes a novel framework called the CodeNet Integrity Layer (CIL). This system integrates multiple advanced technologies, including Trusted Execution Environments (TEEs), Zero-Knowledge Proofs (ZKPs), and blockchain-based audit mechanisms, to create a decentralized and trustless verification model. The framework ensures that computation outputs are provably linked to the correct code and inputs without relying on blind trust in the provider. The proposed solution is evaluated through experimental implementation, demonstrating that strong execution integrity can be achieved with minimal performance overhead, making it practical for real-world deployment. The research contributes to the future of secure, transparent, and trustless cloud computing, particularly for sensitive applications in finance, healthcare, and critical infrastructure.

Jordana Siteneski do Amaral, Salete Oro Boff

Este trabalho propõe-se a discutir a proteção dos Direitos Autorais em uma nova forma de adquirir e investir em arte digital: a criptoarte. Utilizando-se do método hipotético-dedutivo, o problema de pesquisa ao qual o presente trabalho pretende responder é se a criptoarte encontra-se dentro do campo de incidência do Direito Autoral. Parte-se da hipótese inicial afirmativa, de que a criptoarte é passível de proteção pelo Direito Autoral, estando portando, dentro do campo de incidência do Direito Autoral, dado que a regra geral é o reconhecimento da paternidade da obra e consequente remuneração do autor. Observou-se que a arte digital em si não é novidade, mas a possibilidade de comercialização e comprovação de autenticidade e unicidade ocorre graças às tecnologias da criptografia e da blockchain e aos non-fungible tokens (NFTs) que ficam permanentemente vinculados à obra. Considerando que a criptoarte trata-se de uma obra com finalidades estéticas, e não uma obra utilitária, que possui um autor pessoa física, e que a regra é a proteção da obra e consequente remuneração dos autores e/ou titulares, tais obras encontram proteção no instituto do Direito Autoral. Não obstante, considerando que a lei de Direitos Autorais (Lei nº 9.610/98) possui três campos distintos, de incidência, de isenção e de imunidade, verifica-se por fim, corroborada a hipótese inicial, de que a criptoarte perfaz os requisitos necessários para estar no campo da incidência.

Yu-Chao Huang, Zhen Tan, Mohan Zhang, Pingzhi Li · 6 authors

Large Reasoning Models (LRMs) and Multi-Agent Systems (MAS) in high-stakes domains demand reliable verification, yet centralized approaches suffer four limitations: (1) Robustness, with single points of failure vulnerable to attacks and bias; (2) Scalability, as reasoning complexity creates bottlenecks; (3) Opacity, as hidden auditing erodes trust; and (4) Privacy, as exposed reasoning traces risk model theft. We introduce TRUST (Transparent, Robust, and Unified Services for Trustworthy AI), a decentralized framework with three innovations: (i) Hierarchical Directed Acyclic Graphs (HDAGs) that decompose Chain-of-Thought reasoning into five abstraction levels for parallel distributed auditing; (ii) the DAAN protocol, which projects multi-agent interactions into Causal Interaction Graphs (CIGs) for deterministic root-cause attribution; and (iii) a multi-tier consensus mechanism among computational checkers, LLM evaluators, and human experts with stake-weighted voting that guarantees correctness under 30% adversarial participation. We prove a Safety-Profitability Theorem ensuring honest auditors profit while malicious actors incur losses. All decisions are recorded on-chain, while privacy-by-design segmentation prevents reconstruction of proprietary logic. Across multiple LLMs and benchmarks, TRUST attains 72.4% accuracy (4-18% above baselines) and remains resilient against 20% corruption. DAAN reaches 70% root-cause attribution (vs. 54-63% for standard methods) with 60% token savings. Human studies validate the design (F1 = 0.89, Brier = 0.074). The framework supports (A1) decentralized auditing, (A2) tamper-proof leaderboards, (A3) trustless data annotation, and (A4) governed autonomous agents, pioneering decentralized AI auditing for safe, accountable deployment of reasoning-capable systems.

Miguel Isabel, Enric Rodríguez-Carbonell, Clara Rodríguez-Núñez, Albert Rubio

Zero-knowledge proofs (ZKPs) are an emerging technology that has become the solution to efficiently provide security and privacy along with the transparency requirement of blockchains. ZKPs are usually expressed by means of arithmetic circuits and, more generally, systems of polynomial equations in a large prime field (commonly ranging from 64-bit to 256-bit values). An increasing interest to apply formal verification techniques to ensure soundness and completeness properties of ZKP protocols has shown the need of developing powerful SMT solvers able to handle such constraint systems. In this paper we consider the problem of deciding the satisfiability of existentially quantified first-order formulas defined over polynomial equations on a prime field. We present a new DPLL($T$)-based approach in which the theory solver orchestrates several modules with different trade-offs between completeness and efficiency. We have implemented the proposed techniques in a prototype that already shows better results than existing state-of-the-art tools on both benchmarks from the domain of ZKP compiler correctness and new benchmarks coming from the verification of arithmetic circuits for ZKPs. \keywords{SMT \and Finite field \and Polynomials \and Zero-Knowledge Proofs.

Ignacio Peyrano

Enterprise software engineering is shifting away from deterministic CRUD/REST architectures toward AI-native systems where large language models act as cognitive orchestrators. This transition introduces a critical security tension: probabilistic LLMs weaken classical mechanisms for validation, access control, and formal testing. This paper proposes the design, formal validation, and empirical evaluation of a Semantic Gateway governed by the Model Context Protocol (MCP). The gateway reframes the enterprise API as a semantic surface where tools are dynamically discovered, authorized, and executed based on intent and policy enforcement. The central contribution rests on a paradigm shift: autonomous agents must not be validated as traditional software nor as simple API consumers, but as stochastic state-transition systems whose behavior must be abstracted, fuzzed, and audited through enabled-tool graphs. The architecture introduces a three-layer Zero-Trust security model comprising a pre-inference Semantic Firewall, deterministic Tool-Level RBAC, and out-of-band Cryptographic Human-in-the-Loop approval. Enabledness-Preserving Abstractions (EPAs) and greybox semantic fuzzing--originally developed for blockchain smart contract verification--are adapted to audit agent behavior in enterprise environments. Results demonstrate an 84.2% reduction in incidental code. Across 500,000 multi-turn fuzzing sequences, the methodology achieved a 100% discovery rate of hidden unauthorized state transitions, proving that dynamic formal verification is strictly necessary for secure agentic deployment.

Catharina Araújo Lisbôa

Considerando a crescente expansão do mercado de criptoativos e a recorrente associação do bitcoin a práticas de ocultação patrimonial, torna-se relevante examinar sua utilização no delito de lavagem de dinheiro, especialmente diante dos riscos de responsabilização penal indevida de agentes que atuam licitamente nesse setor. Objetiva-se analisar a utilização do bitcoin no delito de lavagem de dinheiro, a partir do exame de sua definição, de suas formas de circulação e de sua possível inserção em dinâmicas de ocultação e dissimulação de valores de origem ilícita. Para tanto, proceder-se-á a uma pesquisa de abordagem qualitativa, com emprego do método jurídico-dogmático e da linha crítico-metodológica, mediante revisão bibliográfica e documental da legislação e da doutrina especializada. Desse modo, observa-se que o bitcoin, embora apresente características que podem favorecer sua utilização em esquemas de lavagem de capitais, como pseudoanonimato, descentralização, mobilidade transnacional e inexistência física, não constitui, por si só, instrumento ilícito. O que permite concluir que sua relevância penal depende da demonstração concreta de vínculo com infração penal antecedente e da prática de atos voltados à ocultação ou dissimulação da origem ilícita dos valores.

Ray Iskander, Khaled Kirah

This is Paper 6 of a series of formally-verified analyses of masked NTT hardware for post-quantum cryptography; Paper 1 [1] established structural dependency analysis of the QANARY platform, and Paper 2 [2] quantified security margins under partial NTT masking. Boolean masking composition is well-understood through NI, SNI, and PINI. Arithmetic masking over $\mathbb{Z}_q$ for prime $q$, the foundation of NTT-based post-quantum cryptography, has lacked an analogous theory. We prove, to our knowledge, the first machine-checked composition theorems for arithmetic masking over prime fields. Our key insight is the renewal argument: when a fresh random mask is applied between two pipeline stages, the intermediate wire becomes perfectly uniform regardless of Stage 1's security parameter. For two PF-PINI gadgets with parameters $k_1$ and $k_2$, the composed two-stage pipeline with fresh masking satisfies PF-PINI($k_2$), Stage 1's multiplicity is completely erased from the composed output. Without fresh masking, intermediate wires have multiplicity up to $k_1$, creating a necessary condition for differential power analysis. We formalize both theorems in Lean 4 with 18 machine-checked proofs and zero sorry stubs. We formally bridge the algebraic and hardware-faithful arithmetic models of Barrett reduction, and instantiate the theorems to formally diagnose Microsoft's Adams Bridge PQC accelerator: its absence of fresh inter-stage masking leaves Barrett output wires non-uniform under the first-order probing model, the same architectural flaw that two independent empirical analyses [3, 4] and our own prior structural analysis [1] identified. Computational evidence further suggests the 1-Bit Barrier is universal across Barrett and Montgomery reductions.

Radhika A Jujare

Interoperability of patient files between hospitals continues to present significant obstacles. Health systems frequently utilize central EHR systems that could suffer malfunctions, data breaches, and unauthorized access by third parties. Not only does this jeopardize patient confidentiality, but it also hinders the efficient operations of hospital processes.Blockchain technology is viewed as a prospective remedy for the issue. Blockchain keeps its data differently, allowing users to store data securely and make changes difficult. In this study, we analyze research works published between 2016 and 2023 regarding blockchain-based hospital-to-hospital data exchange.The methodologies differ widely: there are cases where researchers use smart contracts in Ethereum, build a system on Hyperledger Fabric, and deploy IPFS. Moreover, certain studies incorporate encryption methods, machine learning algorithms, and more. In summary, the results show that blockchain allows for improved data protection and transparency while giving patients more control over their personal information. Still, some issues persist, such as scalability, expenses, integration with existing infrastructure, and adherence to GDPR and HIPAA requirements. For future work, more improvements are necessary. For instance, zero-knowledge proofs, cybersecurity measures for new technologies, and using artificial intelligence to audit and validate smart contracts may be promising solutions.

Jhitsayarat Siripai, Chris Haywood

This article explores how Thai men construct and perform masculine identities through cryptocurrency trading, using the concept of crypto-masculinity to examine how digital finance becomes a site for gendered self-making. While existing scholarship on masculinity in financial contexts often centers on transnational business masculinities in Western corporate settings, little attention has been paid to how masculinity is enacted in decentralized, digital financial spaces, particularly in non-Western contexts. Addressing this gap, this article draws upon in-depth interviews with 21 male traders in Thailand to analyze how masculinity is shaped by the internal instability of masculinity and local cultural norms. This study identifies three key themes through which Thai men's subjectivity is negotiated: valorizing failure, homosociality, and ‘becoming a good Thai man.’ As a result, this article challenges assumptions about the naturalized links between men and finance, suggesting the need for further research on how exclusions within digital finances are taking place to better support equality on crypto platforms.

Bowen Cai, Weiheng Bai, Youshui Lu, Haoran Xu · 7 authors

As blockchain ecosystems grow, financially motivated attackers increasingly exploit decentralized finance (DeFi) protocols, causing frequent and severe losses. Unlike conventional cyberattacks, DeFi exploits propagate rapidly due to the transparent and composable nature of smart contracts. We identify a critical pattern, Imitative Attack Cascade: an initial successful exploit is quickly followed by mimicking transactions that reuse attack logic with minor modifications or parameter changes. Our empirical analysis shows that over 69% of DeFi attacks exhibit strong behavioral similarity to earlier incidents, often within hours or days of the initial attack. This exposes a fundamental limitation in current reactive detection. Initial attacks are typically flagged via heuristic alerts (Tornado Cash traces, anomalous nonce usage, exploiter labels), but turning these signals into detection rules requires manual validation and handcrafted trace analysis -- a labor-intensive, slow process that leaves follow-up attacks to spread. Our goal is to ensure that once an attack has been observed, even a single instance, it can be rapidly abstracted into an actionable, generalizable detection rule. We decompose the problem into two challenges: (I) abstracting the semantics of diverse, obscure function signatures, and (II) matching transaction logic in noisy, evasive traces. We leverage two insights: (i) the open-source nature of most DeFi protocols enables high-fidelity semantic classification of function signatures; (ii) contract labels isolate essential logic by filtering irrelevant calls and classifying attack intent. Building on these, we develop GenDetect, which achieves ACC 98%, FPR 1%, FNR 3% and discovers 56 previously unrevealed attacks from the past three years. Source code and dataset: https://github.com/NobodyIsAnonymous/GenDetect_ICSE2026

Mikhail Perepelitsa

This paper introduces a heterogeneous macroeconomic model of a Proof-of-Stake (PoS) network to analyze the long-term centralizing effects of external traditional finance (TradFi) yields. We model a continuum of rational actors divided into two distinct classes: investors, who optimize portfolios between staking and external variance-dominated investments, and consumers, who balance staking yields against the transactional utility of holding liquid assets. By employing a quasi-linear utility function to model consumer behavior, we derive a cubic polynomial that strictly defines the unique macroeconomic equilibrium of the coupled network. The model demonstrates that, at scale, external macroeconomic factors force the complete institutional capture of the PoS consensus layer. Because investors have access to external risk premiums, their wealth compounds exponentially, leading to massive capital inflows that crush the protocol's internal staking yield to effectively zero. We show that as the yield is crushed, consumer wealth becomes strictly upper-bounded. Ultimately, consumers are forced to cease staking entirely and hold all remaining wealth in liquid form to satisfy their transactional constraints.

Razwan Ahmed Tanvir, Greg Speegle

Collaborative blockchain ecosystems allow diverse groups to cooperate on tasks while providing properties such as decentralization and transaction security. We provide a model that uses a repository blockchain to manage hard forks within a collaborative system such that a single process (assuming that it has knowledge of the requirements of each fork) can access all of the blocks within the system. The repository blockchain replaces the need for Inter Blockchain Communication (IBC) within the ecosystem by navigating the networks. The resulting construction resembles a tree instead of a chain. A proof-of-concept implementation performs a depth-first search on the new structure.

Lidia Losavio, Luca Persia, Madan Sathe, Dimosthenis Pasadakis

Technological advancements in cryptocurrency markets have increased accessibility for investors, but concurrently exposed them to the risks of market manipulations. Existing fraud detection mechanisms typically rely on machine learning methods that treat each financial asset (i.e., token) and its related transactions independently. However, market manipulation strategies are rarely isolated events, but are rather characterized by coordination, repetition, and frequent transfers among related assets. This suggests that relational structure constitutes an integral component of the signal and can be effectively represented through graphical means. In this paper, we propose three graph construction methods that rely on aggregated hourly market data. The proposed graphs are processed by a unified spatio-temporal Graph Neural Network (GNN) architecture that combines attention-based spatial aggregation with temporal Transformer encoding. We evaluate our methodology on a real-world dataset comprised of pump-and-dump schemes in cryptocurrency markets, spanning a period of over three years. Our comparative results showcase that our graph-based models achieve significant improvements over standard machine learning baselines in detecting anomalous events. Our work highlights that learned market connectivity provides substantial gains for detecting coordinated market manipulation schemes.

Fiza Naseer, Javed Ali Khan, Muhammad Yaqoob, Alexios Mylonas · 5 authors

Context: Software vulnerabilities pose significant security threats to software systems, especially as software is increasingly used across many areas of daily life, including health, government, and finance. Recently, transformer-based models have demonstrated promising results in automatic software vulnerability identification due to their robust contextual modelling and representation learning capabilities. Objectives: While numerous systematic literature reviews (SLRs) have examined machine learning and deep learning methods for identifying vulnerabilities, a more transformer-centric analysis remains to be explored. This SLR critically analysed 80 studies published between 2021 and 2025 that utilised transformer models to identify software vulnerabilities. Methods: Using Kitchenhams SLR guidelines, we methodically evaluate current research from various perspectives, encompassing study trends, datasets and sources, programming languages, transformer frameworks, detection detail levels, assessment metrics, reference models, types of vulnerabilities, and experimental configurations. Results: We classify transformer models into encoder, decoder, and combined architectures and analyse both pre-trained and fine-tuned versions utilized on source code, logs, and smart contracts. The results emphasise prevailing research trends, frequently utilised benchmarks, and main baselines. It also uncovers crucial technical issues like data imbalance, interpretability, scalability, and generalization across programming languages. Conclusion: By integrating current evidence and recognising unaddressed research areas, this SLR provides a consolidated resource for researchers and professionals seeking to develop more reliable, precise, and interpretable transformer-based vulnerability identification systems.

Zijun Feng, Yuming Feng, Yu Wang, Weizhe Zhang · 7 authors

Cross-chain bridges, the critical infrastructure of the multi-chain ecosystem, have become a primary target for attackers, resulting in over $2.8 billion in losses due to subtle implementation flaws. Existing defenses, such as bytecode-level static analysis, are ill-equipped to handle the semantic complexity of cross-chain interactions, while LLM-based approaches, which can understand source code, struggle with hallucinatory reasoning over complex, multi-contract dependencies. In this paper, we propose GoAT-X, a framework that shifts automated cross-chain smart contract codebases auditing from heuristic pattern matching toward systematic first-principles verification. GoAT-X structures the audit process as a Graph of Auditing Thoughts, explicitly mirroring how human experts decompose, reason about, and validate security logic. By anchoring LLM reasoning in statically extracted data flows and explicitly linking abstract security properties to concrete code implementations, the framework constrains semantic reasoning within well-defined structural and state boundaries. Within this constrained space, GoAT-X treats missing constraints and adversarial bypass paths in cross-chain logic as first-class vulnerability targets and dynamically explores reasoning paths to identify exploitable semantic gaps. We evaluate GoAT-X on a comprehensive benchmark covering all known cross-chain token transaction attacks. GoAT-X achieves 92% recall on fine-grained audit points and 95% coverage of vulnerable projects, while identifying 117 confirmed risks in the wild with low operational cost, establishing a new standard for scalable, logic-driven cross-chain security.

Malcolm Kinney

No abstract is available for this record.

Kazunori Ohumi

This paper argues that the contemporary debate on genetics and equality is fundamentally misframed. The problem does not lie in how genomic information should be regulated, but in the deeper ontological assumption that human value is reducible to structural output (S). By introducing Universal Phase Crystallization Theory (UPCT), the paper demonstrates that existence is not structure, but generative resonance (E=ΦR). This shift reveals that meritocracy, equality theory, and even diversity discourse remain trapped within an S-centric evaluative paradigm. As advances in AI commoditize structural ability, and genetics exposes its arbitrariness, civilization faces an irreversible bifurcation: persist in S-based optimization and collapse, or transition toward a generative system grounded in relational participation. The paper proposes a new framework—Generative Equality—where ability is redefined as ΦR, and social organization is governed not by privilege, but by proportional responsibility. Highlights Reframes the genetics–equality debate as an ontological, not policy, problem Demonstrates the structural self-collapse of S-centric meritocracy Introduces Generative Equality as a post-distributive model of justice Formalizes ethics as a dynamical condition: d(ΦR)/dt≥0 Positions AI as the historical trigger of a civilizational phase transition Core Arguments and Contributions 1. Reframing the Problem This paper fundamentally reframes the genetics–equality debate. Rather than treating genetic differences as a policy issue of redistribution or regulation, it identifies the deeper source of conflict: the assumption that human ability and value can be reduced to structural output (S). This shift moves the discussion from bioethics to ontology. 2. Structural Collapse of S-Centric Civilization The paper demonstrates that S-centric systems contain an inherent contradiction. By optimizing structure, they eliminate the generative and relational conditions (ΦR) that sustain them. This leads to “ontological cooling,” where systems lose adaptive capacity and collapse. Meritocracy is thus shown to be structurally unstable. 3. Ontological Transformation via UPCT Using UPCT, the paper redefines existence as E=Φ×R, shifting the basis of human value from output to generative participation. This provides a unified framework linking biology, ethics, and social systems within a dynamic model of existence. 4.Redefinition of Ethics and Equality Ethics is reformulated as a dynamical condition (d(ΦR)/dt≥0), and equality is reconceptualized as “Generative Equality,” consisting of participation in relational processes rather than distribution of resources. This dissolves the zero-sum logic of traditional equality theories. 5. Civilizational Implication The paper argues that advances in AI and genetics are not merely technological developments but catalysts of an irreversible civilizational bifurcation. Humanity must transition from a Machine OS (optimization) to a Life OS (generation), redefining ability as responsibility and existence as continuous relational renewal. Author’s Related Works UPCT Foundational Theoretical Works Ohumi, K. (2026). Universal Phase Crystallization Theory (UPCT): A Generative Relational Ontology of Existence, Stability, and Emergence.https://doi.org/10.5281/zenodo.19065461 Ohumi, K. (2026). Universal Phase Crystallization Theory (UPCT): A Unified Generative Theory of Time, Life, and Civilization.https://doi.org/10.5281/zenodo.18653237 Ohumi, K. (2026). Universal Phase Crystallization Theory (UPCT) Phase I: A Unified Resolution of Quantum Paradoxes via Temporal Sampling.https://doi.org/10.5281/zenodo.18230537 Ohumi, K. (2026). Universal Phase Crystallization Theory (UPCT) Phase II: A Phase Transition Law for Generative Systems under Measurement Optimization.https://doi.org/10.5281/zenodo.18408708 Ohumi, K. (2026). Universal Phase-Crystallization Theory (UPCT) I: Generative Time and Relational Space.https://doi.org/10.5281/zenodo.18979001 Ohumi, K. (2026). From Machine Civilization to Generative Civilization: Universal Phase-Crystallization Theory and the Generative Structure of Reality.https://doi.org/10.5281/zenodo.18935934 Ohumi, K. (2026). UPCT Existential Core: A Generative Ontology for Post-Functional Civilization. https://doi.org/10.5281/zenodo.19146516 Ohumi, K. (2026). A Generative-Relational Ontology of Sustained Existence: UPCT. https://doi.org/10.5281/zenodo.19469785 UPCT Ontology and Civilizational Philosophy Ohumi, K. (2026). Existence as Generativity: Desire, Structure, and the Dynamics of Civilizational Transition in Universal Phase Crystallization Theory. https://doi.org/10.5281/zenodo.19198157 Ohumi, K. (2026). From Having to Being: Toward a Generativity-Centered Ontology in the Age of Artificial Intelligence.https://doi.org/10.5281/zenodo.18829129 Ohumi, K. (2026). The Declaration of Life-OS: An Ontological Turn Toward a Generative Civilizational Spiral.https://doi.org/10.5281/zenodo.18645582 Ohumi, K. (2026). From Proof to Resonance: A Φ-Ontology of Existence, Labor, Education, and Economic Life.https://doi.org/10.5281/zenodo.18515955 Ohumi, K. (2026). Returning to the Source of Philosophy: Affirmation of Life as the Life-OS and a Radical Point of Departure.https://doi.org/10.5281/zenodo.18529485 Ohumi, K. (2026). Dialectics as a Relational Logic of Life: From Linear Ascent to Spiral Circulation.https://doi.org/10.5281/zenodo.18522371 Ohumi, K. (2026). Does Color Exist? Overcoming the Ontological-Epistemological Confusion Through Generative Phase Transition: An Application of Universal Phase Crystallization Theory (UPCT). https://doi.org/10.5281/zenodo.19105125 Ohumi, K. (2026). From Color to Sound: Human Cognitive Limits Between Ontology and epistemology and the Generative Resolution of UPCT. https://doi.org/10.5281/zenodo.19110346 Ohumi, K. (2026). Toward a Generative Theory of Human Motivation: Participation, Existence, and the Fundamental Drive. https://doi.org/10.5281/zenodo.19286911 Ohumi, K. (2026). What is Desire? The Transition from the "Machine OS" to the "Life OS" in the History of Human Thought. https://doi.org/10.5281/zenodo.19327281 Ohumi, K. (2026). The Ontology of Resonance Beyond Generative Supremacy: The First Principle of "Existence = Generation = Resonance" and the Mandalic Hierarchy of the Life OS. https://doi.org/10.5281/zenodo.19334259 Ohumi, K. (2026). Life as Generative Resonance: An Ontological Essay on Happiness, Wealth, and the Recovery of Human Generativity. https://doi.org/10.5281/zenodo.19394468 Ohumi, K. (2026). Co-Generative Intelligence: A Relational Framework for Human–AI Collaboration Beyond Optimization. https://doi.org/10.5281/zenodo.19659573 Ohumi, K. (2026). The Equation of Knowledge Dynamics: A Generative–Relational–Structural Field Theory of Intelligence and Civilization. https://doi.org/10.5281/zenodo.19707187 Ohumi, K. (2026). The Meta-principle of Generation and the End of Ideology: Dismantling Structural Illusions and Redefining the Ontology of Value via the Equation E = ΦR. https://doi.org/10.5281/zenodo.19724468 UPCT Science and Physics Foundations Ohumi, K. (2025). A Sampling-Theoretic Reinterpretation of Quantum Uncertainty and Wave Function Collapse.https://doi.org/10.5281/zenodo.18004579 Ohumi, K. (2025). Observation as Operational Crystallization: Resolving Quantum Paradoxes.https://doi.org/10.5281/zenodo.18220191 Ohumi, K. (2025). Dark Energy as a Diffusive Phase of a Relational Universe.https://doi.org/10.5281/zenodo.18081786 Ohumi, K. (2025). It from Wave: Phase Propagation as Physical Basis of Information.https://doi.org/10.5281/zenodo.18256968 Ohumi, K. (2025). Ontological Reconstruction of Quasi-Particles.https://doi.org/10.5281/zenodo.18140041 Ohumi, K. (2025). Envelopment over Unification: Recovering Einstein’s Dream.https://doi.org/10.5281/zenodo.18244683 Ohumi, K. (2026). The Ten Unresolved Problems of Modern Physics Reinterpreted Through UPCT Toward a Generative Ontology of Physical Reality. https://doi.org/10.5281/zenodo.19243422 Ohumi, K. (2026). The Generative Origin of Time A UPCT Resolution of the Problem of Time. https://doi.org/10.5281/zenodo.19360863 Ohumi, K. (2026). Generative Science Manifesto: From Structural Knowledge to Generative Participation Toward a Post-Publication Scientific Paradigm. https://doi.org/10.5281/zenodo.19379510 Ohumi, K. (2026). Generative Peer Review: From Structural Gatekeeping to Generative Participation in the AI Era. https://doi.org/10.5281/zenodo.19382292 Ohumi, K. (2026). The Collapse of the Structural Scaling Paradigm: AI Movement Analysis Failure and the Hard Problem of Consciousness through the UPCT Framework. https://doi.org/10.5281/zenodo.19754117 UPCT Economics, Governance, and Society Ohumi, K. (2026). Generative Resonance Management Theory: Organizational Collapse, Generative Renewal, and Structural Crystallization. https://doi.org/10.5281/zenodo.19603736 Ohumi, K. (2026). Foundational Principles of Resonance Economics.https://doi.org/10.5281/zenodo.18500861 Ohumi, K. (2025). The WGS Model: The Implementation of Generative Governance.https://doi.org/10.5281/zenodo.18308450 Ohumi, K. (2025). Resonant Management.https://doi.org/10.5281/zenodo.18162380 Ohumi, K. (2025). Resonant Politics.https://doi.org/10.5281/zenodo.18180888 Ohumi, K. (2025). The KPI Trap: Over-Optimization and Meaning Collapse.https://doi.org/10.5281/zenodo.18264106 UPCT Civilization and Crisis Analysis Ohumi, K. (2026). Civilization After the Loss of Foundations.https://doi.org/10.5281/zenodo.18722641 Ohumi, K. (2026). The Zeno Civilization: Financial Markets, Algorithmic Saturation, and the Φ–G–S Spiral of Value.https://doi.org/10.5281/zenodo.18862821 Ohumi, K. (2026). Population Decline as Ontological Consequence.https://doi.org/10.5281/zenodo.18801947 Ohumi, K. (2026). The Φ-Depletion Society.https://doi.org/10.5281/zenodo.1890077

Muhammad Umar Jabbar Jabbar

The Jabbar Adal Principle (JAP) is a theoretical framework in non-relativistic Hamiltonian mechanics that formally names, defines, and analyses the instantaneous ratio of kinetic to potential energy at every local subsystem of a closed physical system — a quantity unaddressed by the First Law, Second Law, or the Virial Theorem. This work introduces three new named physical quantities and one new named unit: Jabbar Asymmetry Parameter — A(i, t) = Ti(t) / |Vi(t)| [Jb] Virial Deviation Parameter — ΔA(i, t) = A(i, t) − Avir(i) [Jb] Adal Asymmetry Index — AAI(t) = (1/N) Σ |ΔA(i, t)| [Jb] The Jabbar unit [Jb] — a named dimensionless unit of virial deviation, analogous to the radian and the neper, named after the Jabbar family of Khanewal, Punjab, Pakistan — derived from Abdul Jabbar, daily-wage labourer, father of the author, whose sacrifices made this work possible. Two Proved Theorems Theorem 1 — The Jabbar Vitality Theorem:In any closed non-relativistic Hamiltonian system, physical processes are possible if and only if AAI(t) > 0 Jb. This is a necessary and sufficient biconditional, logically independent of the Second Law of Thermodynamics. Theorem R1 — The Oscillatory Modulation Theorem:For any closed non-relativistic Hamiltonian system of N ≥ 2 coupled harmonic oscillators with distinct normal-mode frequencies ω1 ≠ ω2: AAI(t) = AAI0 · e−γt · [1 + ε sin(ωbeat t + φ)] [Jb] where ωbeat = |ω2 − ω1| is derived entirely from the Hamiltonian eigenvalues — not fitted, not assumed. The heat equation cannot predict this modulation. Derivation Foundations The proof rests on four independently established and undisputed premises: Hamilton's canonical equations (Hamilton, 1835) Normal-mode decomposition (linear algebra) Product-to-sum trigonometric identity (pure mathematics) Virial theorem for V ∝ x² (Clausius, 1870) Numerical Verification System parameters: m1 = 1.0 kg, m2 = 2.0 kg, k1 = 4.0 N m−1, k2 = 6.0 N m−1, κ = 1.5 N m−1, γ = 0.02 s−1. Theoretical ωbeat = 0.646714 rad s−1 (from Hamiltonian eigenvalues) Fitted ωbeat = 0.646686 rad s−1 (from numerical simulation) Deviation: 0.0043% — 1 part in 23,000 RMSE improvement over heat equation: 37.54% Verified independently by Python (NumPy / DOP853 solver, rtol = 10−11) and PHP 8.3 (4th-order Runge–Kutta). Both agree to six significant figures. Supplementary code: JAP_calculations.php (included, CC BY 4.0). Domain of Validity All claims apply exclusively to closed physical systems governed by a non-relativistic Hamiltonian H = T + V. This explicitly excludes General Relativity, quantum field theory, and cosmological scales. The domain encompasses molecular vibrations, coupled mechanical resonators, acoustic lattices, optical traps, and any classical N-body system in the Newtonian limit. Priority and Novelty The following elements have no prior publication in the physics literature to the author's knowledge: The quantity A(i, t) = Ti/|Vi| as a named observable The Virial Deviation Parameter ΔA(i, t) The Adal Asymmetry Index AAI(t) The Jabbar unit [Jb] The Jabbar Vitality Theorem (biconditional) Theorem R1 (oscillatory modulation of AAI) Under CC BY 4.0, any use of these named quantities requires citation of this work. Open Problem — JAP-Entropy Conjecture In the zero-temperature limit (Tbath → 0), during monotonic relaxation, it is conjectured that: AAI(t) ∝ σep(t) / ⟨T(t)⟩ where σep is the entropy production rate. Proof or disproof of this conjecture is the highest-value open problem in the JAP framework. About the Author Muhammad Umar Jabbar (also: Umar Adl Jabbar) was born on 1 February 2008 in village 4/A.H, Khanewal, Punjab, Pakistan. He is 18 years old at the time of publication. His father, Abdul Jabbar, worked throughout his life as a daily-wage labourer and is now bedridden with heart disease. His mother works as a domestic worker earning Rs. 5,000 per month. He has four siblings — two brothers and two sisters — all in education. He could not afford medical college. He could not afford nursing school. He had no university, no laboratory, no supervisor, and no funding. He is believed to be the youngest independent theoretical physics researcher in Pakistan to formally propose and prove named theorems in non-relativistic Hamiltonian mechanics without any institutional support. The Jabbar unit [Jb] is named after his family — derived from his father Abdul Jabbar's name — so that the sacrifice of a labourer from a small Pakistani village is permanently recorded in the language of science. ORCID: 0009-0008-5968-0991Email: umarjaumofficial@gmail.comLicence: CC BY 4.0