Blockchain Papers

Musharraf N. Alruwaill, Saraju P. Mohanty, Elias Kougianos

No abstract is available for this record.

I Gede Agus Krisna Warmayana

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.

Zihao Liu, Huaping Wu

No abstract is available for this record.

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.

Gang Han, Yan Ma, Zhong-Liang Zhang, Yuxin Wang

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.

Hui Tian, Nan Gan, Fang Peng, Hanyu Quan · 6 authors

No abstract is available for this record.

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.

Rupali Sachin Vairagade, Priya Parkhi, Yogita Hande, Bhagyashree Hambarde

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.

Yan Liu

The rapid digital transformation across various sectors has intensified the need for secure, automated management systems to handle sensitive data with integrity and privacy. Traditional systems often struggle to securely manage and authenticate larg e volumes of data, leaving it vulnerable to unauthorized access and breaches. This paper presents an intelligent information management system based on blockchain technology, designed to enhance data security, integrity, and automated access control through decentralized storage, cryptographic algorithms, and smart contracts. The proposed system leverages blockchain's decentralized ledger to offer a tamper-resistant, distributed storage solution, minimizing risks of data tampering and enhancing transparency. Smart contracts add automation to access control and data verification processes, reinforcing system robustness and reducing the potential for human error. This paper's contributions include developing a blockchain-based intelligent data management framework, evaluating its efficacy in real-world scenarios, and demonstrating its advantages over traditional centralized approaches in terms of security, privacy, and operational automation. This study provides a foundational approach to enhance the security and autonomy of digital information systems, enabling more resilient data management infrastructures.

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.

Xiaoxuan Hu, Xiao Chen, Zhenjiang Dong, Yanfei Sun · 7 authors

With the rapid development of the blockchain industry and the widespread adoption of IoT devices, which are often deployed on different blockchains, the need for cross-chain value and data exchange has become increasingly important. However, existing cross-chain transactions face challenges such as low efficiency, high costs, and insufficient security. To address these issues, this paper proposes a cross-chain transaction scheme based on aggregated zero-knowledge proofs. This scheme optimizes the allocation of computing resources in a distributed environment and employs a multi-branch balanced Merkle tree to construct aggregated zero-knowledge proofs, significantly reducing the verification costs for batch cross-chain transactions.To further enhance data privacy and integrity, this paper introduces the Secure Aggregated Block Verification (SABV) algorithm and improves system consistency and reliability through the Local Merkle Tree Rebalance (LMTR) algorithm. In addition, this paper analyzes the basic security of the proposed scheme when implemented in adversarial environments and provides countermeasures for common threats in distributed systems. Finally, simulations and actual deployment on the Ethereum test network were conducted. The results indicate that our method reduces CPU usage, memory consumption, and time expenditure by 50.10%, 99.03%, and 99.47%, respectively, during the generation of zero-knowledge proofs for batch cross-chain transactions. At the same time, building upon the performance improvements of the existing zero-knowledge proofs, our approach also demonstrates significant enhancements in contract deployment and cross-chain transaction efficiency.

V. Ananthakrishna, Chandra Shekhar Yadav

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.

Xiaojun Zhang, Qing Liu, Bingyun Liu, Yuan Zhang · 5 authors

Data auditing contributes to checking the integrity of outsourced data, promoting the vigorous development of cloud storage services. In actual scenarios, such as migration of electronic medical records or data transfer of enterprise mergers and acquisitions, it always require data auditing to help clients with dynamic data migration and integrity checking. In this paper, we present an efficient dynamic certificateless outsourced data auditing mechanism supporting multi-ownership transfer (CDA-MOT), addressing the issue of key escrow and without needing complex certificate management. By integrating a certificateless multi-signature on the same data file into the construction of a homomorphic authenticator based on the Lagrange inverse Multinomial theorem, CDA-MOT not only achieves integrity verification but also enables clients to transfer ownership rights and responsibilities for multi-ownership data in collaboration with cloud servers. Utilizing blockchain systems to store necessary data conversion and update records, as well as smart contracts to fulfill auditing tasks, CDA-MOT owns the characteristics of openness, transparency, accountability, and decentralized public auditing. Besides, CDA-MOT could be further applied in the extension of dynamic update operations, even if outsourced data have been transferred. The security analysis and performance evaluation have demonstrated the feasibility of CDA-MOT in the secure deployment of cloud storage.

Biswanath Saha

No abstract is available for this record.

Maher Boughdiri, Takoua Abdellatif, Chirine Ghédira

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.

Vo Nhut Tin, Nguyen Tien Thuan, Le Nhut Anh, V. H. Khanh · 5 authors

No abstract is available for this record.

Ritu Mishra, Sandip Kumar Goyal, Sanjeev Rana

No abstract is available for this record.

Godfrey Wandwi, Diana Mjema

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.

Xin Tan, Xiaoxin Lin, Anxue Yin, Le Wang · 5 authors

No abstract is available for this record.

Chang Liu, Wenzhang Zhu, Zhongyuan Yao, Xueming Si · 5 authors

No abstract is available for this record.

Shanu Khare, S. K. Wasim Haidar, Navjot Singh Talwandi, Sukhdev Singh · 5 authors

No abstract is available for this record.

Abiodun Okunola, Beloved Joy

No abstract is available for this record.

Kaleru Vikram, Sunil Kumar, Ashwin Satyanarayana, Rakesh Kumar

No abstract is available for this record.