K. Sundara Krishnan, R. Chithra Devi, Christo Ananth, D. Easwaramoorthy · 8 authors
E-commerce platforms incorporate reviews and reputation systems, allowing retailers and customers to manage and track their financial transactions. Consequently, it is crucial to design a reliable reputation system for the e-commerce environment, as it faces well-documented threats, including sybil attacks, feedback collusion, impersonation, review tampering, and whitewashing attacks. Current centralized systems are vulnerable to impersonation attacks, feedback manipulation, and lack automated verification against collusion-based reputation distortion. These unwanted ratings and reviews are highly correlated with abnormal cyber-attacks that damage both seller reputations and buyer experiences. To address these challenges, we propose a Blockchain-based Two-Level E-Commerce Trustable Reputation Framework (BTL-ETRF) utilizing deep learning-embedded transformers and redactable blockchain systems. Initially, we implement Multi-Factor Authentication for e-commerce users, utilizing three factors: PIN, OTP, and biometric fingerprint, to mitigate impersonation attacks. Only authenticated users are allowed to proceed to the reputation verification stage, where the proposed work considers five major metrics to classify user reputation using the Residual Dilated Convolution Transformer. To automate the reputation verification process, we design and employ two smart contracts, the Authentication Smart Contract and the Reputation Smart Contract which trigger automated actions based on the BTL-ETRF results. All transactions include reputation classification, and triggered actions are stored in the redactable blockchain, which can modify the stored transactions if needed. Finally, we demonstrate the performance of the proposed BTL-ETRF using Python and Ethereum Solidity, and conduct a formal analysis that shows the proposed model outperforms the compared works.
The Fifth Industrial Revolution (Industry 5.0) foregrounds human–machine collaboration, sustainability, and resilience as organizing principles for next-generation cyber-physical systems. Yet the identity and access management (IAM) architectures inherited from Industry 4.0 remain perimeter-centric, policy-static, and blind to the behavioral dynamics of human–AI teaming. This paper introduces the Human-Centric Zero Trust Identity Architecture (HC-ZTIA), a novel framework that repositions identity as the adaptive control plane for Industry 5.0 environments. HC-ZTIA integrates three mutually reinforcing innovations: (1) a Joint Embedding Predictive Architecture (JEPA)-driven Behavioral Identity Assurance Engine (BIAE) that learns abstract world models of operator and machine-agent behavior to perform continuous, context-aware identity verification without relying on raw biometric surveillance; (2) a Privacy-Preserving Adaptive Authorization Protocol (PP-AAP) employing zero-knowledge proofs and federated policy evaluation to enforce least-privilege access across human, non-human, and hybrid identity classes while satisfying data-minimization mandates; and (3) a Resilience-Oriented Trust Degradation Model (RO-TDM) that guarantees fail-safe identity governance under adversarial, degraded, or disconnected operating conditions characteristic of operational technology (OT) and critical infrastructure. The framework is grounded in the Agile-Infused Design Science Research Methodology (A-DSRM) and formally extends NIST SP 800-207 and the CISA Zero Trust Maturity Model by addressing five identified gaps in human-centric identity governance. We present the formal system model, threat model, architectural specification, and a multi-scenario evaluation spanning energy-sector OT, smart manufacturing, and vehicle-to-everything (V2X) environments. Simulation results, validated through Monte Carlo trials with 95% confidence intervals, demonstrate that HC-ZTIA reduces identity-related breach exposure by 73.2% (±4.1%) while maintaining sub-200 ms authorization latency, offering a principled bridge between Zero Trust rigor and Industry 5.0 human-centricity.
Enterprise identity systems can authenticate workloads, credentials, and attested platforms, but they do not close the composition layer where runtime model identity enters authorization. A token can verify that a service is running in a trusted environment, that its credentials are valid, and that its actions are authorized — without ever establishing which neural network is actually computing. When model identity evidence is inserted into standard authorization flows, new security properties emerge that are not inherited from the underlying protocols and must be formally established rather than presumed. This paper presents a live integration architecture for model-identity attestations in JWT and SPIFFE-style token flows, grounded in real measurements from six neural networks executed inside an NVIDIA H100 Confidential Computing enclave. It formally verifies four composition properties — non-separability, temporal binding, issuer authenticity, and reference integrity — across three Coq proof files with zero unfinished proof obligations. Every remaining trust dependency is explicitly named, traced to an integration control, and paired with a concrete falsification witness. The result is a formally hardened composition layer where no security property is left implicit and no assumption is left silent. Supplementary Material This paper is accompanied by three Coq proof files — ComposableIdentity.v, IssuerAuthenticity.v, and ReferenceIntegrity.v — that formally verify the four composition properties described in §§4–6: non-separability, temporal binding necessity, issuer authenticity, and reference integrity. Together the files prove thirteen theorems from eleven named axioms, each paired with a concrete falsification witness and an integration control. No file contains unresolved obligations (Admitted), and all three compile cleanly under the Rocq Prover 9.1.1 (the current release of the Coq proof assistant, compiled with OCaml 5.4.0). They are available for download as supplementary files attached to this record. The Neural Network Identity Series — Mathematical foundations, empirical validation, and governance frameworks for verifying which model is running Newest addition: Technical Note: The Disappearing Window — AI Logprob Access Withdrawal and the Structural Verifiability of Frontier Model Contracts (DOI: 10.5281/zenodo.20362098) Paper 1: The δ-Gene: Inference-Time Physical Unclonable Functions from Architecture-Invariant Output Geometry (DOI: 10.5281/zenodo.18704275) Paper 2: Template-Based Endpoint Verification via Logprob Order-Statistic Geometry (DOI: 10.5281/zenodo.18776711) Paper 3: The Geometry of Model Theft: Distillation Forensics, Adversarial Erasure, and the Illusion of Spoofing (DOI: 10.5281/zenodo.18818608) Paper 4: Provenance Generalization and Verification Scaling for Neural Network Forensics (DOI: 10.5281/zenodo.18872071) Paper 5: Beneath the Character: The Structural Identity of Neural Networks — Mathematical Evidence for a Non-Narrative Layer of AI Identity (DOI: 10.5281/zenodo.18907292) Paper 6: Which Model Is Running?: Structural Identity as a Prerequisite for Trustworthy Zero-Knowledge Machine Learning (DOI: 10.5281/zenodo.19008116) Paper 7: The Deformation Laws of Neural Identity (DOI: 10.5281/zenodo.19055966) Paper 8: What Counts as Proof? — Admissible Evidence for Neural Network Identity Claims (DOI: 10.5281/zenodo.19058540) Paper 9: Composable Model Identity — Formal Hardening of Structural Attestations in the Enterprise Identity Stack (DOI: 10.5281/zenodo.19099911) Paper 10:Where Identity Comes From: Path Sensitivity and Endpoint Underdetermination in Neural Network Training (DOI: 10.5281/zenodo.19118807) Paper 11: Post-Hoc Disclosure Is Not Runtime Proof: Model Identity at Frontier Scale (DOI: 10.5281/zenodo.19216634) Paper 12: Family-Dependent Response to Reasoning Distillation Across Structural and Functional Identity Layers (DOI: 10.5281/zenodo.19298857) Paper 13: Safety-Alignment Removal as a Model-Identity Failure — Structural Evidence from Published Weight-Level Mutation Checkpoints (DOI: 10.5281/zenodo.19383019) Technical Note: Agent Identity Is Not Model Identity (DOI: 10.5281/zenodo.19240883) Technical Note: Gap Invariance: Why PPP Measurements Are Domain-Independent by Construction (DOI: 10.5281/zenodo.19275524) Technical Note: Measured Model Substitution Under Valid Agent Credentials (DOI: 10.5281/zenodo.19342848) Technical Note: Artifact Identity Is Not Runtime Identity — Trustfall Lite and the Boundary of File-Level Model Verification (DOI: 10.5281/zenodo.20019127) Formal Verification Stack for Neural Network Structural Identity (IT-PUF Coq Proofs) (DOI: 10.5281/zenodo.18930621) Copyright (c) 2026 Anthony Ray Coslett / Fall Risk AI, LLC. All Rights Reserved. Confidential and Proprietary. Patent Pending (Applications 63/982,893, 63/990,487, 63/996,680, 64/003,244).
In decentralized web applications, users face an inherent conflict between public verifiability and personal privacy. To participate in regulated on-chain services, users must currently disclose sensitive identity documents to centralized intermediaries, permanently linking real-world identities to public transaction histories. This binary choice between total privacy loss or total exclusion strips users of agency and exposes them to persistent surveillance. In this work, we introduce a Selective Disclosure Framework designed to restore user sovereignty by decoupling eligibility verification from identity revelation. We present ZK-Compliance, a prototype that leverages browser-based zero-knowledge proofs to shift the interaction model, enabling users to prove specific attributes (e.g., "I am over 18") locally without revealing the underlying data. We implement a user-governed Grant, Verify, Revoke lifecycle that transforms the user's mental model of compliance from a permanent data handover into a dynamic, revocable authorization session. Our evaluation shows that client-side proof generation takes under 200ms, enabling a seamless interactive experience on commodity hardware. This work provides early evidence that regulatory compliance need not come at the cost of user privacy or autonomy.
Cross-chain technology is the key to solving the “data silo” problem in medical blockchain systems. However, it is difficult for existing cross-chain consensus mechanisms to meet the high standards of data security and consensus efficiency in medical scenarios. Therefore, this paper proposes a medical cross-chain Delegated proof of stake consensus(DPoS) scheme that integrates reputation and contribution evaluation. First, a dynamic reputation evaluation model was constructed, and the historical behaviour and communication quality of nodes were incorporated into the evaluation system, thereby mitigating the risk of centralization caused by the excessive reliance on the number of coins held in the DPoS consensus. Second, a hybrid random block generation mechanism combining the multiparty coin-tossing protocol and the secure shuffling algorithm was proposed. By collaboratively generating a verifiable global random seed and uniformly and randomly shuffling the candidate node sequence, the predictability of the block generation order was eliminated. Finally, a two-layer incentive architecture based on the Shapley value was proposed. Fine-grained contribution assessment mechanisms were established at both the candidate node layer and the voting node layer, making the reward distribution more equitable, enhancing the enthusiasm of nodes for voting and improving the consensus efficiency. Theoretical analysis and experimental results show that compared with the DPoS scheme, the proposed scheme improves the throughput by approximately 30% and reduces the average latency by approximately 50%. Compared with existing similar schemes, this scheme also has significant advantages in terms of reputation calculation overhead and malicious node elimination and can provide efficient and reliable consensus support for cross-chain scenarios in the medical field.
Abstract: This paper introduces an innovative access control architecture based on a dual-blockchain framework that distinctly separates access management from data storage to enhance system security, scalability, and privacy. Architecture employs a primary blockchain to manage user authentication and enforce dynamic, fine-grained permissions through smart contracts. In parallel, a secondary, isolated blockchain is used exclusively for storing sensitive data, which can only be accessed following successful authorization on the primary chain. To ensure data integrity and tamper resistance, the system utilizes the SHA-256 cryptographic hash function for securing access logs and verifying data authenticity across both blockchains. The two chains are securely interconnected using Hyperledger YUI, which facilitates reliable inter-chain communication while maintaining a decentralized structure. A proof-of-concept implementation using Ethereum-based blockchains demonstrates the system's capability to enforce secure, dynamic access controls across chains. Overall, the proposed architecture overcomes key limitations of conventional blockchain systems by enhancing modularity, strengthening governance, and providing a robust, adaptable framework suitable for data-sensitive applications requiring strict regulatory compliance.
Tourism relies on central review platforms which produces three major systemic issues that include fake content, unclear moderation activities and inadequate compensation systems for authentic consumer contributions. TrustChain resolves industry review challenges using a blockchain formation that combines Layer-2 scaling solutions with zero-knowledge proofs (ZKPs) and tokenized governance system. The transaction cost reductions are huge following the implementation of a Proof-of-Stake consensus system on the Polygon-based architecture although the system maintains confirmation times shorter than 2 seconds. The implementation of Self-Sovereign Identity framework alongside transaction-linking smart contracts maintains highly accurate review authenticity in prototype evaluations through TripAdvisor datasets. Through its DAO governance structure users can verify review authenticity by using multi-signature checks which resolve all major disputes in less than one day. The integration of IPFS for multimedia storage generates an 83% decline in blockchain bloat that does not affect cryptographic security.
The medical systems are becoming challenged by the issues associated with the secure verification of patient identities, privacy-protecting access control, and dynamic consent management of Electronic Health Records (EHRs). Conventional centralized designs infringe on patient-centered autonomy, have poor identity management, and put sensitive information at the risk of inaccessible information. The paper introduces a proposal to develop a decentralized and privacy preserving mechanism of access control using blockchain-enabled Self-Sovereign Identity (SSI), as proposing a combination of verifiable credentials (VCs), smart contracts, and zero-knowledge proofs (ZKPs). The proposed Consent-Driven Decentralized Identity Verification Algorithm (CD-DIVA) enables the patient to create decentralised identities, issue tokens of consent, and dynamically assign or remove access rights without having to involve third-party authorities. Smart contracts enable the conjurant enforcement of various consent terms and offer an inauditable audit trail and ZKPs grant healthcare providers with the ability to demonstrate their authority without revealing sensitive information. Experimental assessments show the framework to be efficient in minimizing the access latency, eliminating unauthorized disclosures and providing effective interoperability of heterogeneous healthcare systems. This contribution will be a complement to the current blockchain-based healthcare solutions since it helps adopt a patient-centric, tamper-proof, and privacy-preserving healthcare ecosystem by bridging the access control and trust gap in such systems.
We present APIS v2.0 (Agent Passport Issuance Standard), a cryptographic identity framework for autonomous AI agents operating across organizational boundaries and agentic frameworks. APIS v2.0 defines a credential chain grounded in legal mandate doctrine, hardware trust anchors (TPM 2.0), and DNS-anchored identity for cloud-hosted agents. Each agent receives a realm-scoped Decentralized Identifier (DID) and a signed Passport JWT binding the agent to a named principal, a scoped mandate, and a verifiable machine identity. The framework introduces a tiered trust model accommodating physical TPM (Tier 1) through DNS-registered identity (Tier 2.5), enabling CMMC Level 2 compliance for AI agent operations. We describe the APIS-APP provisioning protocol — an ACME-equivalent automated passport issuance mechanism — and demonstrate interoperability across OpenHands, Claude Code, Codex, and custom agent frameworks. A reference implementation is available at passportalliance.org.
Every standard signature scheme enforces one property: only the key holdercan sign. What the key holder signs is unconstrained. Policy enforcement-- spending limits, rate limits, access control -- lives in smartcontracts, middleware, or governance: layers that can be upgraded,bypassed, or exploited. We call this the software-layer assumption:compliance holds only if the enforcing code is correct and unmodified. We eliminate this assumption. We introduce behavior-bound signatures(BBS), in which a policy constraint delta(x) < epsilon is committed atkey generation and enforced inside the signature's zero-knowledge proof.If the action violates the policy, the ZK constraint system isunsatisfiable -- no witness, no proof, no signature. This is not asoftware check. It is a mathematical impossibility. No software canoverride. Unlike policy-based signatures (where an authority imposes policy onsigners), BBS is self-committed: the signer binds their own futurebehavior at key generation, and even the signer cannot later violate orrevoke this commitment. We formalize this as policy-soundness (PS-CMA), a security modelstrictly stronger than EUF-CMA, and prove it under standard assumptions(Pedersen binding, Poseidon CR, ZK knowledge soundness). From thissingle primitive, five independent consequences follow -- not as separatedesigns, but as necessary implications of one cryptographic root: (A) Compliance safety under f <= n-1 Byzantine faults, decoupled from honest-quorum assumptions.(B) O(1) verification and audit via a single ZK check and Pedersen homomorphic aggregation.(C) Elimination of the virtual-machine execution layer for policy-constrained transactions.(D) A gasless ledger: branch C removes metering, while ZK-encoded rate limits make spam mathematically nonexistent.(E) The first cryptographic guarantee that a compromised autonomous AI agent cannot exceed its authorized behavioral envelope. Moreover, the zero-knowledge property ensures that complianceverification reveals neither the signer's identity nor the transactionparameters -- achieving regulatory compliance without identitydisclosure, complementary to existing ZK-KYC frameworks that verifystatic identity attributes.
Rosa Pericàs Gornals, M. Magdalena Payeras Capellà, Victor Garcia Font, M. Puigserver · 5 authors
The exchange of non-fungible tokens (NFTs) traditionally occurs on centralized NFT marketplaces, which often wield significant control over transactions, as the imposition of restrictions and fees. Additionally, the current NFT standard (ERC-721) lacks certain functionalities that hinder the seamless direct exchange of NFTs between owners. This article introduces a novel protocol that eliminates the need for an intermediary marketplace, as well as their intermediary smart contract or escrow contract, facilitating a fair exchange of NFTs as collectibles. The protocol is represented by an extension of the ERC-721 called Exchangeable NFTs (ExNFTs), which introduces the necessary functionalities to enable direct NFT exchanges. We analyze the limitations of the ERC-721 standard and build upon our previously proposed protocol of Rejectable NFTs (RejNFTs), which introduces a rejectable functionality empowering the receiver to reject the transfer of an NFT. Additionally, we discuss the reasons why achieving a fair direct exchange of NFTs is currently unattainable with the prevailing standards. We present the key functionalities of the ExNFT approach, along with a Solidity implementation of the ExNFTs. Furthermore, we evaluate the performance of the protocol, considering costs and security.
The task of access control in distributed information systems utilizing smart contracts is considered. A concise review of the main access control approaches — mandatory, role-based, and discretionary — is presented, along with their key features and limitations. Particular attention is paid to the access control approach based on mandatory access control (MAC). Known access control approaches applied in both traditional non-distributed and distributed information systems utilizing smart contracts are analyzed. The peculiarities of these distributed information systems that influence access control decisions are identified. Based on these peculiarities, the drawbacks of the discretionary and role-based approaches are determined, and the mandatory approach is proposed. To formalize the approach, a mathematical description of MAC for smart contracts is provided. To demonstrate the concept, several examples of implementing this mathematical description are presented in the form of Solidity code fragments: a direct naive implementation, an implementation using modifiers, and an implementation based on a dedicated access manager contract. The code is described, its main idea is explained, and possible directions for further scaling of these code fragments are outlined. Based on the analysis of the proposed applications, the modifier-based implementation of MAC is identified as the most efficient in terms of computational resources, while the access manager approach is considered the most scalable. The latter approach is proposed for complex distributed systems involving multiple smart contracts. The results of the experimental study are presented to compare the performance indicators of the proposed access control implementations with known implementations. Prospects for further research aimed at improving access control in distributed information systems utilizing smart contracts are identified.
Every standard signature scheme enforces one property: only the key holdercan sign. What the key holder signs is unconstrained. Policy enforcement-- spending limits, rate limits, access control -- lives in smartcontracts, middleware, or governance: layers that can be upgraded,bypassed, or exploited. We call this the software-layer assumption:compliance holds only if the enforcing code is correct and unmodified. We eliminate this assumption. We introduce behavior-bound signatures(BBS), in which a policy constraint delta(x) < epsilon is committed atkey generation and enforced inside the signature's zero-knowledge proof.If the action violates the policy, the ZK constraint system isunsatisfiable -- no witness, no proof, no signature. This is not asoftware check. It is a mathematical impossibility. No software canoverride. Unlike policy-based signatures (where an authority imposes policy onsigners), BBS is self-committed: the signer binds their own futurebehavior at key generation, and even the signer cannot later violate orrevoke this commitment. We formalize this as policy-soundness (PS-CMA), a security modelstrictly stronger than EUF-CMA, and prove it under standard assumptions(Pedersen binding, Poseidon CR, ZK knowledge soundness). From thissingle primitive, five independent consequences follow -- not as separatedesigns, but as necessary implications of one cryptographic root: (A) Compliance safety under f <= n-1 Byzantine faults, decoupled from honest-quorum assumptions.(B) O(1) verification and audit via a single ZK check and Pedersen homomorphic aggregation.(C) Elimination of the virtual-machine execution layer for policy-constrained transactions.(D) A gasless ledger: branch C removes metering, while ZK-encoded rate limits make spam mathematically nonexistent.(E) The first cryptographic guarantee that a compromised autonomous AI agent cannot exceed its authorized behavioral envelope.
Open access
3 source records
Cryptography and Data Security
Advanced Authentication Protocols Security
Physical Unclonable Functions (PUFs) and Hardware Security
The rapid expansion of enterprise-scale data ecosystems and AI-driven services has created an urgent need for autonomous governance mechanisms capable of operating across distributed, dynamic, and heterogeneous environments, where traditional centralized control models increasingly fail to provide the scalability, adaptability, and real-time compliance required by modern enterprises. In response to these limitations, this paper introduces the concept of Multi-Agent Autonomous Governance Networks (MAAGN), a novel architectural paradigm that leverages advances in multi-agent systems (MAS), policy-driven governance, and self-adaptive computing to enable truly self-regulating AI ecosystems. MAAGN is designed to distribute governance responsibilities across intelligent, cooperative agents that operate with contextual awareness, enabling localized decision-making while maintaining global policy alignment. By integrating cognitive agent models capable of perception, reasoning, and learning with layered governance frameworks that enforce regulatory, organizational, and operational constraints, the architecture supports continuous compliance and dynamic policy evolution. Furthermore, the incorporation of enterprise-scale coordination mechanisms such as decentralized consensus protocols, adaptive orchestration layers, and feedback-driven control loops ensures system-wide resilience and fault tolerance even in highly volatile environments. The study synthesizes foundational theories in MAS, contemporary developments in multi-agent reinforcement learning, and emerging governance-aware AI frameworks to propose a scalable, extensible, and future-ready model for enterprise AI control systems, positioning MAAGN as a critical enabler for trustworthy, transparent, and autonomous digital infrastructures.
Anthony Uchenna Eneh, Love Allen Chijioke Ahakonye, Jae Min Lee, Dong-Seong Kim
Modern auto-insurance workflows require sharing heterogeneous digital evidence across multiple organizations. Yet, current cloud-based role-based access control mechanisms remain coarse-grained and poorly suited for expressing time, purpose, and case-specific constraints. This study presents ClaimGuard, which addresses these limitations by placing a blockchainbacked attribute-based access control gateway in front of existing evidence stores, enforcing fine-grained on-chain policies, and issuing short-lived capability tokens for authorized access. Implemented as a REST gateway with PureChain smart contracts, ClaimGuard is evaluated using realistic workloads involving up to 200 subjects and 1000 evidence resources. Experiments on a local Ethereum network shows sub$\sim 70 ~\text{ms}$tail latency, throughput exceeding$\sim 1000$requests/s, rapid policy updates, and zero false accepts, demonstrating the practicality of decentralized, auditable access control for privacy-preserving claims evidence sharing.
Mohamed Seifelnasr, Mohamed Mobarak, Riham AlTawy, Amr Youssef
The metaverse transforms how individuals interact, work, and engage in virtual environments, creating new opportunities in gaming, education, e-commerce, and social networking. At the core of this experience are avatars (i.e., digital representations of users that serve as their proxies in virtual spaces). Ensuring secure and privacy-preserving communication between avatars presents critical challenges, particularly in protecting metaverse user privacy by preventing the linking of avatars to users' social and professional lives. Adopting anonymous schemes such as ring signature schemes requires access to all public keys within the anonymity set, which is impractical in the metaverse. In this paper, we proposeSPARTA(Secure andPrivacy-preserving protocol withRole separation andTrustworthiness forAvatars in the metaverse), a protocol that enables avatar authentication and maintains avatar unlinkability. By leveraging mercurial signatures, our approach allows metaverse users to generate multiple unlinkable avatars without requiring repeated registration with the metaverse service provider, thereby enabling seamless role separation. Additionally, by using a time-based hash chain, only avatars in possession of a reputation token from the time-based hash chain can submit their feedback on a smart contract based on their interactions. Given the soundness property of zero-knowledge proof and the origin-hiding property of mercurial signatures, we formally prove that${\sf SPARTA}$achieves mutual authentication, avatar unlinkability, and penalization enforcement. Additionally, we analyze the performance overheads introduced by its cryptographic primitives and compare${\sf SPARTA}$with existing metaverse authentication protocols. Furthermore, we implement the protocol using socket programming. This implementation simulates real-time message exchanges between protocol entities, resulting in an end-to-end latency of 105 ms. Compared to existing metaverse authentication frameworks,${\sf SPARTA}$provides unlinkable avatar authentication that achieves mutual authentication, role separation, and data sovereignty without reliance on an online trusted third party. The concurrent implementation between two Raspberry Pi devices demonstrates the scalability of${\sf SPARTA}$, achieving a total completion time of 17.338 seconds for 1000 concurrent authentications, corresponding to a throughput of approximately 57.7 authentications per second, confirming its practicality for large-scale metaverse environments.
Hari Purnama, I Putu Bakta Hari Sudewa, Tazkia Nizami, Bagas Sambega Rosyada · 6 authors
Electronic Medical Records (EMRs) are mandatory in Indonesia following the Ministry of Health regulation, which raises significant challenges in data security and patient-centric access control. Current implementations rely on centralized healthcare systems or third-party vendors, creating risks of unauthorized access, data leakage, and uncertain data integrity. To address these issues, this study proposes DecMed, a decentralized EMR management framework built on IOTA Distributed Ledger Technology (DLT). DecMed integrates Capability-Based Access Control (CapBAC), Proxy Re-Encryption (PRE), and the InterPlanetary File System (IPFS) to enforce patient ownership of medical data. Patients actively grant or revoke access, define access duration, and selectively share data with healthcare personnel. The system is implemented using smart contracts in the Move programming language on the IOTA ledger, while encrypted clinical data is stored on IPFS. Evaluation through unit testing of various unauthorized access scenarios demonstrates that DecMed effectively enforces fine-grained access rules, preserves data confidentiality and integrity, and ensures compliance with national healthcare requirements.
We propose Trustless Agent Swarms, a framework enabling privacy-preserving coordination among autonomous AI agents on EVM-compatible blockchains. Our system integrates four cryptographic primitives: (1) Groth16 zero-knowledge proofs for proving reputation thresholds without revealing scores; (2) EIP-5564 stealth addresses for unlinkable fund transfers; (3) ERC-4337 account abstraction for gasless autonomous execution; and (4) Semaphore for anonymous group signaling. We implement a 586-constraint reputation proof circuit and deploy five smart contracts on Base Sepolia. Proof generation: 580ms. On-chain verification: 407,576 gas.
Everybody is these days plunging into decentralized applications, blockchain, and digital identity. And honestly, it's a rendering that the ancient method of authenticating yourself looks nice, outdated and risky. Whenever you give up your personal info, you are just wishing it does not find its way into a data leak or get misused. Precisely, this is the reason that we constructed a new path to manage identity checks that really care about your privacy. This is what we are doing: our framework is based on Ethereum Attestation Service (EAS) and Zero-Knowledge Proofs (ZKPs). To begin with, we generate offchain attestations based on the EIP-712 standard. Your signature remains verifiable; however, your confidential information doesn't go anywhere and through which we squeeze these attestations. SP1 using zero-knowledge virtual machine (zkVM) this step checks everything twice, the construction, the encryption, the logic, all of it. When it's all good then the system will spit a short, non-interactive Groth16 or Plonk (if)SNARK proofs known as zero-knowledge proofs (you're curious). This evidence makes things private and at the same time accurate. There is the interesting side of it: you can check it immediately in your local devices using a super lightweight browser or with a Node.js app WebAssembly verifier. It does not require any middlemen and there is no need for extra trust. You can send evidences, in case you wish to using Solidity contract on-chain. This allows the system to issue new fraudulent statements such as isOver18 = true without displaying your actual age or any other personal data. So what does this mean? You earn greater confidence, enhanced interoperability and connections through decentralize systems. Transparency is what you have with this of ZKP attestation and actual privacy. It's actually practical, as well, can be used with KYC, DeFi, age-requiring app checks, and secured access controls. Essentially, it is a huge leap higher on behalf of anonymity and trust in electronic self.
This study proposes the multi-layered Decentralised Autonomous Identity System (DAIS) for safe, scalable, and policy-aware identity management for autonomous AI agents. DAIS uses distributed ledgers, trust registries, cryptographic credential processing, and adaptive governance principles to authenticate and authorise without central authority. For security and operational reliability, the architecture uses efficient verification techniques, Byzantine fault-tolerant consensus, hierarchical credential state management, and behaviour-aware trust scoring. The mathematical definitions of credential validation, revocation propagation, and consensus guarantees show how DAIS accomplishes constant-time verification and quick revocation dissemination over distributed systems. A 50-agent testbed, PBFT-based registry duplicates, and enterprise-grade hardware were used to evaluate DAIS to OAuth 2.0 and OpenID Connect under identical settings. DAIS regularly outperforms centralised solutions in latency, revocation speed, computational overhead, interoperability, and scalability, improving verification time by fourfold and revocation responsiveness by sixteen-fold. These findings show that DAIS is a durable, high-performance, and future-ready identification infrastructure for large autonomous agent ecosystems.
Zibin Lin, Taotao Wang, Shengli Zhang, Long Shi · 6 authors
Open Web 3.0 platforms increasingly operate as \emph{service ecosystems} (e.g., DeFi, DAOs, and decentralized social applications) where \emph{admission control} and \emph{account provisioning} must be delivered as an always-on service under bursty demand. Service operators face a fundamental tension: enforcing Sybil resistance (one-person-one-account) while preserving user privacy, yet keeping on-chain verification cost and admission latency predictable at scale. Existing credential-based ZK admission approaches typically require per-request on-chain verification, making the provisioning cost grow with the number of concurrent joiners. We present \textbf{ZK-AMS}, a scalable admission and provisioning layer that bridges real-world \emph{Personhood Credentials} to anonymous on-chain service accounts. ZK-AMS combines (i) zero-knowledge credential validation, (ii) a \emph{permissionless} batch submitter model, and (iii) a decentralized, privacy-preserving folding pipeline that uses Nova-style recursive aggregation together with multi-key homomorphic encryption, enabling batch settlement with \emph{constant} on-chain verification per batch. We implement ZK-AMS end-to-end on an Ethereum testbed and evaluate admission throughput, end-to-end latency, and gas consumption. Results show stable verification cost across batch sizes and substantially improved admission efficiency over non-recursive baselines, providing a practical and cost-predictable admission service for large-scale Web 3.0 communities.
Zibin Lin, Taotao Wang, Shengli Zhang, Long Shi · 6 authors
Web 3.0 platforms need an onboarding mechanism that can admit real users at scale without forcing them to reveal identity documents or pay one on-chain verification cost per user. Existing approaches typically rely on KYC-style disclosure, per-request on-chain verification, or trusted batching, making onboarding cost and latency difficult to predict under bursty demand. We present \textbf{ZK-AMS}, a credibly anonymous admission infrastructure that maps Personhood Credentials to anonymous on-chain Soul Accounts. Rather than introducing a new primitive, ZK-AMS composes zero-knowledge credential validation, permissionless batch submission, recursive proof aggregation, and anonymous post-admission account provisioning into one end-to-end workflow. Its key design feature is a confidential batching pipeline in which admission instances of a common relation are folded off-chain under multi-key homomorphic encryption, allowing an untrusted batch submitter to coordinate aggregation without direct access to individual user witnesses during batching; the confidentiality scope is characterized explicitly in the security analysis. The resulting batch is settled on-chain with constant verification cost per batch rather than per admitted user. We implement ZK-AMS on an Ethereum testbed and evaluate admission throughput, end-to-end latency, gas consumption, and parameter trade-offs. Results show stable batch-verification gas across evaluated batch sizes, substantially lower amortized on-chain cost than the non-recursive baseline, and practical cost-latency trade-offs for high-concurrency onboarding in Web 3.0 platforms.
Atefeh Nekouie, Majid Vafaei Jahan, Mohammad Hossein Moattar, Reza Sheibani
Access control and data privacy are two of the main necessities in managing electronic health records (EHRs) across distributed domain. There are privacy gaps that expose EHRs to risks like unauthorized access by unaffiliated medical personnel. Traditional attribute-based encryption (ABE) allows encryption based on user attributes but is unable to incorporate data-specific attributes, such as the type of medical information included in the record or the potential physician. This paper introduces a novel approach that integrates ABE with large language models (LLMs) and blockchain technology to enhance security and contextual access control in EHR systems. Specifically, a domain-specific LLM, such as ClinicalBERT, is leveraged to automatically extract semantic data attributes from unstructured medical records, enabling a more granular and context-aware encryption process. By embedding both user and data attributes into the ABE framework, access policies are dynamically refined, ensuring that only authorized users can view specific types of medical information. Furthermore, blockchain's immutable ledger enhances trust, streamlines attribute revocation, and fortifies the system against unauthorized modifications and security threats. The proposed framework significantly strengthens EHR privacy by integrating machine learning-driven attribute extraction with cryptographic access control, outperforming existing schemes in both security and flexibility. Evaluations validate the effectiveness of the proposed framework in preventing unauthorized access while maintaining efficient and transparent data management.