The increasing adoption of multi-cloud database systems has transformed enterprise data management, enabling enhanced scalability, reliability, and cost efficiency.However, managing databases across multiple cloud providers introduces significant challenges, including data fragmentation, latency, security vulnerabilities, and inconsistencies in synchronization.Traditional approaches to database management struggle to provide seamless interoperability, fault tolerance, and resilience against failures, necessitating innovative architectural solutions.This paper explores the design and implementation of resilient multicloud database systems, integrating Distributed Ledger Technology (DLT) for enhanced data integrity, fault tolerance mechanisms to ensure high availability, and cross-platform synchronization techniques for maintaining consistency across heterogeneous cloud environments.DLT, particularly blockchain, offers a decentralized approach to data validation, reducing the risk of tampering and unauthorized modifications while enabling transparent and auditable transactions.Fault tolerance strategies, including redundancy, self-healing systems, and predictive analytics, play a crucial role in mitigating system failures and ensuring business continuity.Additionally, cross-platform synchronization mechanisms, such as conflict-free replicated data types (CRDTs) and real-time consistency protocols, are explored to address latency and data consistency challenges across cloud infrastructures.By integrating these technologies, organizations can enhance the resilience, security, and operational efficiency of multi-cloud database architectures.This paper provides a comprehensive framework for implementing adaptive database management solutions, leveraging AI-driven automation, blockchain-based security, and advanced fault recovery models.The findings highlight best practices for enterprises aiming to achieve scalable, reliable, and fault-tolerant multi-cloud database environments.Future research directions include the role of edge computing in multi-cloud synchronization, quantum-safe cryptographic techniques for DLT security, and AI-driven predictive failure management in cloud-native databases.
In materials science, utilizing globally distributed data is essential for advancing materials design through technologies such as materials informatics. Achieving this requires secure, transparent, and efficient methods for managing and sharing materials data. This study explores the potential of blockchain, smart contracts, Non-Fungible Tokens (NFTs), and the InterPlanetary File System (IPFS) within the Web3 framework for managing and sharing materials data. We developed and tested a prototype data management system using a thermophysical properties dataset. This system facilitates NFT minting, data storage on IPFS, and secure, traceable ownership transfer of NFTs, enhancing traceability, transparency, and security in data sharing. Additionally, decentralized systems employing blockchain technology, smart contracts, NFTs, and IPFS effectively address vulnerabilities associated with single points of failure common in traditional centralized systems. This study offers valuable insights for future materials design, demonstrating the efficacy of blockchain and related technologies in managing and sharing materials data.
Nadeem Yaqub, Jianbiao Zhang, Muhammad Irfan Khalid, Weiru Wang · 7 authors
Electronic health record transmission and storage involve sensitive information, requiring robust security measures to ensure access is limited to authorized personnel. In the existing state of the art, there is a growing need for efficient access control approaches for the secure accessibility of patient health data by sustainable electronic health records. Locking medical data in a healthcare center forms information isolation; thus, setting up healthcare data exchange platforms is a driving force behind electronic healthcare centers. The healthcare entities access rights like subject, controller, and requester are defined and regulated by access control policies as defined by the General Data Protection Regulation (GDPR). In this work, we have introduced a blend of policy-based access control (PBAC) system backed by blockchain technology, where smart contracts govern the intrinsic part of security and privacy. As a result, any Subject can know at any time who currently has the right to access his data. The PBAC grants access to electronic health records based on predefined policies. Our proposed PBAC approach employs policies in which the subject, controller, and requester can grant access, revoke access, and check logs and actions made in a particular healthcare system. Smart contracts dynamically enforce access control policies and manage access permissions, ensuring that sensitive data is available only to authorized users. Delineating the proposed access control system and comparing it to other systems demonstrates that our approach is more adaptable to various healthcare data protection scenarios where there is a need to share sensitive data simultaneously and a robust need to safeguard the rights of the involved entities.
Patient privacy data security is a pivotal area of research within the burgeoning field of smart healthcare. This study proposes an innovative hybrid blockchain-based framework for the secure sharing of electronic medical record (EMR) data. Unlike traditional privacy protection schemes, our approach employs a novel tripartite blockchain architecture that segregates healthcare data across distinct blockchains for patients and healthcare providers while introducing a separate social blockchain to enable privacy-preserving data sharing with authorized external entities. This structure enhances both security and transparency while fostering collaborative efforts across different stakeholders. To address the inherent complexity of managing multiple blockchains, a unique cross-chain signature algorithm is introduced, based on the Boneh-Lynn-Shacham (BLS) signature aggregation technique. This algorithm not only streamlines the signature process across chains but also strengthens system security and optimizes storage efficiency, addressing a key challenge in multi-chain systems. Additionally, our external sharing algorithm resolves the prevalent issue of medical data silos by facilitating better data categorization and enabling selective, secure external sharing through the social blockchain. Security analyses and experimental results demonstrate that the proposed scheme offers superior security, storage optimization, and flexibility compared to existing solutions, making it a robust choice for safeguarding patient data in smart healthcare environments.
Yang Liu, Ru Huo, Ningjie Gao, Cheng Chi · 5 authors
In order to address the challenges encountered in the current Industrial Internet of Things scenarios, such as single points of failure, difficulties in ensuring data privacy and integrity, and a lack of access control, a blockchain-based data security exchange architecture was proposed. To ensure the privacy of industrial data, a data exchange process based on public key encryption and keyword search was introduced. Industrial data is encrypted multiple times and uploaded to the blockchain network. Users retrieve ciphertext from the cloud server after obtaining the key through the blockchain and then decrypt it. To achieve flexible access control, a zero-knowledge proof-based access control mechanism was proposed, utilizing Pedersen commitments and zero-knowledge proofs for access permission issuance, validation, and revocation. Additionally, various forms of smart contracts were proposed for secure data exchange, user authentication, access authorization, and data integrity verification. Finally, a system prototype was built and experimental results confirmed the superiority of the proposed approach.
ABSTRACT The rapid advancement of financial technology (FinTech) has led to the integration of advanced technologies like data science, blockchain, cloud computing, and artificial intelligence. However, trust evaluation remains a critical challenge in dynamic landscape. Existing trust evaluation methods often neglect key aspects of timeliness, reliability, and non‐invasiveness, leading to imprecise trust assessments and insufficient detection of malicious user behavior. This paper introduces a robust four‐layer architectural framework with the blockchain layer, edge computing service layer, cloud computing service layer, and terminal user application layer leveraging blockchain technology for authentication and trust evaluation. Blockchain technology transforms FinTech data into linked data, ensuring data security and decentralization during information transfers. A novel hybrid consensus protocol combining Proof of Elapsed Time (PoET) and Proof of Stake (PoS) is introduced to enhance the efficiency and security of the blockchain. Extensive simulation experiments have demonstrated significant improvements in data security, reliability, and accuracy of trust assessments compared to existing methods. This paper presents a comprehensive solution for enhancing trust evaluation in FinTech, emphasizing timeliness, reliability, and non‐invasiveness of assessments.
Mathias Hall-Andersen, Mark Simkin, Benedikt Wagner
Towards building more scalable blockchains, an approach known as data availability sampling (DAS) has emerged over the past few years. Even large blockchains like Ethereum are planning to eventually deploy DAS to improve their scalability. In a nutshell, DAS allows the participants of a network to ensure the full availability of some data without any one participant downloading it entirely. Despite the significant practical interest that DAS has received, there are currently no formal definitions for this primitive, no security notions, and no security proofs for any candidate constructions. For a cryptographic primitive that may end up being widely deployed in large real-world systems, this is a rather unsatisfactory state of affairs. In this work, we initiate a cryptographic study of data availability sampling. To this end, we define data availability sampling precisely as a clean cryptographic primitive. Then, we show how data availability sampling relates to erasure codes. We do so by defining a new type of commitment schemes which naturally generalizes vector commitments and polynomial commitments. Using our framework, we analyze existing constructions and prove them secure. In addition, we give new constructions which are based on weaker assumptions, computationally more efficient, and do not rely on a trusted setup, at the cost of slightly larger communication complexity. Finally, we evaluate the trade-offs of the different constructions.
Ahmed Ayoub Bellachia, Mouhamed Amine Bouchiha, Yacine Ghamri-Doudane, Mourad Rabah
Blockchain-based Federated Learning (BFL) is an emerging decentralized machine learning paradigm that enables model training without relying on a central server. Although some BFL frameworks are considered privacy-preserving, they are still vulnerable to various attacks, including inference and model poisoning. Additionally, most of these solutions employ strong trust assumptions among all participating entities or introduce incentive mechanisms to encourage collaboration, making them susceptible to multiple security flaws. This work presents VerifBFL, a trustless, privacy-preserving, and verifiable federated learning framework that integrates blockchain technology and cryptographic protocols. By employing zero-knowledge Succinct Non-Interactive Argument of Knowledge (zk-SNARKs) and in-crementally verifiable computation (IVC), VerifBFL ensures the verifiability of both local training and aggregation processes. The proofs of training accuracy and aggregation are verified on-chain, guaranteeing the integrity and auditability of each participant's contributions. To protect training data from inference attacks, VerifBFL leverages differential privacy. Finally, to demonstrate the efficiency of the proposed protocols, we built a proof of concept using emerging tools. The results show that generating proofs for local training and aggregation in VerifBFL takes less than 81s and 2s, respectively, while verifying them on-chain takes less than 0.6s.
In the rapidly evolving landscape of cloud computing, the burgeoning growth and centralization of data exacerbate security vulnerabilities, necessitating robust and scalable cryptographic solutions. This paper introduces the QP-ChainSZKP framework, a novel architecture that amalgamates Quantum-Secure Cryptographic Algorithms with Zero-Knowledge Proof Management to shield cloud environments against both classical and emerging quantum threats. The proposed QP-ChainSZKP framework effectively integrates advanced cryptographic techniques, enhancing the security protocols and compliance measures required for robust cloud operations. This ensures not only adherence to high-security standards but also provides strong protection against data breaches and unauthorized access, crucial for maintaining data integrity and confidentiality in cloud environments. We employ a dual approach in our methodology by simulating and rigorously testing the framework to evaluate its security, scalability, and performance metrics. The experimental results demonstrate a significant enhancement in transaction throughput and reduction in latency, corroborating the framework’s capability to manage high throughput cloud applications effectively. Specifically, the framework achieves a throughput improvement of 20% and a latency reduction of 30% under peak load scenarios, establishing its efficacy in handling dynamic cloud environments. Notably, the QP-ChainSZKP framework addresses future quantum computational threats by modifying existing cryptographic practices used in public clouds, setting a pioneering standard for using advanced cryptographic technologies in cloud security. Our study contributes a scalable, quantum-resistant solution tailored for extensive cloud applications, marking a substantial advancement in cloud computing security frameworks that can meet the imminent global security requirements.
The scalability of blockchain storage presents a critical bottleneck that hinders the widespread adoption of this transformative technology. Addressing this challenge is paramount to realize the full potential of blockchains. This paper presents a systematic review of the literature (SLR) that focuses on storage scalability challenges and solutions in the context of blockchain technology. The SLR meticulously extracted 131 primary articles from prominent scientific databases, including Scopus, IEEE Xplore, ScienceDirect, Google Scholar, and Web of Science. The synthesis of these papers enables an in-depth analysis of storage scalability issues in blockchain networks. Highlights key factors contributing to these issues, identifying eight key factors, including distributed storage, immutability, decentralization, programmability, block size, transaction volume, node capacity, and replication strategy. Then, it examines the latest state-of-the-art solutions proposed to address them. These solutions are broadly categorized into (1) on-chain solutions and (2) off-chain solutions. Furthermore, the paper evaluates storage optimization strategies in light of the blockchain trilemma, which highlights the inherent balance between scalability, security, and decentralization. By providing a comprehensive overview of existing research, this study aims to offer valuable insights and pathways for future research and development of scalable blockchain storage solutions while preserving its core principles.
With the rapid expansion of the Internet of Things (IoT), the integrity of connected devices has emerged as a critical concern. Malicious actors increasingly target vulnerabilities in device firmware, communication protocols, and system configurations, compromising the reliability and trustworthiness of data. Traditional security mechanisms have struggled to scale with the decentralized and heterogeneous nature of IoT networks. To address this challenge, this paper proposes a blockchain-based framework designed to safeguard the integrity of IoT devices. The framework leverages a lightweight consensus mechanism and a distributed ledger to establish tamper-evident records of device behavior and configuration states. Additionally, smart contracts are employed to automate verification processes, detect anomalies, and enforce compliance with integrity policies in real time. The case study conducted demonstrates how this approach enables secure attestation of device states while minimizing computational overhead, making it suitable for resource-constrained environments. The proposed framework represents a step forward in embedding trust into the fabric of IoT systems through decentralized integrity assurance mechanisms.
S Remya, Manu J. Pillai, Preethi Ann Jacob, Sruthi Suresh · 5 authors
Certificateless Proxy Re-Encryption (CL-PRE) eliminates certificate management and private key exposure risks for blockchain data sharing, but existing schemes have critical security vulnerabilities and performance limitations. This research work presents comprehensive security analysis and performance evaluation of CL-PRE schemes for blockchain applications. The primary contribution is discovering a critical public key replacement attack against Wang et al.’s CL-PRE scheme, where Type I adversaries completely compromise message confidentiality by substituting legitimate public keys with adversary-controlled keys, enabling ciphertext decryption without private keys and violating IND-CCA security. The systematic performance evaluation of pairing-free PRE schemes for blockchain environments is conducted through extensive benchmarking of three schemes implemented in Go. Results show self PRE achieves superior security but incurs 13.7% higher execution time than certificateless schemes. To address vulnerabilities, this work proposes a secure CL-PRE framework with enhanced validation mechanisms. The Ethereum implementation reduces on-chain storage by 40% while maintaining provable security. The framework achieves 14.1% better performance than existing secure schemes and reduces gas costs by 14.3%. These findings establish security benchmarks and practical guidelines for blockchain developers, emphasizing rigorous cryptographic analysis importance for decentralized access control advancement.
B a c k g r o u n d . The study addresses the rapid expansion of data processed within distributed digital ecosystems, where traditional centralized storage models introduce risks due to single points of failure and limited transparency in monitoring changes. The need is emphasized for secure, resilient, and verifiable mechanisms capable of protecting sensitive information in dynamic multi-user environments. M e t h o d s . A hybrid blockchain architecture integrating public and private ledgers is developed. A mathematical model of decentralized data protection is formalized, digital signatures, smart contracts, and cryptographic hashing are applied, and a functional prototype is implemented using Hyperledger Fabric with the RAFT consensus algorithm to validate secure access and ensure transaction integrity. R e s u l t s . Analytical modeling and simulation experiments involving networks of 10–100 nodes demonstrate increased system resilience by approximately 20–25% while maintaining stable transaction latency. The implemented model reliably detects unauthorized access attempts and modification actions and shows compliance with international standards, including ISO/IEC 27001 and GDPR. C o n c l u s i o n s . The findings confirm that blockchain-based architectures can significantly enhance data security in distributed environments and surpass traditional centralized protection models. The proposed framework ensures integrity, transparency, and traceability with minimal performance degradation, making it suitable for financial, governmental, medical, and corporate systems. Further development is considered promising in the context of integrating machine learning, quantum resistant cryptography, and cloud infrastructures.
The rapid evolution of digital identity verification demands solutions that balance security, privacy, and efficiency. The electronic know your customer (eKYC) is a technological integration for client identification. It automates the process, reducing costs related to traditional know your customer (KYC). This includes eliminating paper-based document management, reducing manpower needs, and minimizing human errors. This systematic literature review (SLR) uses the preferred reporting items for systematic reviews and meta-analyses (PRISMA) model to investigate the revolutionary potential of blockchain-based electronic KYC (eKYC), focusing on self-sovereign identity (SSI) and Decentralized Identifiers (DID). The evaluation summarizes the current state by critically assessing 44 selected research works from an initial pool of 367. Our findings show that decentralized eKYC improves security with tamper-proof credentials and cryptographic verification. SSI and DID give users control over their data and selective disclosure. However, there are key limitations: 1) a focus on financial applications, ignoring Internet of Things (IoT) integration; 2) a lack of comprehensive technical analysis on scalability and interoperability; and 3) limited real-world case studies on regulatory compliance and challenges. This work combines insights from research and industry, highlighting the need for regulatory collaboration, hybrid architectures for scalability, and user-centric design. In addition, most identity management solutions are based on Ethereum (33%), followed by Hyperledger (18%). Around 51% of solutions use smart contracts, with banking (23%) and the financial industries (19%) being the primary adopters. It emphasizes the importance of standardized eKYC protocols, technical evaluations, and interdisciplinary collaboration for practical adoption across sectors.
The rise of quantum computing threatens to break many of the cryptographic systems that secure today’s digital world. In response, researchers are developing new tools designed to remain secure in a post-quantum future. Most of the promising candidates for post-quantum digital signatures rely on security assumptions based on lattices or properties of hash functions. Another promising approach transforms secure multi-party computation protocols into zero-knowledge proofs, which are then turned into digital signatures. This technique, known as multi-party computation in-the-head (MPCitH), offers strong security properties and flexibility for distributed applications. This thesis investigates whether MPCitH digital signatures can be efficiently adapted for use by two cooperating parties to jointly produce a signature. Here we show how to construct two-party signatures based on syndrome decoding in-the-head (SDitH) signatures. We propose a provably secure scheme that achieves the smallest known communication overhead among two-party MPCitH signatures, while resulting in a signature size approximately double that of a single-prover variant. This result provides a new data point in the design space of multi-party MPCitH signatures and post-quantum digital signatures in general.
The rapid growth of the metaverse has led to a scattered ecosystem in which digital assets are deployed on different blockchain platforms. This disintegration creates significant challenges for interoperability, as users need secure, decentralized, and privacy-preserving protocols to enable interoperability between chains. Existing solutions typically depend on centralized exchanges or third-party relays, introducing a single point of failure and potential privacy risks. We propose MAM (Metaverse Asset Management), a novel user-centric protocol utilizing zkSNARK technology (Zero-Knowledge Succinct Non-Interactive Argument of Knowledge) that enables seamless movement of metaverse assets across various blockchain platforms. MAM’s architecture ensures privacy by generating all zkSNARK proofs locally on the user’s machine, ensuring that sensitive data, including private keys and asset metadata, never leave the device. The protocol employs a secure one-time setup to distribute the global circuit-specific proving key, ensuring the permanent destruction of toxic-waste data. Experimental evaluation demonstrates that MAM achieves a constant and minimal proof size (192 bytes), low gas cost (281,107 Gas per verification), and an end-to-end asset transfer latency under 15 seconds, outperforming recent alternatives such as MetaOpera and MAP. Static security analysis confirms the robustness of MAM’s smart contracts against the most significant vulnerability types. This research enhances the state-of-the-art of privacy-preserving and scalable cross-metaverse interoperability, providing a practical approach for fully decentralized digital asset management and transfer across the Metaverse.