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.
Blockchain platforms enable transparent and immutable solutions for verification of proofs of digital claims, permissions, states, and events. However, numerous decentralized applications still force their users to operate with wallets, native tokens, and transaction costs, even though they have nothing to do with their verification purpose. This issue makes decentralized systems less user-friendly and constrains their adoption among not technically proficient Web3 users. This paper explores different patterns for gasless verification of proofs on decentralized platforms. The research focuses on five architectural patterns of such decentralized proof systems, including read-only blockchain verification, off-chain signature verification, relayer-based meta-transactions, account abstraction with paymasters, and hybrid on-chain/off-chain proof anchoring. Each architecture is analyzed qualitatively considering its usability, cost-effectiveness, decentralization, security, scalability, and implementation complexity. The results show that gasless verification enhances the usability of such systems, but at the same time transfers responsibility of trust assumptions to relayers, paymasters, backend servers, signature protocols, and off-chain data availability mechanisms. In this regard, potential risks, which include replay attacks, centralization of relayers, malicious paymaster activities, uncertainty of signers’ identity, and dependence on backend servers, are discussed. Besides, the paper offers a decision-making framework for choosing one of gasless verification architectures depending on the presence/absence of state change, authority of proofs, required verification frequency, degree of decentralization needed, and level of technical maturity of system users.
This research presents a novel decentralized identity management system leveraging Ethereum smart contracts and cryptographic protocols to enable self-sovereign digital identities. Traditional centralized identity solutions pose risks related to data privacy, security, and user autonomy. To address these limitations, we propose a blockchain-based architecture integrating smart contracts for identity governance, IPFS for decentralized attribute storage, and threshold cryptography for private data recovery. Our dual-contract model (Identity Contract and Recovery Contract) facilitates secure identity creation, verifiable attribute attestation, and robust key recovery through social consensus. We introduce a privacy-preserving mechanism using encryption-key splitting among trusted peers to enable recovery of encrypted off-chain data. Implementation uses Web3.js, Solidity, and QR-code-based communication, abstracting cryptographic complexities from end-users. Security analysis addresses replay, man-in-the-middle, Sybil, and multi-user compromise attacks with mitigations including challenge-response authentication and time-delayed contract execution. This work contributes a cryptographically secure, user-centric identity framework ensuring data sovereignty, recoverability, and interoperability within the Ethereum ecosystem.
Blockchain systems provide a decentralized and fault-tolerant infrastructure for maintaining a shared transaction ledger without relying on a trusted central authority. Nakamoto consensus, in particular, enables open participation and robust agreement in permissionless environments. However, these benefits typically rely on broad data replication, which requires participants to download and propagate large volumes of transaction data and can therefore impose substantial communication overhead. This thesis proposes and analyzes a bandwidth-efficient data recoverability protocol for Nakamoto consensus using erasure-coded sampling. Instead of requiring every participant to download a full transaction batch, the protocol allows an operator to encode a large transaction batch, called a mega transaction, into coded chunks and publish a compact cryptographic commitment on chain. Participants verify sampled coded chunks and cast PoW-bound votes on their validity. The Nakamoto consensus layer then determines whether the mega transaction should be accepted as recoverable, so that it can be reconstructed and verified later if a dispute arises. The main focus of this thesis is to formalize the recoverability failure event: the event that the protocol incorrectly accepts a mega transaction as recoverable even though honest participants do not collectively hold enough valid coded chunks for reconstruction. We derive conservative analytical bounds on the probability of this event and use these bounds to formulate a utility-based parameter-selection problem under a target security requirement. Monte Carlo estimates validate the analytical bounds, and numerical results illustrate the tradeoff between recovery communication overhead and confirmation latency.
Multi-cloud computing is becoming a prominent paradigm to improve scalability, flexibility, reliability and costeffectiveness by leveraging services from multiple cloud providers. But distributed resource management with strong security is a big challenge in multi-cloud scenarios, which are heterogeneous and dynamic. This review paper provides an all inclusive overview on various multi-cloud architectures, deployment models,resource allocation techniques, optimization methods, and security assurance mechanisms. It covers the major resource allocation strategies such as provisioning, scheduling, load balancing, resource scaling and intelligent optimization through machine learning and metaheuristicalgorithms to optimize resource utilization and Quality of Service (QoS). Additionally, the article delves into significant security methods for protecting decentralized cloud systems, including authentication, authorization, encryption, intrusion detection, trust management, and zero-trust designs. Also, through the comparison of the most recent literature, the current research trends, challenges and limitations for optimizing resources while keeping security in mind are pointed out. According to the review, combining AI-powered optimisation with sophisticated security frameworks has the potential to enhance the performance, resilience and reliability of multi-cloud environments. Last but not least, the paper outlines future research avenues for explainable AI, federated learning, blockchain-based trust management, energy-efficient resource allocation, and autonomous cloud orchestration to enable secure, scalable, and sustainable next-generation multi cloud computing environments.
The rapid growth of digital education and online recruitment has significantly increased the demand for reliable academic credential verification. Conventional certificate verification methods are often centralized, time-consuming, and susceptible to document forgery, unauthorized modification, and administrative delays. To address these challenges, this paper presents a Blockchain-Enabled Decentralized Framework for Secure Academic Certificate Issuance and Real-Time Verification. The proposed framework utilizes Ethereum blockchain technology through Solidity smart contracts to establish an immutable and transparent repository of certificate records, ensuring that issued credentials cannot be altered without detection. A SHA-256 cryptographic hashing mechanism is employed to generate unique digital fingerprints for each certificate, while Firebase Authentication and Cloud Firestore provide secure identity management and efficient off-chain metadata storage. The user interface is developed using React.js, enabling educational institutions to issue certificates and allowing employers, universities, and other stakeholders to verify credentials instantly through a simple web-based platform. During verification, the system recomputes the certificate hash and compares it with the blockchain record to detect tampering and validate authenticity in real time. Experimental evaluation on a local Ethereum network demonstrates reliable certificate issuance, rapid verification with sub-second response times, secure transaction handling, and effective resistance against certificate forgery. The proposed framework enhances transparency, trust, and operational efficiency while minimizing manual verification efforts. Furthermore, its modular architecture facilitates future migration to public blockchain networks and decentralized storage platforms, making it suitable for scalable deployment across educational institutions and digital credential ecosystems.
Cloud computing infrastructures are facing serious risks from Distributed-Denial-of Service attacks, which include historically high attack volumes and ineffectiveness of conventional defensive strategies. The usefulness of blockchain based security measures in detecting and preventing DDoS attacks on cloud computing infrastructure is covered in this paper. Analyzed a hybrid approach that integrated distributed ledger technology with smart contracts for the identification of attack patterns across 50 enterprise cloud environments over a period of 18 months. Our results show a reduction of false positives by as much as 87% for blockchain-based validation compared to the conventional approach and a 94% success rate in the detection of advanced DDoS variants. The response time remained, on average, around 2.3 seconds during the high-volume attack in comparison to traditional centralized solutions. The results in the paper gives an idea that an immutable and distributed consensus characteristic based on blockchain provides robust defenses against modern DDoS threats. This work represents a growing body of evidence supporting the validity of incorporating blockchain into the architecture of the next generation of cloud-based security.