In the digital era, personal data is continuously collected, processed, and shared by organizations across various sectors. Traditional consent management systems suffer from centralization, opacity, and insufficient user control, making it difficult for individuals to track and enforce their data-sharing preferences. This paper presents ConsentChain, a decentralized consent governance protocol built on the Polygon blockchain. The system leverages Ethereum-compatible smart contracts to implement purpose-bound, time-limited, and user-revocable consent records, backed by an immutable on-chain audit trail. The architecture employs two core Solidity smart contracts—ConsentManager and AccessController—supported by a React-based frontend and MetaMask wallet integration. Comprehensive end-to-end testing demonstrates 18 of 18 test cases passing, validating the correctness of consent lifecycle management, access validation, role-based access control, and event logging. ConsentChain demonstrates that blockchain technology can provide a transparent, tamper-proof, and user-sovereign alternative to conventional consent management systems, with clear pathways toward enterprise adoption, multi-chain deployment, and zero-knowledge privacy extensions. Index Terms—Blockchain, Consent Management, Smart Contracts, Data Privacy, GDPR, Decentralized Systems, Ethereum, Polygon, Access Control, Audit Trail.
Digital identity management is a cornerstone of effective e-governance, yet centralized identity systems face critical challenges including single points of failure, data breaches, and lack of citizen control over personal information. This paper proposes a blockchain-based Self-Sovereign Identity (SSI) framework for e-governance that enables citizens to own, control, and selectively disclose their identity credentials without relying on centralized authorities. Built on Hyperledger Fabric with W3C Decentralized Identifier (DID) standards and Verifiable Credentials, the framework incorporates zero-knowledge proofs (ZKPs) for privacy-preserving authentication and smart contracts for automated credential verification. Performance evaluation on a 4-organization, 16-peer Hyperledger Fabric network demonstrates a throughput of 4,800 transactions per second with an average identity verification latency of 85 ms, suitable for citizen-scale e-governance applications. Security analysis confirms resistance to identity theft, Sybil attacks, man-in-the-middle attacks, and credential forgery, achieving resistance scores above 94% across all evaluated attack vectors. The framework provides a practical pathway for governments to modernize identity infrastructure while preserving citizen privacy and data sovereignty.
In the context of rapid and widespread digitalization of society, active implementation of new innovative technologies, and the growth of cyber threats, the issue of organizing effective cybersecurity for enterprises is becoming particularly important. To protect today's modern digital enterprise, you need a comprehensive strategy for secure access to your corporate resources anytime, anywhere, regardless of where they are located. By following Zero Trust Architecture (ZTA) principles, which call for least privilege access and continuous verification, businesses can effectively minimize their attack surface and limit potential losses from compromised accounts. However, existing access control and authentication mechanisms alone are not always sufficient to ensure complete protection of critical data, especially in scenarios where proof of access rights or actions is required without revealing content. In such cases, an effective addition to ZTA can be the use of Zero-Knowledge (ZK) concept, which allows confirming access rights or ownership (knowledge) of certain information without the need to disclose it, which significantly reduces the risks of leaks and unauthorized access. At the same time, representatives of businesses interested in the security of their systems are not yet fully aware of the advantages of this concept. The practical application of already known Zero-Knowledge Proof (ZKP) capabilities in various relevant areas that ensure security is being hampered, among other things, by a lack of awareness and insufficient theoretical training in this area among specialists responsible for security and communicating these capabilities (their potential) to the managers of relevant IT companies. In other words, there is currently a problem related to a lack of awareness about the zero-knowledge concept (its theoretical and practical significance) for making the right decision when building a security system for a corporate information system in modern conditions. This article is exactly aimed at solving this problem. The purpose of this work is to systematize the theoretical foundations and practical application of the zero-knowledge concept using simple and obvious examples in order to understand the potential of ZKP in solving problems of confidentiality/privacy and data verification. To this end, it outlined the main aspects of the zero-knowledge concept, including an analysis of the applicability of interactive and non-interactive approaches, an assessment of existing ZKP systems, and a conceptual representation of zk-SNARK technology based on the popular Groth16 scheme with mathematical justification. This contributes to a better understanding and future use of this dynamically developing and complex concept as one of the key mechanisms of modern cryptography, providing the ability to prove the correctness of calculations without disclosing the computational process or the initial data.
Healthcare data is among the most sensitive and frequently targeted information in the digital era. Existing centralised Electronic Health Record (EHR) systems are vulnerable to data breaches, unauthorised access, and single-point failures. This paper introduces a blockchain-based privacy-preserving framework for healthcare data management that integrates smart contracts, attribute-based encryption (ABE), and zero-knowledge proofs (ZKP) to ensure tamper-proof, role-gated data access. Our system is deployed on a permissioned Hyperledger Fabric network with a RESTful API gateway and a React-based patient portal. Experimental evaluations show that the proposed system achieves 99.2% access-control policy enforcement, reduces unauthorised access incidents to near zero, and maintains record retrieval latency under 180 ms at the 95th percentile. The framework also supports HIPAA and GDPR compliance through immutable audit trails and consent lifecycle management
In the context of rapid and widespread digitalization of society, active implementation of new innovative technologies, and the growth of cyber threats, the issue of organizing effective cybersecurity for enterprises is becoming particularly important. To protect today's modern digital enterprise, you need a comprehensive strategy for secure access to your corporate resources anytime, anywhere, regardless of where they are located. By following Zero Trust Architecture (ZTA) principles, which call for least privilege access and continuous verification, businesses can effectively minimize their attack surface and limit potential losses from compromised accounts. However, existing access control and authentication mechanisms alone are not always sufficient to ensure complete protection of critical data, especially in scenarios where proof of access rights or actions is required without revealing content. In such cases, an effective addition to ZTA can be the use of Zero-Knowledge (ZK) concept, which allows confirming access rights or ownership (knowledge) of certain information without the need to disclose it, which significantly reduces the risks of leaks and unauthorized access. At the same time, representatives of businesses interested in the security of their systems are not yet fully aware of the advantages of this concept. The practical application of already known Zero-Knowledge Proof (ZKP) capabilities in various relevant areas that ensure security is being hampered, among other things, by a lack of awareness and insufficient theoretical training in this area among specialists responsible for security and communicating these capabilities (their potential) to the managers of relevant IT companies. In other words, there is currently a problem related to a lack of awareness about the zero-knowledge concept (its theoretical and practical significance) for making the right decision when building a security system for a corporate information system in modern conditions. This article is exactly aimed at solving this problem. The purpose of this work is to systematize the theoretical foundations and practical application of the zero-knowledge concept using simple and obvious examples in order to understand the potential of ZKP in solving problems of confidentiality/privacy and data verification. To this end, it outlined the main aspects of the zero-knowledge concept, including an analysis of the applicability of interactive and non-interactive approaches, an assessment of existing ZKP systems, and a conceptual representation of zk-SNARK technology based on the popular Groth16 scheme with mathematical justification. This contributes to a better understanding and future use of this dynamically developing and complex concept as one of the key mechanisms of modern cryptography, providing the ability to prove the correctness of calculations without disclosing the computational process or the initial data.
Tom Sorger, Eric Cornelissen, Aman Kumar Sharma, Javier Ron · 6 authors
Software Bills of Materials (SBOMs) are increasingly mandated by regulators, yet existing sharing mechanisms impose a binary choice between full disclosure and full opacity. This exposes software suppliers to attacks that can be deduced from the SBOM only, such as the presence of a vulnerable dependency. Conversely, software consumers can be fooled by software suppliers who modify or misrepresent published SBOMs. We present zkSBOM, a privacy-preserving SBOM sharing mechanism designed to address these threats. zkSBOM uses zero-knowledge sets to cryptographically commit to the components within an SBOM. Software consumers can query for known vulnerabilities and receive a cryptographic proof confirming whether the artifact described by the SBOM is affected, without revealing any additional SBOM content. We conduct a security analysis of zkSBOM by quantifying expected leakage from inclusion and exclusion proofs. We demonstrate real-world feasibility by applying it to realistic scenarios and evaluating its operation requirements. Our evaluation demonstrates that zkSBOM is a strong, secure, and privacy-preserving mechanism for SBOM sharing, protecting software suppliers and software consumers from one another.
Zero-knowledge succinct non-interactive arguments of knowledge (zk-SNARKs) allow for elegant, privacy-preserving validation of computations. PLONK, a subclass of the zk-SNARKs, is certainly useful, but its complex interactions with permutation arguments, lookup tables, and blinding, among other considerations, make the protocol difficult to follow, let alone understand. This paper describes a framework centered around the core components of zk-SNARKs. In particular, we detail the construction of arithmetic gate constraints, representation of witness polynomials, and the Kate-Zaverucha-Goldberg (KZG) commitment scheme. By removing permutation proofs, lookup, and blinding, we aim to simplify the pedagogy of zk-SNARKs and preserve their essential properties of soundness and completeness. We describe a Python module from the ground up that demonstrates the generation and validation of proofs in a PLONK-modified zk-SNARK. We validate the framework and its foundations with a benchmark of a module generating and validating proofs in a PLONK-modified zk-SNARK. We validate the module against a circuit of 1,000 gates and demonstrate that the system correctly rejects all invalid witnesses. We illustrate the expected asymptotic behavior, with a pro tor of tight the module is quasi-linear, and verification, tight. We justify the foundations of the module and describe tight with zero private inputs. We have also bridged the gap between abstract zk-SNARK theoretical arguments and their practical implementation and research. We have provided a simple, empirically grounded mechanism that describes the key components of PLONK. We have done this in such a way that researchers, developers, and teachers can build on this base module and create production-ready systems without the abstraction.
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.
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.
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.
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.
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.
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
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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
Linear contracts are ubiquitous in practice, yet optimal contract theory often prescribes complex, nonlinear structures. We provide a distributional robustness justification for linear contracts. We study a principal-agent problem where the agent exerts costly effort across multiple tasks, generating a stochastic signal upon which the principal conditions payment. The principal faces distributional ambiguity: she knows the expected signal for each effort level, but not the full distribution. She seeks a contract maximizing her worst-case payoff over all distributions consistent with this partial knowledge. Our main result shows that linear contracts are optimal for such a principal. For any contract, there exists a linear contract achieving weakly higher worst-case payoff. The proof introduces the concavification approach built around the notion of self-inducing actions; these are actions where an affine contract simultaneously induces the action as optimal and supports the concave envelope of payments from above. We show that self-inducing actions always exist as maximizers of the gap between the concave envelope and agent's cost function. We extend these results to multi-party settings. In common agency with multiple principals, we show that affine contracts improve all principals' worst-case payoffs. In team production with multiple agents, we establish a complementary necessity result: if any agent's contract is non-affine, the unique ex-post robust equilibrium is zero effort. Finally, we show that homogeneous utility and cost functions yield tractable characterizations, enabling closed-form approximation ratios and a sharp boundary between computational tractability results.
Privacy-preserving truth discovery (PPTD) has garnered significant attention in mobile crowdsensing (MCS). However, existing research lacks sufficient privacy protection and is often vulnerable to collusion attacks among malicious participants. Moreover, incorrect data submitted by unreliable users and their weights may reduce the accuracy of truth discovery. To address these issues, this paper proposes a privacy-preserving truth discovery framework resistant to collusion and reputation fraud (TD-RCRF) that is highly resistant to collusion and reputation fraud. The scheme employs additive secret sharing to protect sensing data, weights, intermediate results, and ground truth. To screen trustworthy users who meet reputation requirements under the non-colluding dual-server model, we propose a privacy-preserving reputation verification algorithm that combines Pedersen commitment and zero-knowledge proof to verify the validity of mobile users’ reputation values. Additionally, we propose a homomorphic strategy that converts shares between multiplication and addition and use it to design a lightweight truth discovery algorithm that further improves the accuracy of the “truth” using reputation values. Security analysis proves that TD-RCRF is privacy-preserving and secure under the non-colluding dual-server assumption. Theoretical analysis and experiments show that it is practical and efficient.
Canon² — Trust Layer Research Archive. In deterministic, decentralized computational frameworks, state mutations are immutable, linearly ordered, and rigidly governed by consensus constraints. Reversing or rolling back such state transitions traditionally necessitates revealing the sensitive state artifacts subject to the rollback, fundamentally destroying the cryptographic confidentiality of participant actors. I introduce the Zero-Knowledge State Reversal Protocol (ZK-SRP), a method designed to allow participating deterministic nodes to cryptographically prove the legitimacy, necessity, and validity of a state rollback without disclosing the underlying payloads of the state to any governing validator. I present a framework wherein zero-knowledge succinct non-interactive arguments (SNARKs/STARKs) are bound tightly into deterministic hashing algorithms (specifically SHA3-256) and anchored directly to the Trust Layer Certificate Fabric. In this design, execution nodes issue Reversal Envelopes that contain mathematically verifiable proofs that a specific backward transition maps cleanly onto earlier hash obligations. Through this protocol, the rollback itself becomes deterministic and universally validatable. I outline how this operates within the Lume-V wrapper ecosystem, the DAIGS master taxonomy, and the self-healing mechanisms of Type-4 Synthetic Organisms. I present what is, to my knowledge, the first deterministic privacy-preserving state reversal architecture that guarantees zero state leakage while maintaining general-purpose runtime rollbacks, ensuring that synthetic agents and multi-agent arbitration channels can effectively unspool catastrophic logic errors without breaking strict confidentiality agreements.
Auditing the semantic properties of proprietary data creates a fundamental tension: verification requires transparent access, while proprietary rights demand confidentiality. While Zero-Knowledge Proofs (ZKPs) ensure privacy, they are typically limited to precise algebraic constraints and are ill-suited for verifying qualitative, unstructured properties, such as the logic within a codebase. We propose {\em Agentic Witnessing}, a framework that moves verification from attested execution to {\em attested reasoning}. The system is composed of three agents: a Verifier (who wants to check properties of a dataset), a Prover (who owns the dataset) and an Auditor (that inspects the dataset). The Verifier is allowed to ask a limited number of simple binary true/false questions to the auditor. By isolating an LLM-based Auditor within a Trusted Execution Environment (TEE), the system enables the Verifier to query a Prover's private data via simple Boolean queries, without exposing the raw dataset. The Auditor uses the Model Context Protocol (MCP) to dynamically inspect the target dataset, producing a yes/no verdict accompanied by a cryptographic transcript: a signed hash chain binding the reasoning trace to both the original dataset and the TEE's hardware root of trust. We demonstrate this architecture by automating the artifact evaluation process for 21 peer-reviewed computer science papers with released codebases on GitHub (e.g. Does the codebase implement the system described in the paper?). We verified five high-level properties of these codebases described in the corresponding publications, treating the source code as private. Our results show that TEE-enabled agentic auditing provides a mechanism for privacy-preserving oversight, effectively decoupling qualitative verification from the need for data disclosure.
Financial privacy protocols on public blockchains protect transaction linkability but offer no defense when users are physically compelled to reveal their credentials — the "$5 wrench attack." This paper presents a complete solution in two integrated parts. Part I provides the formal cryptographic foundation: dual-nullifier arithmetic selectors within Groth16 zk-SNARK circuits, where path selection between real and decoy funds is computed entirely within the zero-knowledge witness without conditional branching. The R1CS structure is identical for both execution paths (<8% overhead), and the resulting proof is computationally indistinguishable regardless of whether coercion resistance was activated. We formalize peace of mind as a protocol design principle, prove coercion resistance through a four-game sequence-of-games reduction under the Sponge PRF and q-SDH assumptions, and prove withdrawal soundness, double-spend prevention, and front-running resistance. Part II presents ZK-Sentinel V11: a Diamond EIP-2535 architecture with 10 independently upgradeable facets and 104 functions; Stealth Shielded Transfers eliminating temporal correlation at ~60% lower gas cost; 92 privacy pools across 12 tokens on two networks; and a Multi-Tier Compliance Oracle with 4 KYC levels. Indistinguishability is confirmed empirically: a Random Forest classifier trained on 10,000 simulated transactions achieves 50.3% accuracy (AUC-ROC 0.501, p=0.87), consistent with random guessing. To our knowledge, this is the first work providing both a formal coercion resistance proof and a production-scale multi-asset deployment validated across all 12 tokens on two networks.
Anti-Money Laundering regulatory frameworks share an unstated design premise: the adversary is human. We demonstrate that this premise is architecturally false: a fully autonomous, deterministic multi-agent system can perform every function of a human criminal organization without possessing computational mens rea. We formalize this system as HYDRA-A and prove that against it, intent-based AML detection mechanisms have zero expected utility. Contributions: (C1) A formal model of the autonomous AML adversary with role-by-role replacement of human criminal organization structure. (C2) The Theorem of Absent Mens Rea: a formal proof that a fully-specified autonomous adversary cannot possess criminal intent, derivable from the typed component interfaces of HYDRA-A. (C3) A Corollary of AML Framework Obsolescence: every intent-based detection mechanism has zero expected utility against HYDRA-A. (C4) A personality vector P=(rho, alpha, sigma, tau) with five adversarial archetypes. (C5) A No Stationary Nash Equilibrium theorem for the arms race between HYDRA-A and adaptive defenses. (C6) Zero-knowledge behavioral verification is the only architectural class that provides a formal defense guarantee against HYDRA-A.
The proliferation of sophisticated AI and bot networks necessitates robust methods for verifying human uniqueness and liveness in digital ecosystems. Existing Proof-of-Personhood (PoP) solutions rely on centralized authorities, invasive static biometrics, or socially-correlatable data, creating vulnerabilities in privacy, security, and accessibility. We introduce the Entros Protocol, a decentralized framework for PoP and Self-Sovereign Identity built on Solana. The core innovation is temporal consistency: the assertion that human identity is best proven not by a static secret, but by the bounded, chaotic drift of biological and behavioral patterns over time. The framework captures multi-modal behavioral data (voice prosody, hand tremor, touch dynamics) during a configurable behavioral challenge, extracts a 308-dimensional feature vector, and produces a 256-bit locality-sensitive hash via SimHash. A Groth16 zero-knowledge proof verifies that consecutive fingerprints fall within a bounded Hamming distance without revealing either value. Attestations are anchored to non-transferable identity tokens (SPL Token-2022) with progressive Trust Scores. We provide formal security definitions, analyze the protocol against replay, synthesis, and Sybil attacks, introduce a graduated trust model distinguishing first-time liveness checks from sustained temporal consistency, and present benchmarks from a working implementation deployed on Solana devnet.
We prove three impossibility theorems establishing fundamental limits on universal AML compliance in zero-knowledge financial systems. T1 (Completeness Impossibility): no ZK compliance system achieves complete coverage of illicit transactions under rational adversarial behavior. T2 (Oracle Integrity Impossibility): no decentralized oracle network achieves integrity guarantees when state-level adversaries control oracle nodes — cryptographically valid compliance proofs can be semantically false by construction. T3 (Sovereignty Gap Impossibility): no voluntary international compliance framework achieves universal participation when sovereign defection is individually rational. These theorems are not engineering limitations addressable by better cryptography — they are structural properties of the compliance problem under adversarial conditions. Validated empirically against the Tornado Cash OFAC designation (T3) and the Lazarus Group / Ronin Bridge exploit (T2). The theorems characterize the residual attack surface that any compliance architecture must acknowledge and bound rather than claim to eliminate.
The Model State Attestation Framework (MSAF) is the theoretical foundation of the Auburn Governance Stack. It establishes the intellectual authority for why cryptographic AI attestation is necessary, defines the three-tier attestation architecture, surveys over 200 papers from 2022 through 2026 confirming that no existing system composes hardware trust, continuous model health monitoring, and supply chain provenance into a unified attestation artifact, and documents the theoretical ceilings that bound what attestation can and cannot guarantee. The framework addresses a fundamental governance paradox: organizations deploying foundation models into critical infrastructure cannot definitively demonstrate that a specific output was generated by a model version in a compliant internal state. Current governance artifacts including model cards, training logs, and static benchmarks are descriptive rather than prescriptive and fundamentally non-verifiable. MSAF composes three verification tiers into a layered architecture. The first tier provides TEE-backed platform attestation for execution environment integrity, proving the silicon is real and uncompromised. The second tier provides signed continuous metrics for training and inference health monitoring, proving the model is healthy at the moment of inference. The third tier provides selective zero-knowledge proofs for high-value inference verification, enabling verification without exposing proprietary model internals. The composed attestation artifact is mapped to specific evidence requirements across five regulatory frameworks: EU AI Act Articles 11 and 15, FDA Software as a Medical Device Pre-Determined Change Control Plans, Federal Reserve SR 11-7 ongoing monitoring requirements, US Federal Procurement mandates, and AI insurance underwriting. The framework identifies the theoretical ceilings that bound attestation: Rice's theorem establishing the undecidability of semantic properties, the Impossibility Sandwich bounding what verification can achieve between Rice's theorem and Gödel's incompleteness, and TEE physical side-channel vulnerabilities limiting hardware trust guarantees. The honest framing: MSAF provides probabilistic risk reduction and accountability infrastructure, not behavioral safety guarantees. This is analogous to financial auditing, which certifies process compliance without guaranteeing future solvency. The building blocks exist individually. MSAF is the composition that binds them into an enforceable governance architecture. This work was previously hosted on Figshare, where the author maintained a portfolio of 29 publications with minted DOIs and an established ORCID record. The author's Figshare account was disabled without prior notice, without citation of a specific terms violation, and without opportunity for review, rendering all published items and their associated DOIs inaccessible. No communication was provided before or at the time of the disable action. This deposit and associated deposits on Zenodo ensure continued public accessibility of the author's research on institutional infrastructure with appropriate permanence guarantees.
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Adversarial Robustness in Machine Learning
Security and Verification in Computing
Physical Unclonable Functions (PUFs) and Hardware Security
Abstract Multi-Scalar Multiplication (MSM) is the primary computational bottleneck in zero-knowledge (ZK) proof generation for decentralized networks. This research accelerates MSM by solving the memory bandwidth constraints inherent in high-dimensional elliptic curve cryptography. We introduce Modular Hypercube Chunking, a novel microarchitectural approach that partitions high-dimensional algebraic precomputations into smaller, orthogonal blocks. Specifically, we divide a 12-dimensional workload into three separate 4D hypercubes, restricting the entire memory footprint to 31.1 KB. This geometric partitioning ensures perfect residency within the ultra-fast L1 cache of modern processors. By employing shared doubling across these blocks, the algorithm processes twelve scalars simultaneously with a single elliptic curve duplication, bypassing slow RAM access entirely. Empirical evaluations conducted on an ARM Snapdragon 8 Gen 2 mobile processor demonstrate a peak 5.37× speedup compared to optimized sequential baselines, reducing the computational cost to 18.44 microseconds per scalar. These findings prove that geometric data partitioning within strict L1 cache boundaries significantly outperforms traditional arithmetic-heavy optimizations. The implications of this work provide a highly scalable architecture capable of executing server-grade ZK-Rollup proof generation on resource-constrained edge devices, while establishing a highly efficient blueprint for future multicore hardware accelerators. Furthermore, initial stress-tests of a 12D monolithic architecture (68 MB footprint) yielded an anomalous 8.88× peak speedup. This finding reveals a novel sparse-access memory optimization path, which we introduce as an open architectural challenge.