Secret Sharing Schemes are cryptographic tools for securely distributing a secret among participants, ensuring that only authorized subsets can reconstruct it while unauthorized coalitions cannot, a property known as information-theoretic security. A key challenge in designing such schemes is reducing share size, which impacts efficiency and scalability in distributed systems. This thesis studies this problem in structured access structures. After reviewing threshold schemes and their ideality, it focuses on weighted threshold access structures, analyzing classical constructions and methods, including approximation techniques, to reduce share size. Their relevance is illustrated in Proof-of-Stake blockchain protocols, where influence is proportional to staked resources. Ideal hierarchical access structures are then characterized using matroid theory, Boolean polymatroids, and lattice path matroids, and related to applications in multi-level blockchain networks such as Polkadot.
Nacereddine Sitouah, Francesco Bruschi, Stefano De Cillis
The passing of the eIDAS amendment marks an important milestone for EU countries and changes how they must manage digital credentials for both public services and businesses. Italy has led in adopting eIDAS, first with CIE and SPID identity schemes, and now with the Italian Wallet (IO app) aligned to eIDAS 2.0. Self-Sovereign Identity (SSI) is a decentralized model born from the success of Distributed Ledgers, giving individuals full control over their digital identity. The current eIDAS 2.0 and its implementation acts diverge from SSI principles, rendering the European Digital Identity Wallet (EUDIW) centralized and merely user-centric, prioritizing security and legal protection over true self-sovereignty. This paper proposes an architecture that enables the use of IT Wallet credentials and services in an SSI-compliant environment through Trusted Execution Environments and Zero-Knowledge Proofs.
This deliverable (D4.4 â Federated AI/ML) defines the architecture, requirements, and enabling technologies for secure and privacy-preserving federated learning within the CONFIDENTIAL6G project. The document specifies how federated AI/ML can be safely deployed across heterogeneous 6G cloudâedge environments, allowing collaborative model training while ensuring that sensitive data remains local and protected throughout the learning lifecycle. The deliverable consolidates background and state-of-the-art insights on federated learning in 6G, identifies key security, privacy, and trust challenges, and derives a set of functional, security, governance, and operational requirements that guide system design. It then presents the overall federated AI/ML architecture developed under this task, which brings together confidential orchestration, federated learning coordination, cryptographic trust mechanisms, and secure execution across cloud-edge environments. The architecture builds on the confidential orchestration foundations established in Deliverable 4.3 and integrates key enablers from WP2âsuch as Decentralized Identifiers, Verifiable Credentials, and Zero-Knowledge Proofsâto support verifiable, policy-driven, and privacy-preserving participation throughout the federated learning lifecycle. Within this architecture, blockchain-enabled aggregation is introduced as a complementary mechanism to strengthen integrity, auditability, and decentralized trust in model management and aggregation workflows by removing single points of failure and providing tamper-evident provenance for AI/ML models. In parallel, the deliverable reports algorithmic contributions that enhance robustness and fairness under non-IID data distributions and device heterogeneity, ensuring that the proposed architecture remains effective under realistic deployment conditions. Finally, the document outlines how the Federated AI/ML integrates with WP5 use cases, demonstrating its relevance for real-world validation scenarios. Overall, this deliverable establishes a coherent and secure federated learning foundation that supports CONFIDENTIAL6Gâs objectives for trustworthy, privacy-preserving AI in next-generation 6G environments.
We present Y.I.N.-MEMORIA, a comprehensive privacy-preserving architecture addressing fundamental vulnerabilities in AI conversation systems across all platforms, including large language model interfaces, enterprise AI assistants, domain-specific chatbots, and agentic AI systems. The system implements mandatory cryptographic ordering enforcement (DP â ZK â BLINDING â HE, or functional equivalents), mathematically proven unique among 24 permutations, achieving 99.37% accuracy for valid authorizations versus 50.7% for invalid attempts (t = 147.3, p < 10âťâľâ°). KEY CONTRIBUTIONS:⢠Hybrid local-cloud storage with zero-knowledge properties ensuring cloud providers mathematically cannot decrypt conversations⢠Enterprise Shadow AI governance achieving 99.7% detection across 50+ services via network pattern analysis without plaintext access⢠Y.A.N.G. constant-time retrieval providing 340Ă timing attack resistance (reduced leakage from 2.72 to 0.008 bits per 1,000 queries)⢠Complete defense taxonomy across 8 attack categories with quantified metrics (92-99% detection rates)⢠Advanced cryptographic primitives including post-quantum aggregate signatures (90% size reduction), threshold token generation, VRFs, adaptive differential privacy (4-tier Îľ system), federated unlearning (SISA), and incremental Merkle tree encryption⢠Four complete deployment architectures (cloud-only, local-only, mobile-only, enterprise gateway) validated across 4 hardware platforms and 5 operating systems⢠Y.I.N. CERTIFY compliance verification layer enabling machine-readable regulatory certificates for GDPR, DORA, EU AI Act, HIPAA, and Singapore's Model AI Governance Framework for Agentic AI⢠Synergistic combination claims and negative exclusion claims establishing comprehensive defensive prior art ENHANCED VERSION 10.0 FEATURES:Academic Rigor: 4 formal research questions with quantified success criteria; 3 mathematical security proofs (Privacy Preservation, Computational Soundness, Unbypassability); Ablation studies validating necessity of each component; Cross-platform validation (4 hardware platforms, 5 operating systems, <3% variance); 3 novel attack scenarios with >94% detection rates. Comparative Analysis: Table comparing against 8 major systems (Federated Learning, CrypTen, TF Privacy, Opacus, PySyft, Microsoft SEAL, Zcash). Y.I.N.-MEMORIA demonstrated as only system providing mandatory DP enforcement, ZK verification for AI governance, 340Ă timing resistance, 99.7% Shadow AI detection, and complete lifecycle coverage. Legal Protection: Doctrine of equivalents coverage (Warner-Jenkinson precedent); Willful infringement notice (Halo Electronics, 3Ă damages); Comprehensive functional equivalents (12 categories); Minimum performance thresholds excluding weak implementations. Reproducibility Commitment: Complete reference implementation under open-source license; Experimental datasets via Zenodo; Cryptographic test vectors for independent verification; Performance benchmarks across all platforms. Scholarly Depth: 38 peer-reviewed citations (65% increase); Comprehensive related work analysis; Explicit limitations and future research directions; Historical non-obviousness evidence. THREE-PHASE AI LIFECYCLE COVERAGE:Y.I.N.-MEMORIA completes the Y.I.N. Architecture's three-phase AI lifecycle: Training (Y.I.N.-LLM, USPTO 63/941,283), Generation (Article 50 Compliance Engine, USPTO 63/957,571), and Usage (Y.I.N.-MEMORIA, USPTO 63/967,805). The Y.I.N. CERTIFY verification layer spans all three phases. Together, these components provide 643 total claims covering every stage where privacy vulnerabilities can emerge in AI systems. EXPERIMENTAL VALIDATION:85-95% bandwidth reduction, 97% conflict resolution, and compliance scores of 94.7-97.3% for GDPR, HIPAA, DORA, EU AI Act, Singapore MGF for Agentic AI, ISO/IEC 42001, CCPA, and NIS2 Directive. IMPACT METRICS:This architecture prevents Shadow AI breaches costing $4.63M average (20% of all data breaches according to IBM's 2025 Cost of a Data Breach Report), addresses the 20M ChatGPT conversation log discovery precedent (NYT v. OpenAI, January 2026), and satisfies Singapore's Model AI Governance Framework for Agentic AIâthe world's first comprehensive government framework for autonomous agents published January 22, 2026 (4 days prior to this work). DEFENSIVE PRIOR ART:This work establishes comprehensive prior art corresponding to USPTO Provisional Application 63/967,805 (438 claims filed January 25, 2026), part of the Y.I.N. Architecture Portfolio (22 applications, 1,360+ total claims). Includes explicit functional equivalents coverage, doctrine of equivalents, and willful infringement notice enabling enhanced damages up to 3Ă under Halo Electronics precedent. Patent Reference: USPTO Application 63/967,805 (Y.I.N.-MEMORIA) License: CC BY-NC-ND 4.0Corresponding Author: ilyesmazari@hotmail.comVersion: 1.0Publication Date: January 26, 2026
Uma Girish, Greg Gluch, Shafi Goldwasser, Tal Malkin ¡ 6 authors
Position verification schemes are interactive protocols where entities prove their physical location to others; this enables interactive proofs for statements of the form "I am at a location $L$." Although secure position verification cannot be achieved with classical protocols (even with computational assumptions), they are feasible with quantum protocols. In this paper we introduce the notion of zero-knowledge position verification, which generalizes position verification in two ways: 1. enabling entities to prove more sophisticated statements about their locations at different times (for example, "I was NOT near location $L$ at noon yesterday"). 2. maintaining privacy for any other detail about their true location besides the statement they are proving. We construct zero-knowledge position verification from standard position verification and post-quantum one-way functions. The central tool in our construction is a primitive we call position commitments, which allow entities to privately commit to their physical position in a particular moment, which is then revealed at some later time.
Blockchain technology is a Distributed Ledger Technology (DLT) where the digital information is stored across multiple computers and not centralized.Each system stores a copy of DLT to avoid single point of failure.Blockchain stores the information in blocks.All copies are validated and updated simultaneously.There are four main types of blockchain, they are Private / Permissioned, Public / Permissionless, Hybrid and Consortium.Corda is a distributed ledger open-source platform, it was introduced by R3 consortium (R3CEV LLC).It is not a public blockchain, based on agreement network and Peer to Peer (P2P) connections.No native cryptocurrency.Tech stack platform based out of JVM written in Koltin.
The increasing demand for autonomous and open peer-to-peer (P2P) data sharing has driven the widespread adoption of decentralized file systems, such as the InterPlanetary File System (IPFS). However, decentralized data sharing inherently requires distributed access control mechanisms due to the absence of centralized authorities. Although blockchain-based access control has become a primary solution, the public nature of blockchain can unintentionally reveal user attributes, posing significant privacy risks. To address the leakage of attribute sets in blockchain, we propose zk-Guard, a decentralized access control framework integrating blockchain and zero-knowledge Succinct Non-interactive Arguments of Knowledge (zk-SNARKs) tailored for IPFS. To further improve the efficiency of zero-knowledge policy checking and reduce the delay of policy updating, we employ a universal constraint circuit and encode policies into sparse configuration matrices, achieving fine-grained, rapid policy updates without regenerating proving keys while guaranteeing constant-time verification regardless of policy complexity. Additionally, to prevent repeated permission checks for large f iles and improve system responsiveness, zk-Guard integrates Merkle Tree Proof (MTP) mechanisms to securely link sub-data blocks to their root block. Comprehensive theoretical complexity analysis and extensive experiments demonstrate that zk-Guard achieves substantial performance improvements over existing schemes, with constant-time proof verification under 2.5 ms enabling efficient data retrieval, and policy deployment and updates completed within 0.2 seconds even for 1,000 attributes. The source code is available at https://github.com/ningboliucug/zk-Guard.
Minghui Zheng, Shicheng Huang, Deju Kong, Xing Fu ¡ 6 authors
Linkable ring signatures are a type of ring signature scheme that can protect the anonymity of signers while allowing the public to verify whether the same signer has signed the same message multiple times. This functionality makes linkable ring signatures suitable for applications such as cryptocurrencies and anonymous voting systems, achieving the dual goals of identity privacy protection and misuse prevention. However, existing post-quantum linkable ring signature schemes often suffer from issues such as excessive linear data growth the adoption of post-quantum signature algorithms, and high circuit complexity resulting from the use of post-quantum zero-knowledge proof protocols. To address these issues, a logarithmic-size post-quantum linkable ring signature scheme based on aggregation operations is proposed. The scheme constructs a Merkle tree from ring members' public keys via a hash algorithm to achieve logarithmic-scale signing and verification operations. Moreover, it introduces, for the first time, a post-quantum aggregate signature scheme to replace post-quantum zero-knowledge proof protocols, thereby effectively avoiding the construction of complex circuits. Scheme analysis confirms that the proposed scheme meets the correctness requirements of linkable ring signatures. In terms of security, the scheme satisfies the anonymity, unforgeability, and linkability requirements of linkable ring signatures. Moreover, the aggregation process does not leak information about the signing members, ensuring strong privacy protection. Experimental results demonstrate that, when the ring size scales to 1024 members, our scheme outperforms the existing Dilithium-based logarithmic post-quantum ring signature scheme, with nearly 98.25% lower signing time, 98.90% lower verification time, and 99.81% smaller signature size.
Shaoyu Li, Hexuan Yu, Md Mohaimin Al Barat, Yang Xiao ¡ 6 authors
With the rise of decentralized finance, fiat-to-cryptocurrency exchange platforms have become popular entry points into the cryptocurrency ecosystem. However, these platforms frequently fail to ensure adequate privacy protection, as evidenced by real-world breaches that exposed personally identifiable information (PII) and crypto addresses. Such leaks enable adversaries to link real-world identities to cryptocurrency transactions, undermining the presumed anonymity of cryptocurrency use. We propose FC-GUARD, a privacy-preserving exchange system designed to preserve user anonymity without compromising regulatory compliance in the exchange of fiat currency for cryptocurrencies. Leveraging verifiable credentials and zero-knowledge proof techniques, FC-GUARD enables fiat-to-cryptocurrency exchanges without revealing users' PII or fiat account details. This breaks the linkage between users' real-world identities and their cryptocurrency addresses, thereby upholding anonymity, a fundamental expectation in the cryptocurrency ecosystem. In addition, FC-GUARD complies with key regulations over cryptocurrency usage, such as know-your-customer requirements and auditability for tax reporting obligations by integrating a lawful de-anonymization mechanism that allows the auditing authority to identify misbehaving users. This ensures regulatory compliance while defaulting to privacy protection. We implement our system on both desktop and mobile platforms, and our evaluation shows its feasibility for practical deployment.
Current electronic voting infrastructure continues to be plagued by security, transparency and voter privacy concerns, in both large and remote elections. In order to cope with these issues, this paper introduces a blockchain-based voting system which fulfills end-to-end verifiability and maintains ballot secrecy. The system proposed uses a permissioned blockchain system along with Byzantine Fault Tolerant (BFT) consensus protocol to guarantee data integrity and resilience to faults when facing partially adversarial conditions. The combination of homomorphic encryption of tallying encrypted votes and zero-knowledge proofs of voter eligibility and validation of ballots, without disclosing the content of the vote, results in vote confidentiality and auditability. Smart contracts facilitate the process of vote validation and aggregation making it publically auditable without trusting third parties. Simulated workload performance evaluation suggests that, under regular operating conditions, the system has a verification accuracy greater than 98 % and has an average processing time and computational overhead that are lower than those of the corresponding blockchain-based voting systems under realistic operating conditions. The given framework is planned to assist with the real-time auditing and ensure privacy assurances. Besides this, the paper also addresses the practicability of post-quantum cryptographic primitives and cross-chain mechanisms as further improvements to ensure enhancement of long-term security and scalability.
The immense Digital Public Infrastructure (DPI) landscapes, such as Aadhaar, Digi Locker, and UPI, built by Indiaâs rapid digitization, promote large-scale Identity, document, and finance services. However, centralised identity systems are very risky, such as a single point of failure, privacy violations, identity theft, lack of user control over their personal data. This increasing reliance on centralised frameworks underlines an acute need for more secure, private, and citizens-centric identity solutions. This research introduces a decentralized identity model that is based on both the principles of blockchain and the Self-Sovereign Identity (SSI). In the proposed system, the individuals are in control of their credentials since they use secure digital wallets to employ these credentials, while verifiable credentials are stored in an immutable blockchain network. The system relies on public-key cryptography, zero-knowledge proofs, and decentralized identifiers (DIDs) in authenticating users without revealing sensitive personal details. A layered architecture is proposed and connected to the existing government DPI platform by way of a permissioned blockchain network to support a scalable and aligned system with the decentralized identity model. Simulation parameters involved are transaction throughput, latency, resistance, and privacy leakage metrics under changing network conditions, as well as identity usage volumes. The presented algorithms for registration, verification, and identity revocation are robust, efficient, and immune to tampering of data or spoofing an identity. Simulation results validate enhanced security, privacy, scalability, and user empowerment compared to the traditional centralized systems. The bottom line is that the decentralized identity framework is not only capable of strengthening Indiaâs DPI from cyber threats, systemic weaknesses but also guarantees that of an inclusive, user-controlled, and future-ready digital identity management system for more than a billion citizens amidst an ever-expanding digital ecosystem.
Zhichao Wang, Xudong Zhu, Xinxuan Zhang, Yi Deng ¡ 5 authors
Abstract Time-release cryptography is a flourishing research area with a long history and has been extensively studied. In this work, we enrich it by introducing a novel concept: a time-release zero-knowledge proof (TRZKP). A TRZKP is a non-interactive zero-knowledge proof that allows one to publish a proof for a given relation $$R_\mathcal {L}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mi>R</mml:mi> <mml:mi>L</mml:mi> </mml:msub> </mml:math> , such that anyone can only finish the verification after time $$\textbf{T}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>T</mml:mi> </mml:math> by performing a sequential computation. This work formalizes the concept of TRZKP and presents light constructions for the time-release version of any NIZK obtained from a public-coin protocol via Fiat-Shamir transformation. TRZKPs can be applied to provide time-release authentication, for example, they can be employed to construct verifiable timed signatures (VTS), introduced by Thyagarajan et al. (CCSâ20). Through both theoretical and practical analysis, our construction has advantages over existing VTS for Fiat-Shamir signatures. Specifically, when instantiated with Shnorr signature, our VTS signing time remains basically unchanged as the delay time grows, and is preferable for longer delay times; our VTS verification time is significantly small (on the level of milliseconds, while existing works on the level of seconds), and our VTS size is 67 times smaller than the state-of-the-art. It also has the time-verifiability property, which ensures the signature is recoverable after the specified time.
The rapid expansion of the Internet of Things (IoT) has introduced critical security challenges in authentication, data integrity, and privacy preservation. Traditional digital signature schemes, such as RSA and ECDSA, rely on identity-based trust models, which face scalability bottlenecks, lack fine-grained access control, and pose privacy risks in IoT environments. Attribute-based signatures (ABS) offer a promising solution by allowing devices to sign data only if their attributes satisfy a predefined policy, without revealing their exact identity. However, most existing ABS constructions rely on pairing-based cryptography, which is vulnerable to quantum computer attacks, while lattice-based ABS schemes often suffer from either large signature sizes or dependence on non-interactive zero-knowledge (NIZK) proofs. In this paper, we propose an efficient lattice-based ABS scheme that eliminates the need for NIZK proofs while achieving constant-size signatures. Our construction leverages the lattice-based vector commitment technique to achieve quantum resistance while reducing signature size to a constant independent of the number of attributes, significantly improving efficiency compared to prior works. Experimental evaluations confirm that our scheme outperforms existing lattice-based ABS in both computational cost and signature size, particularly for large attribute sets and deep policy circuits. Our results pave the way for practical ABS deployment in resource-constrained IoT applications, such as secure firmware updates, industrial access control, and vehicular networks.
With the rapid development of online aquatic product trading, traditional centralized platforms are facing increasing pressure in terms of data security, privacy protection, and trust. Problems such as tampering with transaction records, weak identity authentication, privacy leakage, and the difficulty of balancing matching efficiency with security limit the further development of these platforms. To address these issues, this paper proposes a blockchain-based identity authentication and access control scheme for online aquatic product trading. The scheme first introduces a dual authentication mechanism that combines a verifiable random function with a Schnorr-based zero-knowledge proof, providing strong decentralized identity verification and resistance to replay attacks. It then designs a dynamic access control strategy based on a multi-dimensional reputation model, which converts user behavior, attributes, and historical transaction performance into a comprehensive trust score used to determine fine-grained access rights. In addition, an AES-PEKS hybrid encryption method is employed to support encrypted keyword search and order matching while protecting the confidentiality of order data. This paper implements a multi-channel architecture for aquatic product trading prototype system on Hyperledger Fabric. This system separates registration, order processing, and reputation management into different channels to improve concurrency and enhance privacy protection. Security analysis shows that the proposed solution effectively defends against replay attacks, key leaks, data tampering, and privacy theft. Performance evaluation further demonstrates that, compared to a single-chain architecture, the multi-channel design, while increasing security mechanisms, maintains a stable throughput of approximately 223 tx/s even when concurrency reaches 600â800 tx/s, ensuring normal operation of the trading system. These results indicate that this solution provides a practical technical approach and system-level reference for building secure, reliable, and efficient online aquatic product trading platforms.
Abstract The emerging growth of Quantum computing has significant challenges to change the classical cryptographic protocols, the security of AIâBlockchain systems to provide long-term security and provide federated learning (FL) for current cryptographic systems. This paper introduces a new framework as Quantum-Resistant Federated AI on Blockchain (QFAIB) that integrates Post-Quantum Cryptography (PQC) algorithms with real-time Federated AI Learning (FAIL) on distributed ledgers creation. The proposed QFAIB ensures end-to-end data security and confidentiality, decentralized trust, and adaptive intelligence, resistant to quantum decryption attacks. Through the integration of hybridization of CRYSTALS-Kyber encryption to create challenging task, that makes the Dilithium digital signatures, and Zero-Knowledge Proofs (ZKP) for privacy-preserving model validation and decentralized federated AI models, the proposed QFAIB compared with baseline and evaluated as the performance metrics as data integrity verification accuracy (DIVA), auditing efficiency (AE), quantum resistance efficiency (QRE), privacy leakage reduction (PLR) and throughput (TT) in multi-cloud and IoT environments and this work proved that real time distributed ledger creations.
Proof-of-Stake (PoS) blockchain protocols have gained increasing prominence in recent years due to their energy efficiency. In PoS systems, users stake tokens to become validators. Those who stake more tokens are elected to propose new blocks with higher probabilities and possess greater voting power in consensus decisions. At first glance, threshold signatures appear to be a promising mechanism for aggregating multiple block attestations in PoS blockchain protocols. However, traditional threshold signatures treat each participant equally in signature generation, disregarding the differing weights of participants. This lack of weight consideration poses a challenge in PoS blockchains, where validators inherently have varying levels of influence. To address this issue, a weighted threshold signature scheme is necessaryâone that accounts for the distinct weights of signers, reflecting their respective voting power in PoS blockchains. Despite this need, no existing weighted threshold signature schemes are resistant to attacks by quantum computing. To fill this gap in the literature, we propose the first lattice-based weighted threshold signature scheme, proven secure under the module short integer solution (MSIS) assumption in the random oracle model. Furthermore, we demonstrate the integration of this novel scheme into PoS blockchain protocols for block attestation. Finally, we implement our weighted threshold signature scheme and present its efficiency evaluation.
The increasing importance of privacy and secure communication in distributed environments has fueled research into innovative solutions that combine data concealment and tamper-resistant recordkeeping. This article presents a logically structured architectural framework for covert steganographic communication, utilizing the Microsoft Azure web3 ecosystem as its foundation. The motivation behind this research stems from the limitations of traditional steganography and blockchain technologies when used independently, particularly in addressing the challenges of operational transparency, scalability, and robust data protection. To bridge these gaps, the proposed system integrates Azure Blockchain Development Kit with other Azure native services to provide a unified architecture. This research article introduces a pioneering architectural framework designed to facilitate covert steganographic communication through blockchain technologies, with a focus on leveraging the Microsoft Azure web3 ecosystem. By integrating Azure Blockchain Development Kit (BDK), Azure Confidential Ledger, Azure Blockchain Services, and Azure Blockchain Workbench with Open Steganography solutions deployed on Azure Virtual Machines (VM), the proposed system aims to achieve secure, confidential, and unobtrusive data exchange. The research methodology encompasses a comprehensive literature review, system design, implementation, and rigorous security analysis, followed by experimental evaluation on cloud infrastructure. By leveraging the strengths of Azureâs blockchain and confidential ledger capabilities alongside advanced steganographic techniques, this study demonstrates a practical approach to achieving secure, confidential, and unobtrusive data exchange. The findings confirm the feasibility and effectiveness of the proposed solution, highlighting its potential to facilitate adaptive, scalable, and privacy-preserving covert communication networks. In conclusion, this work charts new directions for integrating blockchain and steganography within cloud-native platforms, offering enhanced privacy and security for sensitive communications in distributed settings.
Current research on cryptocurrency dual-offline payment systems has garnered significant attention from both academia and industry, owing to its potential payment feasibility and application scalability in extreme environments and network-constrained scenarios. However, existing dual-offline payment schemes exhibit technical limitations in privacy preservation, failing to adequately safeguard sensitive data such as payment amounts and participant identities. To address this, this paper proposes a privacy-preserving dual-offline payment method utilizing a cryptographic challenge-response mechanism. The method employs zero-knowledge proof technology to cryptographically protect sensitive information, such as the payerâs wallet balance, during identity verification and payment authorization. This provides a technical solution that balances verification reliability with privacy protection in dual-offline transactions. The method adopts the payment credential generation and credential verification mechanism, combined with elliptic curve cryptography (ECC), to construct the verification protocol. These components enable dual-offline functionality while concealing sensitive information, including counterparty identities and wallet balances. Theoretical analysis and experimental verification on 100 simulated transactions show that this method achieves an average payment generation latency of 29.13 ms and verification latency of 25.09 ms, significantly outperforming existing technology in privacy protection, computational efficiency, and security robustness. The research provides an innovative technical solution for cryptocurrency dual-offline payment, advancing both theoretical foundations and practical applications in the field.
The digitization of medical records in the healthcare sector demands robust mechanisms to ensure data confidentiality, integrity, and privacy. This paper proposes an innovative multi-factor authentication (MFA) mechanism that leverages smart contracts and blockchain technology to secure the tracking of medical records. The proposed system, named Blockchain Authentication with Zero-Knowledge Proof (BAZKP), provides a tamper-proof environment for storing and accessing records while preserving usersâ personally identifiable information (PII). A key novelty of BAZKP lies in storing only the character count structure of passwords rather than the actual credentials, combined with zero-knowledge proofs (ZKP) to verify identity without exposing sensitive data. This hybrid blockchain/ZKP approach addresses limitations of centralized and hardware-based solutions, reducing vulnerabilities while avoiding the cost and usability constraints of dedicated hardware systems. The system was implemented and tested on a private Ethereum testnet, with a proof-of-concept application developed using Solidity, Web3.js, and MetaMask. Performance evaluation over 100 transactions for core operations (registration, login, and password reset) demonstrated practical viability: registration incurred the highest latency (â4500 ms) and gas consumption (â120,000 gas), while login and reset operations were more efficient (â4000 ms/80,000 gas and â3500 ms/60,000 gas, respectively). Comparative security analysis against existing MFA methodsâincluding 2FA, hardware tokens, and biometricsâconfirms that BAZKP provides superior privacy protection through decentralization and ZKP, without the cost and usability drawbacks of hardware-based solutions. Overall, this approach enhances trust in digital health systems by offering a secure, transparent, and privacy-preserving authentication framework for medical data, representing a significant advancement in digital healthcare security. Keywords: Blockchain; Multi-Factor Authentication; Smart Contracts; Zero-Knowledge Proof; Medical Record Security.
Rahul Aravindh M, Prasannavelan R M, Pradeep N, K. Malathi
A secure and transparent blockchain-based voting system is proposed, designed to preserve voter anonymity, prevent tampering, and ensure one-vote-per-user compliance in decentralized digital elections. The system introduces a lightweight voter authentication layer using one-time password (OTP) verification, with off-chain hashed identity storage to prevent exposure of personal data. Unlike traditional models that rely solely on smart contract logic, this approach strengthens the end-to-end security boundary by validating user eligibility before on-chain interaction. Votes are cast through smart contracts deployed on a public blockchain, ensuring immutability and auditability, while maintaining voter anonymity by detaching authentication logic from vote recording. To address performance bottlenecks and storage limitations, non-critical identity data is excluded from the blockchain, with hashed authentication tokens acting as cryptographic proofs of voter legitimacy. The proposed method was validated through simulation of small-scale voting rounds, demonstrating secure vote casting with a rejection rate of 100% for duplicate or invalid attempts. Average authentication time remained under 200 milliseconds per session. The modular design facilitates integration with government or institutional ID systems and supports anonymous and verified voting modes, making it adaptable for educational, corporate, or civic deployment. Future iterations will explore zero-knowledge proofs to further enhance privacy guarantees while preserving voter eligibility validation.
Introduction Digital identity infrastructures used in electronic passports, national eID schemes, and federated authentication systems rely predominantly on centralised registries and classical public key cryptography. These architectures enable large-scale identity correlation, mass data aggregation, and single points of compromise, while remaining vulnerable to quantum attacks against RSA and elliptic-curve cryptography. There is no deployed identity framework that simultaneously provides post-quantum security, cryptographic privacy guarantees, and decentralised trust. Methods This study proposes a quantum-proof digital passport architecture combining lattice-based post-quantum cryptography, decentralised blockchain identifiers, and transformer-based decentralised artificial intelligence. The framework employs NIST-aligned post-quantum key encapsulation and digital signatures, zero-knowledge proofs for selective disclosure of identity attributes, and homomorphic encryption for encrypted identity verification. Blockchain oracles and decentralised identifiers enforce credential integrity and auditability without reliance on central identity providers. Transformer attention mechanisms support adaptive identity validation while preventing persistent identity profiling. Results Architectural analysis shows that the proposed system prevents quantum-enabled credential forgery, retrospective decryption, and cross-service identity linkability. Zero-knowledge verification removes plaintext exposure of personal data, and decentralised credential control eliminates central compromise vectors. The design remains interoperable with existing passport and eID infrastructures. Discussion The results demonstrate that secure post-quantum digital identity requires the combined application of quantum-resistant cryptography, decentralised governance, and cryptographic privacy enforcement.
Open access
Cryptography and Data Security
Quantum Computing Algorithms and Architecture
Physical Unclonable Functions (PUFs) and Hardware Security
Journal of Theoretical and Applied Information Technology
With the growing volume of health information it has become common practice to protect the patient identity while maintaining convenient access to the data. Due to varying flow of cyber security threats, traditional solutions never manage to get flexible access to data without compromising with overflow of data. To overcome these challenges focusing on patient data protection, in this paper, we propose a new Hybrid Integrated Hashing approach entitled "Dynamic Adaptive Hash-Block Access Control (DAHBAC) framework" using blockchain based advanced data access control mechanism. The dynamic multi factor hashing scheme can change in response to the current Vulnerability of data and access patterns, whereas data access control refers to leverage blockchain's immutability and decentralized structure that helps protecting patient privacy while allowing authorized persons to read. The dynamic hashing method prevents intruder attempts by making hash and easy to calculate but requiring real-time modification of the hash for access protection. This is made possible by harnessing the application of zero-knowledge proofs (ZKP) within the frame of blockchain to enable verification of information when there is no disclosure of the data. Compared with the conventional methods, testing of prototype in a health care organization resulted in 92% on attempts by unauthorized workers to enter the system and 7% increasing data retrieval rate. These findings shows that the proposed model is a perfect patient data protection pattern in ehealth systems, because it is not only secures patients data but also enhances the accessibility and scalability to handle more clients. It is enabled by the use of zero-knowledge proofs (ZKP) in combination with blockchain technology to verify information, while keeping the information secret.