In blockchain networks, so-called "full nodes" serve data to and relay transactions from clients through an RPC interface. This serving layer enables integration of "Web3" data, stored on blockchains, with "Web2" mobile or web applications that cannot directly participate as peers in a blockchain network. In practice, the serving layer is dominated by a small number of centralized services ("node providers") that offer permissioned access to RPC endpoints. Clients register with these providers because they offer reliable and convenient access to blockchain data: operating a full node themselves requires significant computational and storage resources, and public (permissionless) RPC nodes lack financial incentives to serve large numbers of clients with consistent performance. Permissioned access to an otherwise permissionless blockchain network raises concerns regarding the privacy, integrity, and availability of data access. To address this, we propose a Permissionless Accountable RPC Protocol (PARP). It enables clients and full nodes to interact pseudonymously while keeping both parties accountable. PARP leverages "light client" schemes for essential data integrity checks, combined with fraud proofs, to keep full nodes honest and accountable. It integrates payment channels to facilitate micro-payments, holding clients accountable for the resources they consume and providing an economic incentive for full nodes to serve. Our prototype implementation for Ethereum demonstrates the feasibility of PARP, and we quantify its overhead compared to the base RPC protocol.
The digital economy is one of the most dynamic, fastest growing, and impactful domains in modern economic development. To fully exploit the potential value of data as an economic resource, many governments have implemented policies to encourage and regulate data circulation and trade. Despite the increasing adoption of blockchain-based data trading platforms, a significant challenge persists: verifying data quality without compromising privacy. This deficiency reduces data utilization efficiency and limits its economic potential We propose HES, a decentralized scheme for data quality verification in transactions, which integrates homomorphic encryption, blockchain, and zero-knowledge proofs to balance privacy and verifiability. The proposed method introduces data meta-certificates to represent the original data and employs cryptographic methods to enable zero-knowledge verification. This mechanism supports the verification of both data content and quality while preserving privacy. Data buyers can verify datasets without accessing specific content or involving third-party intermediaries. In this decentralized framework, data buyers can independently verify whether a dataset meets their requirements based solely on its content and quality indicators. Our experiments show that the proposed approach solves the challenge of reaching data quality consensus in distributed scenarios, enabling data buyers and sellers to swiftly align on quality standards. This facilitates the secure circulation and trade of data assets while unlocking their economic value. The findings offer a robust, privacy-preserving consensus mechanism for evaluating data quality in transactions.
The Artificial Intelligence of Things (AIoT) is driving human society from “information” to “intelligence”, and the information technology industry is undergoing tremendous changes. However, AIoT data faces security threats such as leakage and illegal access when assisted by third parties. Therefore, some scholars use attribute-based proxy re-encryption (ABPRE) for secure sharing of data. However, the existing ABPRE schemes suffer from high computational overhead and inefficient attribution revocation, which seriously hinders practical application. To solve these problems, in this paper, we propose an efficient attribute-based proxy re-encryption scheme with fast attribute revocation (EPREAR). We design a non-interactive zero-knowledge proof protocol based on blockchain to ensure the verifiability of the key during attribute revocation. Furthermore, we devise a boundless encryption and decryption mechanism to enable the system's encryption and decryption with a fixed computation overhead, regardless of the size of the attribute set. And EPREAR possesses the ability to add infinite attributes without re-initializing the system. Finally, we perform theoretical and experimental analyses that show EPREAR has excellent computational performance. As a consequence, it has better application value in AIoT.
In the Internet of Vehicles (IoV) era, connected vehicles are leveraging intelligent sensors to share sensitive and real-time information to enhance road safety, driving comfort, and traffic efficiency. Despite these advancements and benefits, security and privacy vulnerabilities remain a crucial challenge. This article proposes an enhanced trust-enabled Delegated Proof of Stake (DPoS) consensus-based consortium blockchain to address these challenges effectively for information sharing. The proposed consensus approach focuses on miner selection based on trust scores derived from vehicle transaction history analyses. The trust score calculation employs entropy information and binomial distribution, where the entropy measures the uncertainty in a vehicle's behavior, and the binomial distribution assesses the success rate of its transactions. This model ensures traceable and anonymous vehicle-to-vehicle information sharing, preventing unauthorized information transfer and improving overall system reliability. By leveraging the enhanced trust-based DPoS consensus mechanism of consortium blockchains, the proposed scheme leads to overcoming the challenges of vehicular ad hoc networks, along with fostering economic interest through enhanced traffic safety and energy conservation. The experimental results validate the proposed model, revealing significant improvements in terms of detection of malicious vehicles, communication latency, security, and efficiency of IoV applications.
Muhammad Iqbal, Kunal Raj, K.V. Narasimha Reddy, Mohd. Mudaseer Mazharuddin
In today's digital age, student academic data is still largely controlled by educational institutions, which creates major risks and limitations.Centralized systems are vulnerable to data loss due to natural disasters, political instability, or system failures.They also make it difficult for students to access or share their records when participating in exchange programs or pursuing lifelong learning across different platforms.To solve these issues, this paper introduces a decentralized approach where students have full control over their educational data.Using blockchain technology-specifically the Ethereum public network-and Web3 tools, we present DecentralEduChain, a framework that allows students to securely store and manage their academic records through smart contracts.Educational institutions can interact with these contracts via integrated Learning Management Systems (LMS), enabling both the reading and updating of student records without relying on centralized databases.This system not only enhances security and transparency but also empowers students with ownership of their data, making it easier to share academic credentials across institutions.The paper also outlines the practical steps for implementing the system, including smart contract creation and integration with LMS platforms, making it a promising solution for the future of educational data management.
Juan Alamrio Berrios Moya, John Ayoade, Md. Ashraf Uddin
Academic credential fraud presents a significant challenge to the global academic and labor markets, undermining the credibility of legitimate qualifications. In this paper, we introduce ZKBAR-V, a Zero-Knowledge Proof-Enabled Blockchain-Based Academic Record Verification System. This system is designed to provide a privacy-preserving, immutable, and secure framework for managing academic credentials. The proposed system leverages zkEVM smart contracts on a blockchain-based infrastructure that enables credential verification without exposing underlying data. The approach integrates Decentralized Identifiers (DIDs) to standardize identity management while eliminating reliance on centralized authorities. We have used dual-blockchain, which separates public and private information, which can enhance both efficiency and privacy. In addition, this approach employs the Interplanetary File System (IPFS) for decentralized and secure document storage. ZKBAR-V is designed as an open-source, interoperable solution with a standardized Application Programming Interface (API) for seamless integration. We implemented the system and conducted comprehensive testing, which demonstrates its capability to manage transactions securely, maintain privacy, and reduce costs compared to traditional Ethereum mainnet-based solutions. By combining advanced blockchain technologies, decentralized storage, and globally unique identifiers, ZKBAR-V offers a scalable, adaptable, and robust solution for academic credential management. This strategy can significantly enhance credential integrity, promote global student mobility, and provide institutions worldwide with a trustworthy and efficient verification system.
Blockchain technologies are inherently decentralized and designed in such a way to ensure data integrity through cryptographic tools such as hashing, Merkle trees, and event consensus mechanisms involving PoW and PoS. This paper therefore develops an integrated model incorporating the aforementioned elements and hence provides a solid framework for real-time, effective, and scalable validation and security of data. The model ensures high compatibility with prevailing data systems to support efficient and scalable processes of validation. The framework, while in testing, has always returned consistent hash times and efficient recording to the blockchain, regardless of size. This flexible use of PoW and PoS makes it a tunable framework according to the needs of a particular application without sacrificing security or efficiency. This includes an anomaly detection system featuring a 93.5 % accuracy rate in robustly identifying abnormalities within the data authentication process.
Sajan Poudel, Rasib Khan, Aalok Dhonju, Nishar Miya
Edge computing is revolutionizing digital infrastructures by enabling low-latency processing, bandwidth optimization, and real-time decision-making across applications like IoT, smart cities, and industrial automation. However, its decentralized nature introduces significant security challenges, making trust and accountability crucial for reliable service delivery. Secure provenance management is vital to address these challenges, ensuring that distributed services and high data volumes are protected from tampering and unauthorized access. This research presents SPHERE, a scalable framework that integrates distributed ledgers, digital signatures, and cryptographic techniques to ensure service integrity and traceability. By leveraging blockchain for tamper-proof provenance, EdgeX Foundry for service orchestration, and an off-chain database for load balancing, our approach enhances security while maintaining system performance. Empirical analysis through a proof-of-concept deployment on a virtualized testbed validates its effectiveness in strengthening service reliability, auditability, and compliance, addressing critical gaps in edge service security and underscoring the importance of secure provenance-awareness in decentralized environments.
Zhen Chu, Wangjie Qiu, T. T. Lei, Jinchun He · 5 authors
The widespread adoption of emerging technologies in healthcare has led to an exponential increase in medical data generation. However, the security of healthcare data has not kept pace, with frequent breaches and unauthorized access posing substantial threats to patient privacy and the integrity of healthcare systems. Although existing access control frameworks offer partial solutions for secure data access, they fall short in authorization granularity, privacy preservation, and large-scale, high-frequency access. To bridge these critical gaps, we propose a novel role-based access control (RBAC) framework that enables secure and efficient management of large-scale, high-frequency data access. The framework first introduces a real-time access behavior analysis algorithm. It then integrates Ethereum smart contract technology with the RBAC model to construct high-performance, scalable access control contracts. Subsequently, the framework simulates the EMR interaction process in a representative healthcare scenario. Through rigorous security evaluations and experimental simulations, we demonstrate that the proposed framework enables robust accessor management, secure data sharing, and effective support for large-scale, high-frequency access while maintaining operational efficiency. This work offers a scalable and practical solution to healthcare data security in the era of big data and population aging.
Mochan Fan, Zonghang Li, Gang Sun, Hongyang Du · 6 authors
Benefiting from the rapidly expanding Internet of Things (IoT) data and powerful computing devices, AI-generated content (AIGC) trains models with vast knowledge to provide automated content generation services. Sharing knowledge through the ciphertext-policy attribute-based encryption (CP-ABE) algorithm is beneficial for training high-quality AIGC models to offer better services. However, existing CP-ABE sharing schemes often involve untrusted third parties, which can result in issues such as knowledge deletion, unverifiable access, and single points of failure. To address these challenges, some blockchain-based sharing schemes have been developed. However, they still face privacy leakage problems. In this paper, we propose SecureShare, a secure and verifiable knowledge sharing scheme based on a consortium blockchain for AIGC services. We begin by outlining a blockchain knowledge sharing architecture and optimizing the Delegated Proof of Stake (DPOS) committee node selection method to ensure that entities can achieve verifiable access control. Additionally, to achieve fine-grained access to knowledge ciphertext while preserving privacy, we propose a CP-ABE scheme with Policy Hiding, attribute privacy preservation, and Revocation, referred to as PHR-CP-ABE. PHR-CP-ABE ensures the privacy of access policies and attributes, and users whose attributes have been revoked cannot decrypt knowledge further. A case study on Dall-E clearly illustrates the operational mechanism of the proposed scheme. We provide theoretical analysis of the security of both the AIGC knowledge sharing scheme and PHR-CP-ABE. Through extensive performance analysis and comparisons with existing schemes, our approach demonstrates significant advantages in terms of computation and communication overhead.
We present a secure and efficient string-matching platform leveraging zk-SNARKs (Zero-Knowledge Succinct Non-Interactive Arguments of Knowledge) to address the challenge of detecting sensitive information leakage while preserving data privacy. Our solution enables organizations to verify whether private strings appear on public platforms without disclosing the strings themselves. To achieve computational efficiency, we integrate a sliding window technique with the Rabin-Karp algorithm and Rabin Fingerprint, enabling hash-based rolling comparisons to detect string matches. This approach significantly reduces time complexity compared to traditional character-by-character comparisons. We implement the proposed system using gnark, a high-performance zk-SNARK library, which generates succinct and verifiable proofs for privacy-preserving string matching. Experimental results demonstrate that our solution achieves strong privacy guarantees while maintaining computational efficiency and scalability. This work highlights the practical applications of zero-knowledge proofs in secure data verification and contributes a scalable method for privacy-preserving string matching.
Abstract Digital identity data management is a significant challenge for businesses and individuals who wish to interact online in the increasingly digital economy, government, and society. Most recently, non-fungible tokens (NFTs) have been proposed as a solution to represent digital identities and underlying data. NFTs are stored on a blockchain based data management system and seem useful for representing digital identity data stored in independent data systems. The idea of using NFTs to represent digital identities and their associated data is promising, but it also raises significant concerns regarding data privacy and compliance. This article examines the NFT-enabled digital identity data representation and management, highlighting associated privacy risks and mitigation strategies. This study employs a qualitative desk research approach, reviewing industry reports, academic papers, and policy documents to analyze trends, technological advancements, and regulatory considerations. It concludes with recommendations for leveraging programmable privacy to address these challenges, providing valuable insights for researchers and practitioners in privacy-preserving digital identity and NFT-enabled identity management.
Jefferson Celeiro Sousa, Bruno Evaristo, Antonio Mateus de Sousa, Ismael Ávila
Este artigo apresenta uma avaliação de performance de contratos inteligentes voltados à gestão de identidades digitais descentralizadas em redes blockchain baseadas em Ethereum. A análise foca em operações fundamentais do ciclo de vida de identidades, como criação, atualização, definição de esquemas de credenciais e controle de revogação, implementadas em contratos Solidity. Foram considerados dois contextos de execução: um ambiente com Hyperledger Besu operando em modo permissionado, e uma referência ao modelo tradicional Hyperledger Indy. Os testes foram conduzidos em rede privada simulando diferentes níveis de carga e configurações de consenso. As métricas avaliadas incluem tempo de resposta, vazão, uso de recursos (CPU e memória) e escalabilidade. Os resultados fornecem subsídios para a escolha de arquiteturas eficientes para soluções de identidade digital baseadas em SSI (Self-Sovereign Identity) e Ethereum, especialmente em cenários corporativos ou regulados.
L V Vedashree, Yogesh Ramaswamy, Leeladhar Gudala, Haydeer MohamadAbbas · 5 authors
Nowadays, the increasing adoption of cloud computing has raised concerns about data privacy and security. However, the existing Homomorphic Encryption (HE) model has limited scalability which led to time-consuming in large-scale cloud computing environments. Hence, this research proposes Decentralized Blockchain-based Authentication with Zero-Knowledge Cloud Auditing (DBA-ZKCA) to improve data security and integrity in cloud computing environments. The proposed DBA-ZKCA consists of five key phases to ensure the privacy, authentication and secure data communication. The first phase initialization sets up cryptographic keys and identity verification parameters before cloud operations starts. These operations are executed by Cloud Service Providers (CSP) and Revocation Admin (RA) respectively. Then, cloud consumer registration phase allows only authorized users to access the cloud services. After that, authentication based on anonymous access phase utilizes DBA to store immutable authentication records. Next, the secure cloud communications phase with ZKCA where the Zero-Knowledge Proofs (ZKP) allow cloud users to verity data integrity without revealing actual data. Finally, revocation phase utilizes RA to revoke access for unauthorized users and updates authentication records for preventing future access. From the results, the proposed DBAZKCA achieved better results when compared to existing Federated Learning and Cryptography (FLC) in terms of accuracy (98.9%) respectively.
With the rapid advancement of the digital age, the Internet has become an integral part of daily life. While users benefit from the convenience of online services, they are increasingly confronted with a critical conflict between identity privacy and security. Under traditional authentication mechanisms, malicious actors often exploit the login channel immediately after user registration, leading to the leakage of personal data. To address this issue, this paper proposes an anonymous identity authentication scheme based on non-interactive zero-knowledge proof. By employing ring signatures in combination with non-interactive zero-knowledge proofs, the proposed method ensures both the legitimacy of user identities and the security of the authentication process. Furthermore, the use of national cryptographic algorithms enhances the scheme's resilience against external attacks. Finally, we conduct comparative experiments to evaluate the proposed scheme. The results demonstrate that it provides anonymity, zero-knowledge soundness, resistance to quantum attacks, replay attacks, and double-spending. Additionally, the scheme achieves higher efficiency in signature generation and verification compared to an RSA+SHA-based ring signature authentication approach.
This paper explores the emerging paradigm of Blockchain-as-a-Service (BaaS) and its implementation of distributed ledger technology in cloud environments. We examine the key characteristics, benefits, and challenges of BaaS platforms, analyze different architectural approaches and deployment models, and evaluate performance considerations for blockchain networks in the cloud. Through a comprehensive literature review and analysis of existing BaaS offerings, we provide insights into the current state of the technology and identify promising research directions. Our findings indicate that BaaS has significant potential to accelerate enterprise blockchain adoption by reducing complexity and costs, but also faces hurdles related to security, scalability, and standardization that need to be addressed as the field matures.
This article presents a comprehensive framework for applying blockchain technology to secure data integration challenges in multi-cloud and hybrid-cloud environments. This article examines how distributed ledger technology creates a trust layer that addresses key vulnerabilities in traditional integration approaches while maintaining performance characteristics suitable for enterprise deployments. This article's architecture leverages permissioned blockchain networks, smart contracts, and cryptographic verification mechanisms to ensure data integrity, enforce governance policies, and provide immutable audit trails across heterogeneous cloud platforms. Our performance evaluation demonstrates viable throughput and latency characteristics compared to traditional integration methods, while offering enhanced security properties. Through case studies in financial services, healthcare, supply chain, and critical infrastructure protection, we illustrate practical implementations and quantifiable benefits. Despite challenges in scalability, energy consumption, legacy system integration, regulatory compliance, and organizational adoption, the architecture shows promising results for high-value data workflows. The research contributes to the emerging intersection of blockchain and multi-cloud computing by providing both theoretical foundations and practical implementation guidance for organizations seeking to enhance security posture across distributed cloud environments.
Decentralized Identity (DID) management is pivotal for data security and privacy-preserving in the digital era, yet existing systems face critical challenges, including single point of failure, privacy leakage, and high computational overhead. To address these limitations, this paper proposes a multi-party verifiable trust validation mechanism based on Verifiable Relation Sharing (VRS). The mechanism skillfully integrates Multi-Verifier Zero-Knowledge proofs (MVZK) with Verifiable Secret Sharing (VSS) to securely share secret attribute vectors among multiple verifiers. This enables the generation of Zero-Knowledge Proof (ZKP) of relationships without revealing the actual data. This mechanism ensures that each verifier obtains partial information, thereby effectively defending against single-point attacks, and reducing computational and communication costs through distributed verification. Experimental results confirm the practicality within DID ecosystems, offering a scalable and privacy-preserving solution for multi-party verification and a foundational framework for secure DID verification in blockchain.
Aryan A Ayare, Vaishnavi A Jadhav, Mustafa K Banatwala, Shashank V Changlere · 6 authors
Blockchain is a decentralized and distributed ledger technology that ensures data security, transparency, and immutability, making it a promising solution for academic record management. Currently, academic records are managed through centralized databases controlled by educational institutions, relying on manual processes, institutional servers, and third-party services. These systems are prone to inefficiencies, data breaches, and authentication challenges, often requiring time-consuming verification processes vulnerable to fraud. Blockchain technology addresses these limitations by offering a decentralized, tamper-proof framework that enhances security, accessibility, and trust in academic credential verification. This study reviews various blockchain platforms, consensus mechanisms, and scalability solutions, with a focus on Hyperledger Fabric and Ethereum, assessing their applicability in educational contexts. Furthermore, off-chain storage techniques like InterPlanetary File System, consensus algorithms, and access control mechanisms are analyzed to optimize the efficient and secure management of sensitive academic data. By integrating blockchain technology, educational institutions can modernize record-keeping, streamline verification processes, and enhance trust in academic credentials, ultimately creating a more secure and transparent academic record management system. Statistical analysis further highlights blockchain's growing adoption in education, demonstrating its effectiveness in reducing fraud, improving accessibility, and ensuring data integrity.
Information disorder has become a major societal challenge, impacting public discourse and democracy. This phenomenon has been exacerbated by the spread of social media platforms, affecting various areas, ranging from national elections to public health. Addressing fake news through a manual approach (e.g., human fact-checking) is unfeasible due to the rapid production of textual content. At the same time, applying automatic tools is equally challenging, primarily due to the ambiguity of natural language. In this paper, we addressed online information disorder from a different perspective by proposing a platform that supports trustworthy and reputable news producers and enhances awareness among readers across various social media. Specifically, the proposed platform enables news producers to automatically embed a unique watermark in the text they create, ensuring that the news cannot be manipulated or misattributed. The watermarking is embedded in a fine-grained way, allowing even small extracts of the news to be shared while preserving traceability. Additionally, the association between the watermark and the news item is recorded in a distributed ledger, preventing further manipulation that could arise from centralised management. The aim is to enable readers to make more informed decisions about the content they encounter, even when engaging with excerpts of the original document, minimising reliance on external fact-checking organisations.