This paper proposes a Blockchain-Based Distributed Data Verification System (BBDVS) designed to address the inherent trust issues present in traditional distributed data verification methods. The system leverages the core principles of blockchain technology – namely, its consensus mechanisms and immutability – to provide a secure, transparent, and verifiable record of data integrity. BBDVS utilizes a distributed ledger to maintain a chronological and tamper-proof audit trail of data transactions. Each transaction, representing a data verification event, is cryptographically linked to the previous one, forming a chain. The system employs a consensus mechanism to validate transactions and add them to the blockchain, ensuring data integrity and preventing malicious alterations. This approach eliminates the need for a central authority, reducing single points of failure and enhancing overall system resilience. The paper details the architecture and operational aspects of the BBDVS, focusing on the key components and their interactions. We explore the potential applications of the system across various domains where data integrity and trust are paramount.
Centralised cloud authentication and authorisation commonly rely on a trusted server for identity, policy enforcement, and audit logging, which can increase the impact of compromise and complicate tamper-evident accountability. This paper presents a decentralised biometric authentication and authorisation framework that integrates fingerprint minutiae verification with Ethereum smart contracts and IPFS-based off-chain storage. Biometric templates are processed off-chain using a NIST NBIS-based pipeline ( MINDTCT minutiae extraction and Bozorth3 matching) and protected via SHA-256 hashing, zlib compression, and authenticated encryption (Fernet), while the blockchain stores only integrity metadata (hashes and IPFS content identifiers) and authorisation state. To mitigate replay attacks without introducing additional session-creation transactions, the framework uses a domain-separated request-binding hash ( tokenHash ) over the caller, nonce, timestamp, chain id, and contract address, validated on-chain together with one-time nonce consumption. A prototype was implemented using Solidity on a local Ethereum-compatible test network (Ganache), with Python/Web3 tooling and an IPFS-compatible content-addressed storage interface. Biometric performance is reported using standard metrics (FAR/FRR/EER and ROC/DET curves) on SOCOFing and FVC2002/FVC2004 benchmarks. In the core blockchain experiment, the proposed single-call attendance workflow required 74,773 gas while adding nonce-based replay protection and auditable authorisation checks on top of CID/hash anchoring (the separate literature benchmark reports end-to-end call-path gas under a shared harness). Compression reduces encrypted-template storage by approximately 76–84% across tested dataset sizes. Security analysis and attack simulation show that replay attempts (nonce/token reuse), unauthorised access, and off-chain payload tampering are rejected under the stated threat model.
The increasing digitalization of higher education has created growing demands for secure and transparent academic data management. As a background, conventional academic information systems remain vulnerable to data manipulation, unauthorized access, and difficulties in verifying the authenticity of academic records. Therefore, the objective of this study is to investigate the role of blockchain technology in enhancing academic data security and transparency within higher education institutions. The method employed in this research is a quantitative approach using a survey questionnaire distributed to 173 respondents consisting of students, academic staff, and administrative personnel from various higher education institutions. The collected data were analyzed using Structural Equation Modeling (SEM) to examine the relationships between blockchain technology adoption, academic data security, and academic transparency. The results reveal that blockchain technology has a significant positive effect on academic data security by providing decentralized data storage, cryptographic protection, and immutable transaction records. In addition, blockchain implementation significantly improves academic transparency by enabling reliable verification, traceability, and authenticity of academic information and credentials. The findings suggest that blockchain technology can minimize the risk of data tampering while strengthening stakeholder trust in academic information systems. In conclusion, blockchain technology serves as an effective solution for improving academic data security and transparency, contributing to the development of a trustworthy and data-driven governance framework in higher education institutions.
Banik and Kumar (Journal of Information Security and Applications 2023) proposed a blockchain-based public key encryption with keyword search for medical data sharing in cloud environments. In this comment paper, we show that the Banik-Kumar scheme leaks keyword information from both ciphertexts and trapdoors.
This paper presents and evaluates a hybrid blockchain architecture for organizational information systems in which PostgreSQL remains the operational database while Ethereum Sepolia is used as an externally verifiable transaction-recording layer. The implemented proof-of-concept is a university wallet system combining a React and TypeScript frontend, an Express.js backend, PostgreSQL with Drizzle ORM, and an OpenZeppelin-based ERC-20 smart contract deployed on Ethereum Sepolia. The system associates successful application transactions with corresponding Ethereum transaction hashes stored in a dedicated relational table. The experimental evaluation uses sequential workloads of 10, 50, and 100 transactions, comprising 160 measured application transactions in total, together with a separate 30-transaction database-mutation experiment. The performance evaluation measures database insertion time, blockchain transaction time, end-to-end execution time, success rate, and gas consumption. All 160 performance-test transactions completed successfully. Mean database insertion time remained below 32 ms, while blockchain transaction time ranged from approximately 15.26 to 21.93 seconds and dominated end-to-end execution time. Mean gas consumption was approximately 40,324 gas per successful transfer. The database-mutation experiment modified the amount field of 7 of 30 successfully recorded transactions after their blockchain references had been established. All seven modified records retained their corresponding blockchain transaction references. However, the experiment did not perform field-level comparison between the modified database records and blockchain event contents and therefore is not presented as a complete cryptographic tamper-detection validation. The implementation and experimental artifacts are publicly available through the associated project repository. The paper presents the work as a proof-of-concept implementation and empirical evaluation of a hybrid database-to-blockchain transaction architecture.