We present a production-ready framework for verifiable self-organization in networks of 768 coupled quantum oscillators (the “Crystal Brain”), integrating sixfine-tuned components: adaptive SPSA optimization with automatic plateau escape, multi-resolution Louvain community detection, non-deterministic proof seeds,normalized causal efficacy metrics, dynamic Merkle root hashing, and a semanticproof-tagging API. We map the Ising regime classification of Bhalla et al. (2026)onto a Kuramoto-type phase dynamics and demonstrate convergence to a coherentCAPTURE regime with 84.7% capture fraction. A companion octonionic atlas of 50nuclides (OctoSpec v0.4) reveals a moderate anti-correlation (r = −0.54, p < 0.001)between the Octonionic Anomaly Index and nuclear binding energy. All coherencemilestones are certified by zero-knowledge proofs generated at 80-bit security viathe ZEE200 backend and registered immutably on the ARKHE OCTRA chain.
The relationship between deterministic polynomial time (P) and polynomial space (PSPACE) is one of the foundational open problems in computational complexity theory. While proving P = PSPACE remains elusive and is widely believed to be false, the characterizations of PSPACE have yielded profound insights into modern computer science, specifically cryptography and zero-knowledge proofs. This paper surveys the landscape of PSPACE, examines the three fundamental barriers preventing resolution, and presents original systems-level experiments in C and Python that make the space-time tradeoff at the heart of the problem tangible and measurable.
Background: Healthcare organizations face unprecedented challenges in maintaining process compliance due to increasingly federated data and systems topologies, coupled with complex state, federal, and jurisdictional regulatory compliance and verification requirements. The emergence of distributed ledger technology (DLT) and artificial intelligence presents both transformative opportunities and significant compliance challenges. These emerging technologies enable computing paradigms that shift toward data locality models where computational models meet the data rather than moving sensitive patient information across organizational boundaries. This computational approach offers innovative pathways to mitigate data breach risks, while simultaneously introducing new verification complexities as the underlying technologies continue to advance: healthcare entities must cryptographically prove that operations performed on locally-held data were executed according to approved specifications while enabling selective disclosure capabilities across entity lines. However, traditional verification mechanisms lack the cryptographic guarantees necessary for these privacy-preserving, multi-entity healthcare workflows, creating substantial risks in clinical decision-making, patient privacy, and regulatory adherence. Objective: This paper introduces the ZK-PRET Business Process Prover framework that integrates Object Management Group (OMG) business process standards with zero-knowledge cryptographic verification to enable privacy-preserving healthcare process compliance across distributed systems. Methods: We developed a multi-layer architecture combining formal business process modeling, zero-knowledge proof generation, and regulatory compliance verification. The framework extends established OMG standards with cryptographic verification capabilities to achieve verifiable compliance, privacy preservation, and regulatory accountability. Implementation testing was conducted in synthetic data environments designed to represent real-world healthcare scenarios.¹ These environments enable comprehensive modeling and testing of multi-entity process orchestration patterns while maintaining privacy protections essential for healthcare research and development. All scenarios, clinical examples, and process expressions presented in this paper utilize synthetic data to ensure no real patient data, clinical records, or identifiable health information was used. Results: The ZK-PRET Business Process Prover framework demonstrates practical applicability across many healthcare domains including treatment planning, telemedicine coordination, healthcare administration, consumer health services, multi-entity clinical trials, and supply chain management. Implementation results demonstrate cryptographic verification capabilities that enable mathematical prevention of regulatory violations rather than post-hoc detection. The results demonstrate configurable privacy preservation through zero-knowledge verification and consistent proof sizes suitable for modeling complex orchestrations, while leveraging already widely used Web 2 process models, suitable for multiple runtime deployment topologies. Conclusions: Zero-knowledge healthcare process verification represents a foundational technology for regulatory compliance in distributed healthcare systems. While agentic AI systems present important opportunities for automation, the underlying requirement for verifiable process compliance through cryptographic means brings broader challenges. ZK-PRET Business Process Prover addresses these challenges in healthcare transformative flows, enabling safer deployment of autonomous systems while maintaining regulatory standards.
Abstract This paper presents two offline, on-premise NLP proof-of-concept assistants built on a shared architecture for internal knowledge access in the Central Bank of Bosnia and Herzegovina: (i) a semantic document search tool for internal Word/PDF repositories and (ii) an HR chatbot that applies retrieval-augmented generation (RAG) over indexed HR policies and procedures. Rather than proposing a novel NLP method, the paper contributes by documenting a reusable offline architecture for institutional AI assistants in a security-constrained central banking environment and by providing pilot evidence on how established semantic retrieval and RAG techniques can be adapted to strict requirements of confidentiality, data sovereignty, and governance. The semantic search assistant combines exact phrase matching with embedding-based retrieval and hybrid re-ranking, while the HR chatbot generates source-grounded answers using locally hosted language models under explicit governance constraints, including B/H/S-only output, strict fallback behaviour, and transparent display of retrieved passages. Pilot results indicate that hybrid retrieval offers the most reliable performance across representative internal queries, while the HR chatbot demonstrates the feasibility of document-grounded employee support under offline institutional constraints. The findings provide preliminary evidence that offline NLP assistants can improve access to internal institutional knowledge while remaining compatible with the security and operational risk requirements typical of central banking environments.
Achilles was invincible in battle — except for one point of structural vulnerability that no amount of strength could compensate for. Modern LLM-based agent frameworks (LangChain, AutoGen, CrewAI, ReAct) share this property exactly: impressive capability in controlled settings, catastrophically exploitable in regulated production environments through a single architectural flaw — the language model controls the decision. Organizations in regulated sectors (finance, insurance, healthcare, legal, compliance) face a direct consequence: these frameworks cannot be deployed in workflows subject to EU AI Act, DORA, or GDPR Article 22, because they provide no structural guarantee of determinism, auditability, or equal treatment. Traditional symbolic agent systems (JADE, Jason, Jadex) satisfy regulatory requirements but cannot ingest the unstructured natural-language inputs that define real enterprise workflows. The industry needs both properties simultaneously. No existing framework provides them. AQUILES is a production architecture for AI agents in regulated domains that resolves this gap through principled separation of concerns, instantiating the HADD paradigm (Hybrid Agents with Deterministic Decisions). AQUILES organizes agent functionality into five cooperating layers: an Interface Layer converting unstructured input into typed, validated beliefs via LLM sensors; a Cognition Layer performing pure-function BDI deliberation fully determined by its inputs; a Planning Layer selecting from a pre-verified HTN plan library without runtime synthesis; an Execution Layer enforcing typed precondition and postcondition contracts on every capability invocation; and a transverse Observation Layer producing append-only audit entries synchronously with every state transition. Language models are confined strictly to the perception boundary — they parse input into beliefs, they never select goals, plans, or capabilities. The heel remains; it is simply no longer load-bearing. The HADD paradigm is codified as six architectural invariants: (I1) Typed Role Inversion — LLMs as sensors only, never as control-flow components; (I2) Deterministic Cognition — the reasoning layer is a pure function of beliefs, goals, and rules; (I3) Bounded Planning — execution draws exclusively from a pre-verified plan library; (I4) Validated Execution — every capability invocation passes typed pre/post-condition checks; (I5) Complete Observability — every decision is forensically reconstructable from the audit log; (I6) Epistemic Precondition — no belief enters the BDI cycle without satisfying freshness, non-contestation, and source triangulation, enforced by the EVR module (Epistemic Verification for RAG). Any implementation satisfying all six invariants acquires reproducibility, zero LLM hallucination in state, LLM provider independence, and structural alignment with EU AI Act Articles 12–15 — as architectural properties, not retrofitted compliance measures. AQUILES partitions agents into cognitive holons (BDI-HTN reasoning components subject to full HADD governance) and reactive holons (deterministic capability executors verified by typed contracts alone). In observed production deployments, 70–80% of holons by count are reactive, meaning governance complexity scales with the cognitive subset rather than with total component count. The AQUILES protocol is language-agnostic by design: cognitive holons are typically Python (Anthropic SDK, sentence-transformers, pypdf); endpoint-monitoring holons are Go (single-binary cross-compilation); blockchain and zero-knowledge holons are Rust (arkworks, halo2, revm). We prove a Language Neutrality property: HADD compliance is preserved across heterogeneous polyglot deployments. For autonomous field deployments, AQUILES derives MYRMIDON agents that execute a signed MissionPackage autonomously on constrained hardware, inheriting AQUILES's safety guarantees without requiring runtime connectivity. This paper makes five engineering contributions: (C1) the HADD paradigm formalized as six architectural invariants with rationale and derived operational properties; (C2) the cognitive/reactive holon distinction and its governance economy consequences; (C3) a polyglot holon model with Language Neutrality proof and domain-language affinity mapping across Python, Go, and Rust; (C4) a multi-tenant operational-cell formalism enabling cryptographically enforced tenant isolation for regulated multi-client deployments; (C5) four reusable design patterns extracted from production experience (Sensor Firewall, Belief Expiry, Capability Contract, Observation Fanout), together with measurement methodology, adoption guidance, and explicit characterization of the architecture's limits.
While Large Language Models have achieved notable success on formal mathematics benchmarks such as MiniF2F, it remains unclear whether these results stem from genuine logical reasoning or semantic pattern matching against pre-training data. This paper identifies Architectural Reasoning: the ability to synthesize formal proofs using exclusively local axioms and definitions within an alien math domain, as the necessary ability for future automated theorem discovery AI. We use the Obfuscated Natural Number Game, a benchmark to evaluate Architectural Reasoning. By renaming identifiers in the Natural Number Game in Lean 4, we created a zero-knowledge, closed environment. We evaluate state-of-the-art models, finding a universal latency tax where obfuscation increases inference time. The results also reveal a divergence in robustness: while general models (Claude-Sonnet-4.5, GPT-4o) suffer performance degradation, reasoning models (DeepSeek-R1, GPT-5, DeepSeek-Prover-V2) maintain the same accuracy despite the absence of semantic cues. These findings provide a quantitative metric for assessing the true capacity for mathematical reasoning.
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Mathematics, Computing, and Information Processing
Electronic voting systems are designed to modernise democratic processes by providing efficient, transparent, and accessible elections. They promise rapid tallying, reduced human error, and increased participation. However, large-scale deployment remains hindered by unresolved concerns around security, privacy, scalability, and trust. Direct recording electronic machines suffer from limited verifiability. In Internet voting, the more fundamental risks stem from compromised end-user devices, difficulty in achieving end-to-end verifiability that ordinary voters can meaningfully check, and exposure to coercion and vote buying, rather than generic cyberattacks alone. Blockchain-based approaches, while offering immutability and public auditability, face significant scalability limits. Network throughput and latency constrain election-sized workloads, fee volatility creates cost uncertainty, and per-vote on-chain actions, such as posting ballots and verifying cryptographic proofs, incur prohibitive costs that grow linearly with the number of voters. The openness of public ledgers also leaks metadata that can erode privacy. Consequently, achieving accountability and transparency without sacrificing individual ballot secrecy and practical efficiency remains a central challenge. This thesis addresses these challenges by providing the first thorough analysis of a ranked-choice blockchain election protocol that had not been previously examined in detail. The analysis identifies critical limitations related to privacy and efficiency that weaken unlinkability and verifiability. Building on these findings, the first significant contribution of this thesis is the design of a new, verifiable, and privacy-preserving voting framework that eliminates the need for a trusted tallying authority. The scheme employs anonymous participation tokens and nullifiers to enforce one-time eligibility. At the same time, voters cast encrypted ballots accompanied by zero-knowledge proofs that confirm eligibility, correctness, and uniqueness without disclosing their identity or the content of their vote. Tallying is achieved through a decentralised threshold decryption process that ensures fairness and confidentiality. The second significant contribution of this thesis is an efficient proof-batching and verification mechanism that addresses the scalability bottlenecks of existing blockchain-based approaches. By aggregating multiple proofs off-chain and submitting a single, succinct batch proof with updated commitments, the protocol reduces on-chain verification to a near-constant cost per voter. This significantly decreases computational and financial overhead, enabling scalability to large elections. The proposed framework is analysed under realistic adversarial models and shown to achieve privacy, eligibility, uniqueness, and universal verifiability. Performance evaluation demonstrates that the batching mechanism substantially lowers costs compared to existing protocols. Overall, this research advances the state of the art in blockchain-based electronic voting by providing the first comprehensive evaluation of a ranked-choice protocol and proposing novel mechanisms that overcome its limitations, thereby laying a foundation for secure, transparent, and scalable digital elections.
Certificate management systems encompass aca-demic records; government-issued documents; professional li-censes; notary services.They play a vital role in creating a modern e-government system.Current certificate management methods are plagued by forgery, slow veri-fication, fragmented records between several institutions and vulnerability to compro-mise because of increasing numbers of data breaches.Blockchain innovations create the potential to address these different chal-lenges given their unique features such as: immutability, de-centralization, cryptographic security and full traceability via transparent auditability.The objective of this paper is to combine the current research on certificate management with blockchain technology via a systematic review of 12 peer-reviewed journals which focus on: Research methods used by each author.Data sets used by each author.The evaluation environment used by each author.The performance and security metrics that are being utilized in each author's research.The comparative findings of each author's research with respect to certificate management using public and permissioned blockchains.Results of this study demonstrate that the current core tech-nical functionality of certificate management using blockchain has been established; however, there are still major gaps in the current body of knowledge that need to be addressed, including:1. Privacy solutions, specifically zero-knowledge proofs.2. Ability to scale to the national level.3. Cross-platform interoperability.4. Validation of real-world prototypes.Additionally, we have described each of these gaps explic-itly and created a prioritized future agenda for research that addresses issues related to privacy, scalability, interoperability, security auditing and user-centered evaluation.
Biometric authentication has become a crucial element of digital identity systems, leading to a rise in significant challenges for information governance, privacy, and organizational trust. Current approaches address either biometric template protection or liveness verification in isolation, significantly overlooking their interdependence in privacy-preserving system design. In practice biometric privacy depends jointly on template protection, liveness verification, and compliance with biometric standards such as ISO/IEC 24745, which define irreversibility, unlinkability, and renewability requirements. Without integrating all three, biometric systems remain vulnerable. A cryptographically protected template may still be exploited if liveness checks fail, whereas standalone liveness mechanisms risk exposing sensitive biometric features. This research-in-progress paper presents ZKBioVault, a conceptual framework that integrates cancellable biometrics, fuzzy vault cryptosystems, and zero-knowledge proofs to support privacy-preserving authentication. Combining principles from the biometric template protection literature and ISO/IEC 24745 standards, the framework introduces a two-phase architecture that is designed for responsible digital infrastructure. A scenario-driven application example demonstrates how ZKBioVault can reduce organizational risk and strengthen the trust placed in biometric information management. This is extremely useful in environments which are increasingly affected by synthetic and AI-generated biometric artifacts.
Digital contracts are formal agreements created, signed, stored, verified and executed through digital platforms. These contracts require long-term protection because they often contain legally, financially and organisationally sensitive information. However, classical cryptographic methods used in current digital contract systems may become vulnerable with advances in quantum computing. This paper focuses on Quantum Internet of Contracts (QIoCs) as a future direction for preparing digital contracts for the quantum era. It examines post-quantum cryptography, quantum communication, blockchain, smart contracts, digital identity, zero-knowledge proofs and risk-based migration strategies. The paper argues that QIoCs cannot rely on a single security method. Instead, they require a layered approach that combines quantum-resistant blockchain protocols, privacy-preserving data authentication, secure audit trails, legal governance and staged migration from classical systems to quantum-safe contract infrastructures. The paper highlights the need for legal acceptance, governance standards and real-world testing of proposed post-quantum models. Overall, the paper provides a review-based framework for building safer and more reliable digital contracts in a quantum-safe future.
This paper argues that trust scores — from credit ratings and ESG scores to AI-generated trust metrics — fail not because of poor implementation, but because trust itself is the wrong abstraction. Trust is not a scalar quantity but a contextual, relational, and topological phenomenon. Any attempt to reduce it to a universal numerical score leads to fragility, manipulation, exclusion, and systemic failure. We identify five structural failure modes (context collapse, Goodhart's Law, epistemic centralization, irreversibility, and metric substitution for truth), supported by historical case studies (Enron, Wirecard, Volkswagen Dieselgate, the 2008 subprime crisis, ESG rating failures). A formal impossibility argument demonstrates that no universal trust score can simultaneously satisfy context independence, temporal stability, observer neutrality, and manipulation resistance. We propose proof-based systems as the alternative paradigm, where trust is not measured but rendered unnecessary through local, irreversible verification. Examples include Bitcoin Proof-of-Work, zero-knowledge proofs, and blockchain-based supply chain traceability.
Tina Yi Jin Hsieh, Carl Eriksson, Garth Meckler, Matthew Hansen · 12 authors
Introduction and Objective: Traditional adverse safety events (ASE) identification relies on domain experts to manually review and annotate charts, which hinders the scalability of processing high-volume EMS data. This study explores the use of large language model (LLM) with a knowledge base to automate extraction of adverse safety events (ASE) from unstructured emergency medical service (EMS) notes for pediatric out-of-hospital cardiac arrest (OHCA) as proof of concept. Data Sources and Study Design: Pediatric OHCA records from a national EMS provider were obtained from 2017 to 2020. Leveraging the Pediatric Prehospital Adverse Safety Event Detection System (PEDS) as a foundational knowledge base, we used the LinkML framework to develop an ontology to define ASEs across six essential EMS care domains. To convert unstructured EMS narratives into structured prompts, we used the Structured Prompt Interrogation and Recursive Extraction of Semantics (SPIRES) method, which generated schema-driven prompts to guide the GPT-3.5 model in identifying ASEs. By mapping unstructured data into structured concepts consistent with PEDS guidelines, the model produced targeted prompts that supported effective entity extraction. Results: We evaluated framework effectiveness with accuracy, recall, precision, F1 score, and specificity across 42 pediatric OHCA cases covering ASE-related entities. RescueGPT showed high accuracy in detecting common ASEs (Patient Rhythm, Age, Weight, Length) but revealed challenges in rare events (Failure to Establish IV Access, Incorrect Airway Equipment Size, Failure to Ventilate Patient) likely due to more inconsistent and complex documentation. Conclusions: RescueGPT demonstrates potential in scaling automated ASE detection, but performance varies by completeness and clarity of EMS narrative, particularly with rare events. Fragmented clinical documentation limits accuracy and highlights the need for standardized collection protocols in EMS systems. Future directions will focus on implementing rebalancing strategies for rare events, applying explainability methods to improve decision-making transparency, and refining text segmentation techniques to handle mixed outcomes to further improve performance.
Pascal Berrang, Mirco Giacobbe, Jacob Swales, Xiao Yang
We introduce a technology to formally verify that a software system satisfies a temporal specification of functional correctness, without revealing the system itself. Our method combines a deductive approach to model checking to obtain a formal certificate of correctness for the system, with zero-knowledge proofs to convince an external verifier that the system -- kept secret -- complies with its specification of correctness -- made public. We consider proof certificates represented as ranking functions, and introduce both an explicit-state and a symbolic scheme for model checking in zero knowledge. Our explicit-state scheme assumes systems represented as transition graphs. We use polynomial commitments to convince the verifier that the public proof certificates correspond to the secret transition relation. Our symbolic scheme assumes systems specified as linear guarded commands and uses piecewise-linear ranking functions. We apply Farkas' lemma to obtain a witness for the validity of the ranking function with public and secret components, and employ sigma protocols for matrix multiplication and range proofs to convince the verifier of the witness's existence. We built a prototype to demonstrate the practical efficacy of our two schemes on linear temporal logic verification examples. Our technology enables formal verification in domains where both the safety and the confidentiality of the system under analysis are critical.
Electronic Healthcare Records (EHRs) provide distributed access to patient and doctor information through pervasive cloud-based storage. As this data is highly sensitive, robust privacy measures are essential to mitigate adversarial impacts. To ensure optimal privacy across multiple shared EHRs, this article proposes a Session-dependent Zero Knowledge Proof Technique (SZKPT). The framework identifies privacy breaches using two truth values: the first representing optimal session closure, and the second reflecting verification at each sharing instance. Both truth values are validated through iterated session validations, which are managed using a deep learning paradigm. During training, different combinations of truth values are employed to maximize privacy during data sharing, while iterative processes train consecutive validation instances to improve breach detection. Truth values are continuously updated to reflect the session closure and the most recent privacy verification. In practice, if either truth value equals zero, the session is suspended; otherwise, if truth values are valid in consecutive iterations, data sharing is delegated to the authorized user. The process is repeatted at regular intervals with updated truth values, ensuring continuous monitoring and adaptive privacy protection. The proposed technique is rigorously evaluated using key performance metrics, including access verification, computational complexity, privacy breach detection, verification time, and access delegation time. Results demonstrate that SZKPT effectively balances privacy preservation with usability, providing a reliable, scalable, and efficient solution for secure EHR management in cloud-based healthcare systems.
Modern societies are simultaneously confronting demographic collapse and intensifying conflicts over gender equality, care, and labor. These tensions are often treated as policy trade-offs, yet they stem from a deeper ontological limitation: the reduction of human existence to functional structure (E≈S). This paper introduces Universal Phase Crystallization Theory (UPCT) as a foundational shift toward defining existence as generative resonance (E=ΦR). By reframing freedom, equality, and ethics as dynamic conditions of generative participation, the apparent conflict between demographic policy and gender equality dissolves. What emerges is not a compromise, but a civilizational transition from function-centered systems to generation-centered structures. This work provides a unified theoretical framework for rethinking equality, care, and sustainability in the 21st century. Highlights Reveals that conflicts between demographic policy and gender equality originate from a shared S-centric ontology (E≈S) Introduces UPCT (E = ΦR) as a unified framework for redefining existence, equality, and ethics Reconstructs equality as non-comparability of generative potential, beyond functional parity Demonstrates that demographic decline is a systemic failure of generative continuity (d(ΦR)/dt<0) Proposes a civilizational redesign based on generative resonance rather than labor-market optimization Summary & Main Arguments 1. Ontological Diagnosis of Modern CrisisThis paper begins by identifying a foundational contradiction in modern societies: the persistent conflict between demographic sustainability and gender equality. Rather than interpreting this as a policy failure, the paper argues that the root cause lies in an implicit ontological assumption—namely, that human existence is reducible to structural or functional representation (E≈S). Within this framework, individuals are treated as economic actors, legal units, or measurable entities, leading to systemic tensions when biological, relational, and generative dimensions cannot be fully captured. 2. Historical Saturation of Functional EqualityTracing the evolution of equality from formal legal equality to distributive and identity-based equality, the paper demonstrates that modern equality has progressively intensified its reliance on functional comparability. While these developments have been historically emancipatory, they culminate in a paradox: the more equality is pursued through structural comparison, the more differences (biological, genetic, relational) become sources of conflict. This results in a zero-sum system that ultimately fragments social cohesion. 3. UPCT as Ontological ReframingTo resolve this impasse, the paper introduces Universal Phase Crystallization Theory (UPCT), which redefines existence as generative resonance (E=ΦR). Here, Φ represents generative potential, and R relational resonance. Structure (S) is not the essence of existence but a temporary crystallization within a dynamic generative cycle (Φ→R→S→Φ′). This reframing shifts the analytical focus from static structure to dynamic process. 4. Redefinition of Core ValuesWithin the UPCT framework, the foundational concepts of modern philosophy are reinterpreted. Freedom becomes participation in generative processes rather than choice within structures. Equality is redefined as the non-comparability of generative potential rather than functional uniformity. Ethics is formalized as the sustainability condition (d(ΦR)/dt≥0), transforming it from normative prescription to systemic viability condition. 5. Policy Implications and Civilizational TransitionFinally, the paper applies this framework to the conflict between demographic policy and gender equality. It demonstrates that the conflict dissolves when both are reinterpreted through generative conditions rather than structural distribution. Policy interventions—such as reducing structural burdens, restoring relational infrastructure, elevating care, and redesigning time—are reframed as foundational requirements for sustaining generative resonance. This marks not a policy adjustment, but a civilizational transition. Contributions 1. Ontological Regrounding of Social TheoryThis paper provides a fundamental ontological critique of modern social theory by identifying the implicit equation E≈S as the root of contemporary contradictions. By introducing E=ΦR, it establishes a new foundation that integrates process, relation, and generation into the definition of existence. 2. Unified Framework Across DisciplinesThe study bridges philosophy, economics, gender studies, and systems theory by offering a single conceptual framework capable of explaining demographic decline, care crises, and equality conflicts. This integration moves beyond fragmented disciplinary approaches. 3. Redefinition of Equality and EthicsA major theoretical contribution is the redefinition of equality as non-comparability and ethics as a dynamic sustainability condition. This resolves long-standing tensions between fairness, difference, and viability, offering a new paradigm for justice theory. 4. Reinterpretation of Feminist and Critical ThoughtRather than rejecting feminist, Marxist, or care-based critiques, the paper demonstrates how these traditions can be sublated within UPCT. It preserves their insights while extending them beyond structural limitations, avoiding both reductionism and opposition. 5. Civilizational Design FrameworkThe paper advances a practical theoretical model for societal redesign. By translating UPCT into policy principles—structural reduction, relational recovery, generative elevation, and temporal redesign—it provides a concrete pathway for transitioning toward a generative society. 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.1800
Knowledge is free: Zenodo 10.5281/zenodo.20053184Kindle $2.99 for students worldwide This $5,000 Hardcover is not ink. - soon on a suitable platform -It’s a scarecrow stepping down to plant.A humble try to bring 200 years closer. Fields are empty. Fear stands guard.Patience is a cage. Silence feeds no one.Better to be a guide than a ghost. 90% of your hand buys time:Water for the thirsty.Light for the seeking.Breath for the broken.A life sustained to light more lives. If you buy luxury, buy legacy.If you buy this, you buy tomorrow. STNT² = STNT + HumanityManifesto iii "ولست بمحيار الظلام إذا انتحت هدي الهوجل العيسف" ....to Nietzsche. To الشنفريلامية العرب للشنفرى مع الشرح بصوت فالح القضاع Amazon live https://a.co/d/04qKwlpH Paper Book soon.Zero Free Parameters. This is not a popular science book.No analogies were used in the making of this content.This is a technical manuscript. It presents the complete mathematical derivation, reproducible Python code,and experimental logs archived at: DOI:10.5281/zenodo.19894991 Chapter 4: DOI 10.5281/zenodo.19588970Chapter 5: DOI 10.5281/zenodo.19600197Chapter 6: DOI 10.5281/zenodo.19607198 This book contains:- The first geometric structure that brackets Riemann Zeros with 2.23% error- Reproducible Python code for the 25-Cell and 49-Cell operators- A roadmap to 10 technologies: from Zero-Point Energy to Wrap Drive WHAT YOU'LL FIND INSIDE:• The proof that reproduces π²/6 = 1.644934... as the Universe's baseline energy• Why 13+ million quantum vacuum modes collapse to just 24 that matter• The link between Riemann's Zeta Function, Einstein's Λ, and the Riemann Hypothesis FOR WHO:Physicists, mathematicians, engineers, advanced readers comfortable with linear algebra, eigenvalue analysis, and quantum mechanics and anyone who suspects the biggest secrets are hidden in the simplest places.
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.
This chapter explores the intersection between blockchain-based energy systems and data privacy challenges, especially in peer-to-peer energy markets. It highlights how the transparency and immutability of blockchain, combined with real-time data from smart meters and IoT devices, can expose users to re-identification risks and legal conflicts with principles such as the right to be forgotten. The authors examine technical solutions including zero-knowledge proofs, permissioned blockchains, smart contracts with embedded privacy logic, and off-chain storage. Additionally, the chapter emphasizes the importance of privacy-by-design and security-by-default principles in system architecture. It also calls for adaptive legal frameworks such as regulatory sandboxes, along with participatory governance to ensure equitable implementation, especially in the Global South where regulatory and infrastructure disparities persist.
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.