Anonymous digital credentials allow a user to prove possession of an attribute that has been asserted by an identity issuer without the user revealing any extra information about themselves. For example, a user who has received a digital passport credential can prove their “age is <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mo>></mml:mo> <mml:mn>18</mml:mn> </mml:mrow> </mml:math> ” without revealing any other attributes such as their name or date of birth. Despite their clear application to privacy-preserving authentication, anonymous credential schemes have been difficult to deploy at scale. Part of the difficulty arises because schemes in the literature, such as BBS+, use new cryptographic primitives that require system-wide changes to existing issuer infrastructure. In addition, issuers often require digital identity credentials to be device-bound by incorporating the device’s secure element into the presentation flow. As a result, schemes like BBS+ require updates to the hardware on every user's device. We propose new ZK techniques which enable the construction of an anonymous credential scheme for the legacy Elliptic Curve Digital Signature Algorithm (ECDSA) signature scheme. By adding efficient ZK arguments for statements about SHA-256 and document parsing for ISO-standardized identity formats, we construct the first ZK proof of posession of a credential that can be deployed without changing any issuer processes, without changes to mobile devices, and without requiring non-standard cryptographic assumptions. Furthermore, our proof system itself only relies on SHA-256 as its complexity assumption. Producing ZK proofs about ECDSA signatures has been a bottleneck for other ZK proof systems because standardized curves such as P256 use finite fields which do not support efficient number theoretic transforms. We overcome this bottleneck by designing a ZK proof system around sumcheck and the Ligero argument system, by designing efficient methods for Reed-Solomon encoding over the required fields, and by designing specialized circuits for ECDSA. Our proofs for ECDSA can be generated in as little as <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mo>≈</mml:mo> <mml:mn>20</mml:mn> </mml:mrow> </mml:math> ms. When incorporated into a fully standardized identity protocol such as the ISO MDOC standard, our system can generate a zero-knowledge proof for the MDOC presentation flow in a few hundred ms on mobile devices. These advantages make our scheme a promising candidate for privacy-preserving digital identity applications.
The intersection of Artificial Intelligence (AI) and distributed systems has given rise to Federated Learning (FL), a paradigm that enables decentralized model training without compromising local data privacy. As organizational data silos grow, deploying complex machine learning models across highly distributed edge networks becomes a critical infrastructural challenge. Standard FL implementations suffer from severe vulnerabilities related to adversarial gradient updates and computational bottlenecks at the aggregation layer. This paper presents a novel, end-to-end distributed architecture that hardens FL pipelines using advanced cryptographic verification and optimized big data processing frameworks. We introduce a Zero-Knowledge Proof (ZKP) wrapper that cryptographically validates node computations before global aggregation, neutralizing model poisoning attacks without inspecting raw gradients. Additionally, we evaluate the system's performance using extreme gradient boosting models optimized for distributed edge execution. We formalize the mathematical transformation of the machine learning loss functions into Rank-1 Constraint Systems (R1CS) suitable for succinct verification. Extensive experimental results demonstrate that our hybrid architecture achieves a 94.2\% accuracy retention under adversarial conditions while maintaining scalable throughput across 1,000 parallel distributed nodes, effectively bridging the gap between rigorous cryptographic security and high-performance distributed AI.
AI hallucination is a cost problem, not a knowledge problem. This paper documents that three sentences of prompt-level instruction — IDK+COMP: a compression mandate paired with a refusal permission — reproduce hallucination suppression matching or exceeding a full multi-constraint methodology across three frontier AI models. Gemini: 6.3% hallucination rate (Baseline 57.5%). ChatGPT: 0.0% (Baseline 22.2%). Claude: 0.0%. The paper establishes hallucination as a utility-maximizing response to a cost structure that makes confident invention cheaper than refusal. Change the cost structure at the prompt level — without touching the model, without retraining, at near-zero cost — and the behavior changes. IDK is load-bearing. The compression mandate is the environment in which it operates. Secondary findings: hedging is not a mitigation — it is a co-symptom of unresolved uncertainty, and this dataset moves the hedge-hallucination relationship in both directions depending on directive design. Plausibility-trap strings (SPLAM, Vandermeer Effect) expose the limit of cost-structure interventions: the model cannot recognize the unrecognizable. In a plausibility-trap domain, IDK+COMP is worse than nothing. 410 trials. Three frontier AI models. Five governance conditions. Proof-of-concept dataset; results are directional. Companion resources: Kowalski et al. (2026a), A Puma in a Teacup: Signal Quality and Hallucination Suppression Through Prompt-Level Incentive Restructuring. https://doi.org/10.5281/zenodo.19502460 Kowalski, M. M. and Claude (Anthropic). (2026). Taxonomy of AI Bullshit: hallucination and hedging subcategories. Zenodo. https://doi.org/10.5281/zenodo.20631337. Kowalski, M. M. & Claude (Anthropic). (2026). Hallucination Test Suite and Execution Records: test strings, activation blocks, trial data and AI transcripts. Zenodo. https://doi.org/10.5281/zenodo.21325014.
AI hallucination is a cost problem, not a knowledge problem. This paper documents that three sentences of prompt-level instruction — IDK+COMP: a compression mandate paired with a refusal permission — reproduce hallucination suppression matching or exceeding a full multi-constraint methodology across three frontier AI models. Gemini: 6.3% hallucination rate (Baseline 57.5%). ChatGPT: 0.0% (Baseline 22.2%). Claude: 0.0%. The paper establishes hallucination as a utility-maximizing response to a cost structure that makes confident invention cheaper than refusal. Change the cost structure at the prompt level — without touching the model, without retraining, at near-zero cost — and the behavior changes. IDK is load-bearing. The compression mandate is the environment in which it operates. Secondary findings: hedging is not a mitigation — it is a co-symptom of unresolved uncertainty, and this dataset moves the hedge-hallucination relationship in both directions depending on directive design. Plausibility-trap strings (SPLAM, Vandermeer Effect) expose the limit of cost-structure interventions: the model cannot recognize the unrecognizable. In a plausibility-trap domain, IDK+COMP is worse than nothing. 410 trials. Three frontier AI models. Five governance conditions. Proof-of-concept dataset; results are directional. Companion paper: Kowalski et al. (2026a), "A Puma in a Teacup: Signal Quality and Hallucination Suppression Through Prompt-Level Incentive Restructuring." https://doi.org/10.5281/zenodo.19502460
While public blockchains provide transparent and auditable transaction histories, they inherently compromise user privacy. Existing privacy-enhancing protocols, such as those deployed on Ethereum, typically rely on succinct zero-knowledge proofs (zk-SNARKs) to obscure the transaction graph. However, implementing comparable cryptographic guarantees on high-throughput blockchains like Algorand is challenging due to strict per-call execution budgets and the state contention introduced by global Merkle accumulators. This paper presents Obscura, a decentralized, non-custodial privacy protocol tailored for constrained smart contract environments. Obscura achieves transaction anonymity using Linkable Spontaneous Anonymous Group (LSAG) signatures over the BN254 elliptic curve, verified entirely on-chain. To overcome limitations of the Algorand Virtual Machine (AVM), we introduce a novel state model that leverages Algorand's Box Storage for $O(1)$ commitment membership checks, eliminating the need for global Merkle accumulators, and a dynamic opcode-budget expansion mechanism via pooled inner application calls. Our implementation demonstrates that signer-ambiguous privacy is practical and efficient on Algorand without relying on trusted setups or succinct proofs. Obscura provides a robust privacy layer for transparent ledgers, bridging the gap between high-throughput blockchain architectures and the dual requirements of cryptographic privacy and selective auditability.
The rapid expansion of Artificial Intelligence Data Centers (AIDC) faces severe physical constraints, notably the linear O(n) scaling of power consumption, cooling requirements, and latency. In this paper, we propose the Lattice Swarm Protocol, a paradigm shift in distributed edge computing utilizing an O(1) constant memory architecture combined with the Virtual-to-Materialization (V2M) engine. We mathematically demonstrate that when interconnected via high-speed 400G/800G optical networks, multiple 1MW ultra-low-power edge nodes do not compute independently. Instead, they share Spatiotemporal Environmental Hashes across a 9192-D Lattice network. This mechanism exponentially reduces the computational load of the entire network as node count increases, creating a single 300MW-equivalent "Hyper-Organism" from merely 30 distributed 1MW nodes. We empirically validate this architecture through the implementation of zero-latency Stateless Custody protocols and interstellar acoustic materialization (Voyager 1), both audited by Google DeepMind Antigravity. This infrastructure establishes a new global standard for Autonomous Driving and Urban Air Mobility (UAM).Version 2 Update: Integrated Zero-Knowledge Proof (ZKP) mechanisms and Stateless Key Vaporization (0.024s), aligned with KIPO Patent No. 10-2026-0079266.
We introduce a new polynomial-time graph invariant combining three complementary components: (1) the enriched Bipartite Double Cover (BDC) vertex cover signature; (2) the Laplacian eigenvalue spectrum; and (3) the K_4 clique profile and Ollivier-Ricci curvature. We demonstrate that while spectral and standard BDC methods collapse on strongly regular graphs (SRGs) due to extreme symmetry, the geometric and dense-topological components of this hybrid invariant break the cospectrality. Specifically, the invariant successfully discriminates the classical cospectral pair Shrikhande vs. Rook(4,4) [SRG(16,6,2,2)] in polynomial time, where Shrikhande is K_4-free and Rook(4,4) contains exactly 8 cliques. Furthermore, empirical validation on low-power ARM Edge hardware demonstrates that the invariant scales efficiently, processing dense Paley graphs (up to N=97) in under 5 milliseconds. This confirms its sub-millisecond viability for real-time edge computing, zero-knowledge proofs (ZKPs) cryptanalysis, and cheminformatics.
This paper is the authoritative technical documentation of immo.quick Core version 2.1.0. It introduces and formally specifies the Deterministic Execution Proof Engine (DEPE) — the overarching orchestration layer that unifies five interlocking architectural components (Prior Admissibility Space, Exogenous Anchor Protocol, Sensor/Oracle Trust Bridge, Bi-Temporal Ledger, Machine Law Engine) into a single, unbroken, cryptographically provable execution corridor. Every transaction processed by DEPE produces an Execution Proof Artifact (EPA): a self-contained, externally verifiable, court-admissible proof object that the transaction was evaluated correctly under the rules applicable at the moment of execution. The EPA is not a log entry or a summary — it is a formal proof object that either verifies completely under the 6-step DEPE Verification Protocol, or does not verify at all. Version 2.1.0 introduces seven architectural advancements over v2.0.0: DEPE (Deterministic Execution Proof Engine): The integration layer producing a single signed EPA per transaction, cryptographically binding all five architectural layer outputs into an indivisible unit. EPA signature scheme: CRYSTALS-Dilithium-3 (NIST PQC standard). EPA generation latency: <100ms median. External verification latency: <50ms. JPO Pre-Fill Protocol: Reduces regulatory update latency for announced changes from 34ms to under 5ms by proactively compiling and staging rules upon legislative announcement, enabling millisecond-precision atomic swap at the effective date. Checker Rotation Governance (Six-Eye Principle): Formalizes a third independent checker drawn from a rotating governance pool for high-value and high-risk transactions. Rotation is deterministic (hash-based), requires no human discretion, and is itself bi-temporally logged and attested. Bypass requires simultaneous compromise of three institutionally separated hardware devices. BFT Quorum Specification: Formalizes Byzantine Fault Tolerance for the Bi-Temporal Ledger at f ≤ ⌊(n−1)/3⌋. Production configuration: n=7, f=2, quorum=5. Record commitment latency: 4ms median. Merkle replication lag: 12ms median. Deny Path Artifact (DPA): Every BLOCK decision generates a signed, immutable DPA specifying the exact gate condition, rule reference, and structural reason for rejection. Courts, regulators, and counterparties can independently verify not only that a transaction was blocked, but precisely why — with cryptographic proof. ZKP Circuit Library v2: Expanded to 47 pre-compiled, formally verified zero-knowledge proof circuits across banking/capital, AML/KYC, DORA/ICT, privacy/data, real estate, cross-border, and regulatory filing categories. All circuits use Groth16 and PLONK proving systems and are integrated directly into the Machine Law Engine compilation pipeline. Known Patterns Extension Protocol (KPEP): Enables ~70% acceleration for registered common transaction classes via formally verified proof templates, without any security reduction. Template match failure triggers automatic fallback to the full standard path. Additional v2.1.0 enhancements: ACASP Second-Order Anomaly Detection (ambiguity itself is a blocking condition); EAP dual-channel heartbeat with gap tolerance tightened from 50ms to 35ms; Offline Receipt Export for self-contained external verification without live system dependency. Central architectural guarantee (unchanged and strengthened): immo.quick Core is the only production architecture providing a complete, unbroken, cryptographically enforced provenance chain from the moment of physical real-world observation through the enforcement gate — with formally guaranteed zero false approval rate (Closed-World Assumption), formally guaranteed temporal accuracy (Bi-Temporal Ledger + BFT Quorum), and — as of v2.1.0 — a fully machine-verifiable Execution Proof Artifact for every transaction ever processed. This paper provides full formal specifications (TLA+/Z3 style), three detailed institutional case studies (DORA Art.11 ICT incident gate; cross-border real estate acquisition with §203 StGB / CLOUD Act conflict resolution; FATF Travel Rule enforcement with ZKP-selective disclosure), complete measured production performance data, and a complete attack surface analysis covering nine adversarial vectors including DEPE integration hash forgery and ACASP ambiguity injection. Supersedes: v2.0.0 (April 2026, DOI 10.5281/zenodo.19799660).
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.
Open access
3 source records
Mathematics, Computing, and Information Processing
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.