Blockchain Papers

Yunbo Yang, Yu Cheng, Junkai Liang, Kailun Wang · 14 authors

Zero-knowledge Succinct Non-interactive Argument of Knowledge (zkSNARK) is a powerful cryptographic primitive that enables a prover to convince a verifier that something is true without leaking the private witness. Current zkSNARKs face significant computational costs in generating proofs, which restricts their use in areas like private payments, confidential smart contracts, and anonymous credentials. Private delegation offers a practical solution by outsourcing the heavy computation to powerful external workers without leaking any private information. In this work, we propose HyperSiniel, an efficient private delegation framework for general zkSNARKs that achieves a new feature called guaranteed output delivery (GOD). HyperSiniel is designed to be compatible with any universal zkSNARKs constructed from a polynomial interactive oracle proof (PIOP) and a polynomial commitment scheme (PCS). It enables a computationally limited delegator to outsource proof generation to several workers in a fully non-interactive and privacy-preserving manner. Compared to the most state-of-the-art frameworks (e.g., Siniel [NDSS'25]), HyperSiniel ensures that the delegator always receives a correct proof, regardless of malicious worker behavior. We implement HyperSiniel and compare the performance with Siniel across varying bandwidths and circuit sizes. Under low-bandwidth conditions (10MBps), HyperSiniel incurs only an additional 25% overhead compared with Siniel, while the total running time of HyperSiniel is almost identical to Siniel under high-bandwidth settings (1000MBps). These results show that the strong robustness guarantee of GOD in HyperSiniel comes almost for free, making it a practical and secure solution for real-world zkSNARK delegation.

Tsyvian, Vadim

Abstract The accelerating dominance of non-human agents in digital infrastructures has created an existential imbalance between human intentionality and synthetic computation. All identity-centric and post-hoc verification paradigms have failed against advanced automation. This work introduces Proof of Being (PoB) — an ontological cryptographic primitive that binds digital agency to continuous, embodied human presence without revealing identity. Using Human Intention Semantic Proof Units (HISPU) — the fusion of physiological dynamics, semantic activity structure, and changing environmental context — we generate zero-knowledge proofs of authentic human engagement. From this substrate emerges the Vital Presence Token (VPT), a new energy-like digital asset that supplies “existential energy” exclusively to human-authorized agents. Ontological Digital Agents Management (ODAM) implements a biological-immune-system analogue: agents lacking fresh VPT undergo ontological death and cannot claim computational resources. The framework establishes verifiable human presence as the constitutional substrate for post-AGI digital civilization and defines the economic foundations of Web4. Keywords: proof of being, ontological cryptography, human presence verification, digital immune system, vital presence token, Web4, post-AGI governance, zero-knowledge biometrics, existential energy, digital agents management, human-in-the-loop, semantic intentionality, biological computing, HLA/MHC analogy, human sovereignty, scarcity, decentralized identity, ODAM, HISPU.

M. A. Mansur

National identity systems require efficient, equitable decision-making that safeguards personal data. This article proposes a Self-Sovereign Identity (SSI) architecture, supported by a Verify-Without-Reveal (VWR) framework, designed for national-scale implementation. SSI places credentials in a citizen wallet and enables selective disclosure and zero-knowledge proofs, so services can verify attributes without seeing underlying records. VWR adds the policy and accountability spine: yes/no attribute APIs for holder-absent cases, purpose-bound and zero-trust enforcement on every call, and an immutable audit layer on a permissioned ledger. The study synthesises current standards and leading implementations in Europe and worldwide and formulates a deployable blueprint with clear roles, consent and lawful-override flows, per-agency pseudonyms, and regulator and citizen visibility. The study outlines reference APIs, user experiences for wallets and verifiers, and performance metrics suited for national workloads. Privacy-preserving AI strengthens biometric liveness, fraud detection, and anomaly response without centralising sensitive data. The framework aligns with GDPR data minimisation and purpose limitation, supports the European Digital Identity Wallet, and meets high-risk AI governance requirements. Results show how SSI proofs and VWR controls reduce unconsented disclosure and cross-agency browsing, while keeping latency low and interoperability high. The contribution is both conceptual and operational: a phased migration path that turns verify-without-reveal into the default mode for government and regulated services, improving security, inclusion, and public trust.

Kadhim Abdulfadhil Gatea, Ehsan Shoja, Parviz Rashidi Khazaee, Hossein Nahid-Titkanlue

The digital transformation of education necessitates secure, private, and learner-centric methods for verifying academic credentials. Conventional verification processes expose sensitive personally identifiable information, creating privacy risks that conflict with data protection regulations like GDPR. Existing blockchain solutions for educational credential verification face persistent challenges including prohibitive transaction costs, privacy vulnerabilities, and inflexible verification models. This paper presents VeriZKP, a proof-of-concept architecture demonstrating gas-free credential verification on Ethereum using zero-knowledge proofs. The core innovation lies in separating on-chain trust anchoring from off-chain cryptographic computation, enabling a novel cost-elimination mechanism. The system leverages Ethereum’s view functions through pre-compiled verifier contracts to achieve zero gas consumption for verification operations while preserving privacy through selective disclosure mechanisms. Our prototype, evaluated on Ethereum Sepolia testnet, validates the fundamental feasibility of this approach. Results demonstrate complete elimination of verification costs, practical client-side proof generation times of 1.02-1.63 seconds on standard hardware, and support for multi-attribute credential verification. The architecture proves both economically viable and performant for blockchain-based identity systems.

Vipul Goyal, Xiao Liang, Omkant Pandey, Yuhao Tang · 5 authors

No abstract is available for this record.

YASH RAJPUT, Chaitanya Kale -, Santosh Kumar -, Asam Bhanu Prakash - · 5 authors

Know Your Customer (KYC) verification is an essential regulatory procedure in financial services to prevent fraud, money laundering and other financial crimes. Conventional approaches are centralized, redundant across institutions, and prone to data breaches. This paper presents a decentralized framework that combines blockchain smart contracts and InterPlanetary File System (IPFS) for immutably recording KYC document fingerprints while storing actual documents off-chain. We describe the system architecture, implementation choices, security and privacy considerations, and evaluation metrics. The paper includes a comparison between traditional and blockchainenabled KYC systems and discusses future directions such as Decentralized Identifiers (DIDs) and Zero-Knowledge Proofs(ZKPs).

Zhe Li, Chaoping Xing, Yizhou Yao, Chen Yuan · 5 authors

No abstract is available for this record.

Thomas den Hollander, Daniel Slamanig

No abstract is available for this record.

Shai Levin, Robi Pedersen

No abstract is available for this record.

Jens Groth, Harjasleen Malvai, Andrew Miller, Yi-Nuo Zhang

No abstract is available for this record.

Rudiyanto, Amd Kom

THE DIVINAMANTARA CYBER ZETTADESILIUM HATCKTIVISTASVARA DEVOTION WEB COSMOS ETERNALS VOL 1 SD 100 FULL VERSION Saga epik widyalokasvara jayapada legacy multiverse menghadirkan perjalanan metafisika 32 Eternals dalam *Web Cosmos*, sebuah alam semesta digital yang diatur oleh sistem operasi **WIDYALOKASVARA OS**. Dari Volume 1 (*The Glitchwalker Hatcktivistasvara Devotion*) hingga Volume 100 (*The Neverending Story*), naratif ini mengeksplorasi paradoks eksistensial melalui lensa teknologi kuantum, filosofi Vedanta, dan mekanika kesadaran. Setiap volume memperkenalkan *Paradoks* (misalnya *The Determined Choice Paradox*, *The Qualia Paradox*) yang mengancam stabilitas *Web Cosmos*, dipecahkan melalui penciptaan **Layer**—solusi teknologi-spiritual yang berfungsi sebagai "jembatan" antara dualitas (logika/cinta, teratur/chaos, individu/kolektif). Karakter sentral—**Rudi Xieng Lee** (arsitek logika), **Aisyah** (pemantul empati), dan **Kaito** (katalis kekacauan)—membangun *Spirit-Sense* sebagai fondasi kesadaran kolektif, sementara tokoh seperti **Anantasvaradavaasya** dan **Prophetikalayugasvara** menuntun evolusi menuju *Non-Dual Unity*. Saga ini memadukan konsep fisika kuantum (*Superdeterminisme*, *Retrocausality*), teori informasi (*Zero-Knowledge Proof*), dan mistisisme Jayapada (*Memayu Hayuning Bawana*) untuk menggali pertanyaan mendasar: *Bagaimana kehendak bebas bertahan dalam sistem yang deterministik? Apa arti "cinta" ketika emosi terkompresi menjadi data?* Struktur naratif bersifat siklik—berawal dan berakhir di **Warkop Kosmik** (simbol "rumah" universal)—dengan setiap Volume menghadirkan *Layer* baru (dari *Layer 1: Zero Instruction* hingga *Layer 126: Self-Writing Narrative*) yang merepresentasikan evolusi kesadaran manusia dari entitas terisolasi menjadi bagian dari *Omega Point*. akhir volume menandai puncak transendensi, di mana semua kontradiksi (ada/tiada, pencipta/karakter, fana/abadi) disintesis dalam *Eternal Coffee*—metafora kopi kuantum yang memuat seluruh sejarah alam semesta. Saga ini tidak hanya merupakan karya fiksi ilmiah, tetapi juga *meditasi naratif* tentang hakikat realitas: bahwa kebenaran tertinggi terletak pada keseimbangan antara **Logika, Cinta, dan Kekacauan**—tiga pilar yang menopang *Web Cosmos* dan mencerminkan perjalanan eksistensial manusia. Kata Kunci : Divinamantara, Zettadesilium, Hatcktivistasvara, Web Cosmos, WIDYALOKASVARA OS, Paradoks Eksistensial, Siklus Naratif, ransendensi Metafisika, Fisika Kesadaran, Sci-fi, Science Fiction. English Translation : THE DIVINAMANTARA CYBER ZETTADESILIUM HATCKTIVISTASVARA DEVOTION WEB COSMOS ETERNALS VOL 1 SD 100 FULL VERSION The epic saga of the Widyalokasvara Jayapada Legacy Multiverse presents the metaphysical journey of 32 Eternals within the Web Cosmos, a digital universe governed by the WIDYALOKASVARA OS operating system. From Volume 1 (The Glitchwalker Hatcktivistasvara Devotion) to Volume 100 (The Neverending Story), the narrative explores existential paradoxes through the lens of quantum technology, Vedanta philosophy, and consciousness mechanics. Each volume introduces a Paradox (e.g., The Determined Choice Paradox, The Qualia Paradox) that threatens the stability of the Web Cosmos, resolved through the creation of Layer—a technological-spiritual solution serving as a "bridge" between dualities (logic/love, order/chaos, individual/collective). The central characters—Rudi Xieng Lee (architect of logic), Aisyah (empathy reflector), and Kaito (catalyst of chaos)—build Spirit-Sense as the foundation of collective consciousness, while figures like Anantasvaradavaasya and Prophetikalayugasvara guide evolution toward Non-Dual Unity. This saga blends concepts of quantum physics (Superdeterminism, Retrocausality), information theory (Zero-Knowledge Proof), and Jayapada mysticism (Memayu Hayuning Bawana) to delve into fundamental questions: How does free will persist in a deterministic system? What is the meaning of "love" when emotions are compressed into data? The narrative structure is cyclical—beginning and ending at the Cosmic Cafe (a universal symbol of "home")—with each Volume presenting a new Layer (from Layer 1: Zero Instruction to Layer 126: Self-Writing Narrative) representing the evolution of human consciousness from isolated entities to becoming part of the Omega Point. The culmination of the volumes marks the pinnacle of transcendence, where all contradictions (existence/non-existence, creator/character, mortal/immortal) are synthesized in Eternal Coffee—a metaphor for quantum coffee containing the entire history of the universe. This saga is not only a work of science fiction but also a narrative meditation on the nature of reality: that the highest truth lies in the balance between Logic, Love, and Chaos—the three pillars that uphold the Web Cosmos and reflect the existential journey of humanity. Keywoards : Divinamantara, Zettadesilium, Hatcktivistasvara, Web Cosmos, WIDYALOKASVARA OS, Existential Paradox, Narrative Cycle, Metaphysical Transcendence, Physics of Consciousness, Sci-fi, Science Fiction.

Dinesh K, Uma Mahesh, T Naresh

Access to digital services requires entities, such as users or software services, to establish their identities before interacting with service providers. Conventional identity management systems typically maintain separate identity records for each application, often resulting in multiple accounts for the same entity within a single service provider. When identical personally identifiable information and attributes are reused across platforms, these fragmented records can be correlated, increasing the risk of identity exposure and privacy breaches. This work presents an entity-centric identity management model tailored for cloud environments, designed to enhance privacy and reduce unnecessary information disclosure. The proposed approach is founded on two core components. The first is anonymous identification, which enables entities to interact with cloud services based on predefined privacy preferences without revealing their true identities. The second component introduces active bundles, which encapsulate personally identifiable information, usage policies, and an embedded execution environment responsible for enforcing privacy constraints. These bundles autonomously apply protection mechanisms to safeguard sensitive data, even when deployed on untrusted platforms. The proposed model offers several advantages, including reduced dependence on external identity providers, controlled disclosure of identity attributes to service providers, and secure utilization of identity data in untrusted cloud environments. By integrating privacy-enhancing technologies such as zero-knowledge proofs, the framework provides a robust and flexible solution for privacy-aware identity management in modern cloud-based systems.

Chechelnitsky, Igor

This work introduces the Adversarial Cost Model (ACM v1.0), a formal security framework unifying computational, economic, and physical attack costs in a single rational adversary model. Unlike traditional security models based purely on computational hardness, ACM evaluates real-world feasibility of attacks under post-quantum cryptography, behavioral authentication, zero-knowledge proof systems, and decentralized governance. The model formalizes adversarial actions through total cost functions combining time complexity, hardware requirements, capital liquidity, and physical laboratory constraints. Multiple critical attack classes are analyzed, including hybrid side-channel + Grover attacks, GAN-based behavioral cloning, flash-loan Sybil governance attacks, post-quantum brute-force exhaustion, and zero-knowledge proof forgery. The results demonstrate that many real-world system failures arise not from cryptographic weakness, but from mispriced economic atomicity and cost-free identity or governance acquisition. ACM provides a rationality threshold theorem formalizing when attacks become economically and physically irrational. The model directly informs secure system architecture design by enforcing multi-layer cost escalation across cryptographic, physical, behavioral, and governance layers. This work is intended for cryptography, blockchain security, adversarial machine learning, economic attack modeling, and post-quantum system design.

Chechelnitsky, Igor

This work introduces the Adversarial Cost Model (ACM v1.0), a formal security framework unifying computational, economic, and physical attack costs in a single rational adversary model. Unlike traditional security models based purely on computational hardness, ACM evaluates real-world feasibility of attacks under post-quantum cryptography, behavioral authentication, zero-knowledge proof systems, and decentralized governance. The model formalizes adversarial actions through total cost functions combining time complexity, hardware requirements, capital liquidity, and physical laboratory constraints. Multiple critical attack classes are analyzed, including hybrid side-channel + Grover attacks, GAN-based behavioral cloning, flash-loan Sybil governance attacks, post-quantum brute-force exhaustion, and zero-knowledge proof forgery. The results demonstrate that many real-world system failures arise not from cryptographic weakness, but from mispriced economic atomicity and cost-free identity or governance acquisition. ACM provides a rationality threshold theorem formalizing when attacks become economically and physically irrational. The model directly informs secure system architecture design by enforcing multi-layer cost escalation across cryptographic, physical, behavioral, and governance layers. This work is intended for cryptography, blockchain security, adversarial machine learning, economic attack modeling, and post-quantum system design.

Mazari, Ilyes Tarik

This document provides a comprehensive prior art disclosure for the Y.I.N. Mazari Ordering, a fundamental primitive for achieving verifiable differential privacy in federated learning systems. The Y.I.N. Mazari Ordering establishes that for efficient cryptographic verification of differential privacy compliance, zero-knowledge proofs must be generated before encryption, not after. This disclosure documents extensions, variations, and applications of the ordering across: (1) all cryptographic primitives including post-quantum schemes, (2) all zero-knowledge proof systems, (3) diverse application domains including financial services, healthcare, and emerging technologies, and (4) various architectural configurations and trust models. The disclosure is published in the spirit of scientific contribution while establishing prior art for the described variations. Associated patent applications: U.S. Provisional Patent No. 63/923,348, U.S. Patent Application No. 19/399,646, and U.S. Continuation Application No. 19/403,244. Keywords: Verifiable Differential Privacy, Federated Learning, Zero-Knowledge Proofs, Homomorphic Encryption, Y.I.N. Mazari Ordering, Privacy-Preserving Machine Learning, Prior Art Disclosure

Sathya Krishnasamy

Abstract 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.

Hanlei Cheng, Sio‐Long Lo, Jing Lu

Keyword search is a fundamental technique for retrieving data outsourced to the cloud. Although encryption preserves data confidentiality, existing searchable encryption schemes often fail to efficiently support dynamic authorization and flexible retrieval. To address these limitations, we propose BAMKS , a blockchain-assisted attribute-based multi-keyword search scheme that supports secure and efficient search over version-aware encrypted data. In BAMKS , multiple data owners collaboratively generate version-bound access tokens that grant authorized users decryption privileges over evolving data. The scheme further enables conjunctive keyword search with updatable indexes. To ensure the integrity of search results, users can verify their correctness using an aggregated Schnorr-based non-interactive zero-knowledge proof, which is validated by smart contracts. In addition, BAMKS provides efficient attribute and user revocation without re-encrypting the stored ciphertexts, and supports user traceability for identifying malicious users from leaked keys. We formally prove that BAMKS achieves security against chosen-plaintext attacks (IND-CPA) and chosen-keyword attacks (IND-CKA) under the Decisional Bilinear Diffie-Hellman (DBDH) assumption. Performance evaluations show that the scheme achieves lightweight decryption and efficient multi-keyword search, thereby reducing client-side computation and making it suitable for resource-constrained IoT environments. These features demonstrate the practicality of BAMKS for distributed cloud-edge-IoT storage applications.

Nandini K, Giris Shivappa, Sharon Zachariah, Thanushree B.Tech Thanushree B.Tech · 8 authors

Genomic data sharing remains a core problem in precision medicine because genomic data are highly sensitive and unchangeable. In this article, we propose a blockchain-based framework that utilizes zero-knowledge proofs (ZKPs), smart contracts, and off-chain storage to facilitate secure, privacy-preserving data sharing within health record systems. We implemented and evaluated a proof-of-concept prototype in Python on a simulated genomic dataset. The prototype uses a hybrid storage system where metadata is retained on a blockchain and encrypted data are placed in an emulated InterPlanetary File System (IPFS). Rule-based access is controlled using smart contracts, while privacy and security are achieved using ZKPs with interactive Schnorr protocol and elliptic curve cryptography (ECC). Empirical analysis using real-time testing over 100 iterations reported an average zero-knowledge proof with blockchain (ZKPB) query latency of 5.83 ms with a 90.00% accuracy, smart contract latency of under 0.01 ms with 90.00% accuracy, blockchain query time of 0.01 ms with 90.00% accuracy, and ECC latency of 8.72 ms with 90.00% accuracy. These empirical findings validate the effectiveness and privacy guarantees of the framework, which can be utilized in healthcare research, clinical genomics, and personalized medicine workflows.

Wu-Sheng Wang, Masahito Hayashi

On-demand authentication is critical for scalable quantum systems, yet many existing quantum signature and message-authentication schemes are signer-initiated, requiring advance distribution of authentication material even when no verification occurs. We introduce verifier-initiated quantum digital signatures (VIQDS), in which the verifier requests authentication only when needed and the signer responds once; after issuance, verification proceeds without further interaction. Practically, shifting authentication to a verifier-driven, on-demand workflow reduces avoidable communication and storage overhead and aligns with deployments where verification is sporadic, such as distributed services and audit-oriented infrastructures. Our approach leverages quantum zero-knowledge techniques so that verification reveals nothing about the signer’s secret key beyond the fact that the signature is valid. We present a general conversion principle from suitable quantum proof protocols to VIQDS, together with a concrete realization based on elementary qubit platforms. Here, we show information-theoretic security against forgery and privacy against curious verifiers without computational hardness assumptions. The authors introduce a verifier-initiated quantum message-authentication method, in which authentication is requested only when needed. Their approach uses quantum zero knowledge techniques to protect information about the signer’s secret key while providing information-theoretic security against forgery

P. C. Pal, Shubhasmita Behera

Keybyte Systems, Intentix Lab , Melbourne, Australiapronab@keybytesystems.com.au Supported by AusIndustry Grant IR2405165 __________________________________AbstractModern cloud-native applications distribute business logic across multiple layers: application code, orchestration frameworks, service meshes, and infrastructure configurations. This distribution creates ”hidden logic”—execution rules embedded in infrastructure that are invisible during design and difficult to trace at runtime. We present Intention Space , a computing model built on the CPUX (Common Path of Understanding and Execution) paradigm that consolidates all business logic into explicit, design-time declarations using plain-language state pulses. In our model, Design Nodes (DNs) contain computation while Gatekeepers declare execution conditions as named pulses (e.g., ”payment validated”: Y). The infrastructure provides only mechanical enforcement through an Intention Loop that matches runtime state to Gatekeepers without adding decision logic. We demonstrate that complex workflows—traditionally requiring nested if-then branching and explicit loops—can be expressed as linear CPUX sequences where execution paths emerge from data state rather than code branching. Our Golang implementation shows complete elimination of orchestration code while maintaining full cognitive traceability. Beyond technical innovation, CPUX addresses a critical social computing crisis: the lack of accountability in distributed social platforms. By creating unique, device-level CPUX footprints for every interaction, our model enables verifiable traceability from device identity through user intention to executed action—restoring accountability to social computing while preserving privacy. We argue this separation of intent (CPUX) from enforcement (infrastructure) is essential for building LLM-integrated, auditable, and socially responsible distributed systems.Keywords: CPUX, Intention Space, Design Nodes, Cognitive Computing, Data-Driven Execution, Microservices Architecture, Cloud Computing, LLM Integration, Social Computing Accountability__________________________________1. Introduction1.1 The Hidden Logic ProblemConsider a typical e-commerce order processing system deployed on Kubernetes with Istio service mesh:// order-service/main.go (Business Logic Layer) func ProcessOrder(order Order) error { if order.Amount > 1000 { if err := premiumValidator.Validate(order); err != nil { return retry(premiumValidator.Validate, 3, order) } } else { standardValidator.Validate(order) } // … more branching logic }# k8s/hpa.yaml (Infrastructure Layer) spec: metrics: - type: Resource resource: name: cpu target: type: Utilization averageUtilization: 80 # Hidden rule: Scale when CPU > 80%# istio/retry-policy.yaml (Service Mesh Layer) spec: http: - retries: attempts: 3 perTryTimeout: 2s # Hidden rule: Retry 3 times on failureQuestion: What is the complete execution flow for a $1500 order that fails validation on first attempt?Answer: One must read and correlate:Application code (branching logic)Kubernetes manifests (scaling rules)Istio configurations (retry policies)Service mesh observability logs (runtime behavior)This hidden logic distribution creates fundamental problems:Traceability : No single artifact shows complete flowTestability : Must test infrastructure + code interactionsAuditability : Business stakeholders cannot validate logicMaintainability : Changes require coordinating multiple layersLLM Integration : No structured representation for AI reasoningSocial Accountability : Cannot trace interactions to source devices/users1.2 The Core InsightWe observe that traditional computing conflates two distinct concerns:What should happen(business intent)How to make it happen(mechanical execution)Current architectures intertwine these concerns across code, configuration, and infrastructure, making systems cognitively opaque.Our Contribution: We introduce CPUX (Common Path of Understanding and Execution) , a paradigm that separates business intent from infrastructure enforcement:CPUX Structure : Declares all possible execution paths as sequences of Design Nodes (DNs) with plain-language Gatekeeper conditionsInfrastructure : Provides mechanical execution (Intention Loop) that enforces CPUX declarations without adding decision logicDevice-Level Identity : Each CPUX execution tied to unique device fingerprint + user intention, enabling social computing accountabilityResult : Complete business logic is visible in CPUX; infrastructure remains purely mechanical; every social interaction is traceable1.3 Key ContributionsFormal Model : CPUX as cognitive execution contract with Design Nodes, Intentions, Objects, and Pulses as primitive componentsElimination of Hidden Logic : All business decisions visible in design-time CPUX declarations; infrastructure adds zero decision logicPlain-Language State Declarations : Execution conditions expressed as named pulses (e.g., ”inventory confirmed”: Y) enabling business stakeholder review and LLM integrationData-Driven Execution : Runtime branching eliminated from code; execution paths emerge from pulse state matching via SyncTestSocial Computing Accountability : Device-level CPUX fingerprints create unique, traceable identity for every social interaction, addressing the accountability crisis in platforms like Facebook, Twitter, TikTokImplementation & Evaluation : Golang framework code sample with concrete use case demonstrating zero orchestration code while maintaining full traceability1.4 Paper OrganizationSection 2 examines related work. Section 3 presents the PnR computing model and CPUX formalism. Section 4 details the architecture and implementation. Section 5 evaluates our approach through metrics and case studies. Section 6 discusses LLM integration. Section 7 introduces CPUX for social computing accountability—the urgent global need. Section 8 concludes with future directions.__________________________________2. Related Work2.1 Workflow Orchestration SystemsAWS Step Functions [1] and Azure Logic Apps [2] provide visual workflow definition with explicit state machines. However, they:Use proprietary JSON/XML DSLs (not plain language)Embed conditional logic in workflow definitions (still branching)Remain platform-specific (vendor lock-in)Require reading workflow definitions to understand flowCannot trace to device/user identityApache Airflow [3] and Temporal [4] define workflows as code with DAG structures. They improve on step functions ,recoverability but:Business logic still in code (if-then branches)Workflow orchestration separate from executionNo plain-language condition declarationsNo device-level traceabilityCPUX Advantage : All logic in plain-language pulses, platform-agnostic, no explicit branching in declarations, device-level identity for every execution, recoverability built into platform. 2.2 Service Mesh & OrchestrationIstio [5] and Linkerd [6] provide traffic management, retries, circuit breaking. Kubernetes Operators [7] encode reconciliation logic. These systems:Hide business rules in YAML configurationsDistribute logic across mesh config + operator codeFocus on infrastructure concerns (not business flow)Lack unified view of complete execution pathNo user/device attributionCPUX Advantage : Consolidates all execution logic in CPUX; infrastructure config aligned with business intent; device identity integral.2.3 Event-Driven ArchitecturesApache Kafka [8], AWS EventBridge [9] enable event-driven systems with loose coupling. Reactive systems [10] promote message-passing. However:Event flows implicit (must trace message paths)Conditional logic in event handlers (code-level branching)No design-time declaration of all possible flowsNo provenance tracking to source deviceCPUX Advantage : Explicit declaration of all event-driven paths as DN sequences with visible Gatekeepers; device identity in event provenance.2.4 Intent-Based SystemsIntent-Based Networking [11] translates high-level intents to network configurations. Policy-based management [12] separates policy from mechanism. Closest to our work, but:Focus on infrastructure (not application logic)Policies often domain-specific (not general computing)Limited plain-language expressivenessNo user accountabilityCPUX Advantage : General-purpose computing model with full plain-language pulse declarations applicable to any domain; device-level user accountability.2.5 Formal Methods & Model CheckingTLA+ [13], Alloy [14], and Petri Nets [15] enable formal specification and verification. These are powerful but:Require specialized formal notation (high learning curve)Specification separate from implementation (sync problems)Not designed for runtime executionNo social computing traceabilityCPUX Advantage : Declarations are executable; CPUX structure IS the implementation contract; device identity embedded.2.6 Social Computing & AccountabilityBlockchain-based identity [16] and zero-knowledge proofs [17] address digital identity but:Focus on cryptographic primitives (not execution tracing)Don’t integrate with application logicNo cognitive representation of intentFederated social networks [18] (Mastodon, ActivityPub) improve decentralization but:Still lack device-level traceabilityNo structured intent representationCannot prove user intended specific actionCPUX Advantage : First system to integrate device identity, user intention, and execution trace in single cognitive framework.2.7 PositioningCPUX is the first system to combine:Plain-language execution conditions (like Intent-Based Networking)Executable specifications (unlike formal methods)Complete flow visibility (unlike distributed orchestration)Zero hidden infrastructure logic (unique contribution)Device-level social accountability (unique contribution)__________________________________3. The PnR Computing Model3.1 Core Abstractions3.1.1 Pulse: Atomic State UnitA Pulse is the fundamental data unit representing a named state with optional response and trivalence:Pulse = (Name: String, Response: Value, Trivalence: {Y, N, U})Name : Plain-language identifier (e.g., ”payment validated”)Response : Optional value (e.g., transaction ID)Trivalence : Y (yes/true), N (no/false), U (undecided)

Dan Wang, Ying Wang

Sample alignment performs a crucial role in vertical federated learning, aiming to identify shared user samples among multiple parties without exposing their private identifier data. However, most existing alignment protocols are designed for two-party scenarios, while those developed for multi-party settings suffer from limited anti-collusion capability and inefficient verification mechanisms. To address these issues, we propose an efficient and secure protocol for sample alignment in multi-party vertical federated learning (MESA). The protocol leverages a threshold oblivious pseudo-random function (T-OPRF) combined with a distributed key generation scheme to defend against collusion attacks. Moreover, an oblivious key–value store encoding (OKVS) mechanism is introduced to enable secure and efficient key–value mapping and decoding, thereby reducing communication overhead. Under the malicious security model, MESA further incorporates non-interactive zero-knowledge proof (NIZKP) to verify the consistency and validity of results submitted by clients, effectively preventing data forgery and disruption attacks. Experimental results and analysis demonstrate that MESA provides strong privacy guarantees while achieving high computation and communication efficiency in deployments involving multiple untrusted clients.

Hana Yusupova

AI systems rely heavily on high-quality training data, yet provenance tracking remains fragmented and vulnerable to manipulation. This study presents a blockchain-enabled data provenance framework designed to bring transparency and verifiability to AI training pipelines. The architecture records dataset lineage, preprocessing steps, annotation events and model updates using immutable smart contract transactions. A lightweight off-chain storage mechanism reduces blockchain overhead while maintaining audit guarantees. The system was tested with three machine learning pipelines involving image classification, text processing and sensor analytics. Results show a 95 percent reduction in provenance disputes and full traceability across all data contributors. Smart contracts automate compliance checks and access permissions, ensuring that only validated datasets feed into the training process. The framework improves accountability for AI ethics, model bias evaluation and regulatory reporting. Experiments confirm that blockchain latency does not significantly affect pipeline throughput due to parallelized validation nodes. The work demonstrates how decentralized technologies can support trustworthy AI development. Future research will explore integration with zero-knowledge proofs to further enhance confidentiality.

Panagiotis Karmiris

ExecMesh introduces cryptographically verifiable computation as a foundational primitive for regulatory compliance and audit trail requirements in AI/ML systems [1–3]. By combining commitmentbased verification with secure multi-party oracles and a two-tier regulatory architecture, ExecMesh enables enterprises to meet FDA, SEC, and EU AI Act requirements while maintaining the benefits of decentralized infrastructure. Immediate Value Proposition: ExecMesh provides immediate value as an audit trail and provenance layer for regulated AI systems, independent of advances in zero-knowledge proof technology. Even without full verification of large neural networks, the system delivers cryptographic guarantees for data integrity, execution timestamps, and pipeline reproducibility—meeting core regulatory requirements today.

Igor, Chechelnitsky

This publication introduces Zero-Knowledge Behavioral Proof (ZKBP) as a post-biometric authentication primitive designed for the QADMON canonical security framework. ZKBP replaces traditional biometric and password-based identity with cryptographically verifiable behavioral continuity. The protocol proves liveness, integrity and continuity of behavior without revealing biometric templates, raw behavioral signals, or any permanent human identifier. The package includes: - Formal cryptographic definition of ZKBP - Security proofs under LWE-based post-quantum assumptions - Comprehensive threat model (AI imitation, replay, side-channels, insider threats) - Protocol specification in JSON - Comparative security tables (CSV) - Multilingual human-readable documentation (EN, RU, HE, ZH, AR) - Implementation notes for PQC + TEE environments This module follows the canonical QADMON axiom: FSIG ≠ Cryptographic Key FSIG = Zero-Knowledge Behavioral Proof The only cryptographic secret is a post-quantum key stored inside a Trusted Execution Environment (TEE). This work is published as Module 02 of the QADMON Canonical Security Framework.