Utilizing Blockchain Technology to Secure Database from Unauthorized Modifications

This study explores the transformative impact of blockchain technology on data integrity and security in digital environments. Through a comprehensive assessment of data integrity metrics across prominent blockchain networks, including Bitcoin, Ethereum, and Hyperledger Fabric, we unveil nuanced differences in immutability and reliability. Our security analysis delves into the cryptographic strength and resistance to unauthorized access, showcasing the outstanding security features of Hyperledger Fabric and Bitcoin, with Ethereum exhibiting commendable yet moderate security levels. The discussions underscore the multifaceted nature of blockchain technology, emphasizing the importance of selecting a platform aligned with specific use cases. Hyperledger Fabric and Bitcoin emerge as strong contenders for applications requiring high integrity and robust security, while Ethereum offers a reliable but moderate alternative. As blockchain technology continues to evolve, this study provides valuable insights for practitioners and researchers, guiding the strategic selection of blockchain platforms to harness their transformative potential in diverse digital environments.

With the rapid growth of digital data and inter-connected devices, the integration of blockchain and Internet of Things technology offers a promising chance to revolutionize data management approaches. With today's global connectivity, the management and securing of ever-increasing amounts the amount of data produced by Internet of Things (IoT) devices is becoming an increasing concern. This study investigates a new solution to address such a concern by integrating blockchain technology into IoT systems. The aim is to develop a strong framework that takes advantage of the decentralized and secure character of blockchain and the wall-to-wall connectivity offered by the IoT. This integration is intended to address important needs such as data integrity, The integration aims to tackle crucial issues like data integrity, privacy, and unauthorized access. With the connectivity and sensing capabilities of the IoT, along with the blockchain technology of decentralized consensus and immutable ledgers, businesses are able to develop secure systems to retrieve, transfer, and store such data. In the experiments conducted on the Ethereum blockchain platform, it has been found that the blockchain and IoT technology solution not only secures data but also facilitates information management. The experiment results demonstrate that the proposed solution is able to protect against tampering, increase the transparency of transactions, and to minimize the chances of unauthorized access. The framework is scalable and highly adaptable, and it is therefore a promising solution for various applications. This framework employs an innovative approach to ensure secure and efficient data management.

This study investigates the groundbreaking application of blockchain technology in the realm of student physical fitness testing within colleges and universities. The focus is on constructing a secure, transparent, and traceable data management system to enhance the accuracy and reliability of physical fitness assessments. Using literature review to establish a theoretical basis, logical analysis to clarify technical principles, and cross-disciplinary methods to integrate various perspectives, the study provides an in-depth analysis of how blockchain can be seamlessly incorporated into the student physical fitness testing framework. Physical fitness testing in colleges typically includes evaluations of various health metrics such as aerobic capacity, muscular strength, flexibility, and body composition. Traditional methods for recording and managing these tests often face challenges related to data accuracy, tampering, and privacy. Blockchain technology, with its immutable and decentralized nature, offers a solution by ensuring that fitness test results are securely recorded and cannot be altered once entered into the system. The proposed blockchain-based system incorporates several key components tailored to the needs of student physical fitness assessments. The system includes an authentication module to verify basic student information and a management module to handle test scores and related health data. By employing advanced encryption methods and blockchain platforms like Bei-hang Chain, the system provides robust data protection, ensuring both the privacy of individual student records and the integrity of the test data. One of the system’s innovations is its ability to offer real-time access and verification of fitness data for all relevant stakeholders-students, educational institutions, parents, and regulatory bodies. This transparency helps in monitoring students’ health trends and in making informed decisions about physical education programs and health interventions. Furthermore, the decentralized nature of the system reduces administrative overhead and mitigates risks associated with centralized data storage. The integration of blockchain technology addresses significant issues inherent in traditional physical fitness testing systems, such as data tampering, unauthorized access, and inaccuracies in test results. By ensuring that fitness data is accurate, unalterable, and accessible, the system provides a reliable basis for evaluating and improving student health and fitness. This advancement not only supports more accurate assessments of students’ physical fitness and health but also facilitates the development of evidence-based policies and programs aimed at enhancing student wellness. In summary, the blockchain-based physical fitness testing system represents a transformative approach to managing student health data. It not only provides strong support for accurately reflecting the physical fitness and health status of contemporary college students, but also provides a solid data basis for the government and relevant departments to make more scientific and reasonable health policies and decisions, and has far-reaching positive significance for improving the physical fitness level of college students.

Purpose: The purpose of this research is to design and implement a secure, transparent, and tamper-proof attendance management system using blockchain technology, specifically leveraging Hyperledger Fabric 2.5 deployed on Ubuntu 24.04. The paper aims to demonstrate how blockchain can efficiently replace traditional attendance systems by providing enhanced reliability, integrity, and auditability. Through practical implementation, the study evaluates performance, ease of use, and scalability, offering insights into blockchain's applicability in educational institutions and workplaces to mitigate common issues associated with traditional attendance tracking methods, such as data tampering, inefficiency, and lack of trust. Methodology: The methodology involves deploying a blockchain-based attendance system using Hyperledger Fabric 2.5 on Ubuntu 24.04. It includes requirements analysis, blockchain network setup, smart contract (chain code) development, and frontend-backend integration using React.js and Node.js. This is followed by rigorous functional and performance testing to ensure transparency, security, scalability, and overall system robustness. Result/Analysis: The analysis of the blockchain-based attendance system demonstrated significant improvements in data security, transparency, and efficiency compared to traditional attendance methods. Transactions executed reliably, achieving an average throughput of approximately 200 transactions per second with minimal latency, validating the scalability of Hyperledger Fabric 2.5 on Ubuntu 24.04. The use of cryptographic certificates ensured robust security, preventing unauthorized access and data manipulation. Additionally, integration of a React.js frontend provided user-friendly interaction, enhancing usability. Performance tests confirmed efficient resource utilization, maintaining stable CPU and memory consumption under varying workloads. Overall, results indicate the system's feasibility for reliable, secure, and scalable attendance management. Originality/Values: This study uniquely integrates Hyperledger Fabric 2.5 with Ubuntu 24.04, creating a practical, secure, and transparent blockchain-based attendance solution. Its originality lies in demonstrating real-world applicability, comprehensive performance evaluation, and detailed system integration insights, contributing valuable knowledge for institutions seeking innovative, decentralized, and efficient alternatives to traditional attendance tracking systems. Type of Research: Experimental-based Research.

The block chain has many unique characteristics, like decentralization, stability, openness and transparency. We can apply block chain in many fields of railway to improve the comprehensive efficiency and benefit, such as railway passenger and freight service, engineering construction, big data sharing and so on. With the gradual completion of data service platform, big data lake and cloud computing in China Railway, these foundations can support the railway block chain application. The paper analyzed the development status and existing problems of block chain at home and abroad. Through the multidimensional analysis for the mainstream block chain platform architecture, the thesis gets the architecture selection of the railway block chain platform. Based on the hyperledger fabric, we propose the technical architecture and overall scheme for the railway block chain service platform respectively. The paper also designs the implementation path for the platform application construction. This research plays an important role and significance in promoting the block chain technology applying and developing in the railway field.

Blockchain is a key technology that has the potential to decentralize the way we store, share, and manage information and data. One of the more recent blockchain platforms that has emerged is Hyperledger Fabric, an open source, permissioned blockchain that was introduced by IBM, first as Hyperledger Fabric v0.6, and then more recently, in 2017, IBM released Hyperledger Fabric v1.0. Although there are many blockchain platforms, there is no clear methodology for evaluating and assessing the different blockchain platforms in terms of their various aspects, such as performance, security, and scalability. In addition, the new version of Hyperledger Fabric was never evaluated against any other blockchain platform. In this paper, we will first conduct a performance analysis of the two versions of Hyperledger Fabric, v0.6 and v1.0. The performance evaluation of the two platforms will be assessed in terms of execution time, latency, and throughput, by varying the workload in each platform up to 10,000 transactions. Second, we will analyze the scalability of the two platforms by varying the number of nodes up to 20 nodes in each platform. Overall, the performance analysis results across all evaluation metrics, scalability, throughput, execution time, and latency, demonstrate that Hyperledger Fabric v1.0 consistently outperforms Hyperledger Fabric v0.6. However, Hyperledger Fabric v1.0 platform performance did not reach the performance level in current traditional database systems under high workload scenarios.

Performance comparison of permissioned and permissionless blockchain by varying workload transaction

This all-encompassing strategy for improving the pharmaceutical supply chain management process places a strong emphasis on responsibility, transparency, and traceability. Role-based access control, secure hashing algorithms, and blockchain (Hyperledger Fabric) technologies work together to reduce the risk of counterfeit medications and guarantee accurate drug monitoring. In a drug traceability system made possible by blockchain technology, every participant in a supply chain is assigned a unique identity and has access to a shared, decentralized database that follows the transit of pharmaceuticals along the supply chain. To ensure data security and integrity, MedGuard uses the SHA-256 hashing technique for data validation and the PBFT (Practical Byzantine Fault Tolerance) consensus algorithm for network node consensus. To maintain the integrity and security of the data, each participant is only permitted to add new records to the database; they are not permitted to edit or remove alreadyexisting records. All things considered, a blockchain-based drug traceability system might greatly improve the quality and safety of pharmaceutical products and help protect patients and the public from the risks associated with fake or tainted drugs. The complete solution is currently accessible as the “MedGuard” online application.”

This scholarly article examines how traditional Point of Sale (POS) software systems in the retail sector can be revolutionized by incorporating blockchain technology. The study aims to improve transactional security using transparent and decentralized mechanisms to re-architect crucial point-of-sale infrastructure. This study tackles issues with fraud, data integrity, and security in retail transactions by utilizing the capabilities of blockchain technology, including smart contracts and distributed ledgers. Choosing the right blockchain platform, putting strong data security measures in place, and ensuring smooth integration with current systems are all essential aspects of the investigation. By strengthening POS systems with blockchain technology, this project aims to reimagine retail transactions in the future altogether

The current digital age, mainly characterized by an economy based upon information technology, demands a data integrity service, even more so because organizations and companies are migrating their services over the cloud. This is not a simple task; it is cumbersome since traditional schemes in databases could be subject to modifications. However, it can be solved using blockchain technology. This paper provides a data integrity verifiability architecture for cloud systems based on blockchain. The architecture provides a mechanism to store events (as logs) within a blockchain platform from any cloud system. Users can then consult data integrity through a microservice, acting as an intermediate server that carries out a set of verification steps within the blockchain, which confirms the integrity of a previously stored log. Our architecture takes advantage of the blockchain strength concerning integrity, providing a traceability track of the stored logs. A prototype system and a case study were implemented based on the proposed architecture. Our experimental results show that the proposed decentralized architecture can be adapted to cloud existing systems that were born without blockchain technology and require a modular and scalable audit characteristic.

BackgroundResearchers have increasingly adopted AI and next-generation sequencing (NGS), revolutionizing genomics and high-throughput screening (HTS), and transforming our understanding of cellular processes and disease mechanisms. However, these advancements generate vast datasets requiring effective data stewardship and curation practices to maintain data integrity, privacy, and accessibility. This review consolidates existing knowledge on key aspects, including data governance, quality management, privacy measures, ownership, access control, accountability, traceability, curation frameworks, and storage systems.MethodsWe conducted a systematic literature search up to January 10, 2024, across PubMed, MEDLINE, EMBASE, Scopus, and additional scholarly platforms to examine recent advances and challenges in managing the vast and complex datasets generated by these technologies. Our search strategy employed structured keyword queries focused on four key thematic areas: data governance and management, curation frameworks, algorithmic bias and fairness, and data storage, all within the context of AI applications in genomics and microscopy. Using a realist synthesis methodology, we integrated insights from diverse frameworks to explore the multifaceted challenges associated with data stewardship in these domains. Three independent reviewers, who systematically categorized the information across critical themes, including data governance, quality management, security, privacy, ownership, and access control conducted data extraction and analysis. The study also examined specific AI considerations, such as algorithmic bias, model explainability, and the application of advanced cryptographic techniques. The review process included six stages, starting with an extensive search across multiple research databases, resulting in 273 documents. Screening based on broad criteria, titles, abstracts, and full texts followed this, narrowing the pool to 38 highly relevant citations.ResultsOur findings indicated that significant research was conducted in 2023 by highlighting the increasing recognition of robust data governance frameworks in AI-driven genomics and microscopy. While 36 articles extensively discussed data interoperability and sharing, AI-model explain ability and data augmentation remained underexplored, indicating significant gaps. The integration of diverse data types—ranging from sequencing and clinical data to proteomic and imaging data—highlighted the complexity and expansive scope of AI applications in these fields. The current challenges identified in AI-based data stewardship and curation practices are lack of infrastructure and cost optimization, ethical and privacy considerations, access control and sharing mechanisms, large scale data handling and analysis and transparent data-sharing policies and practice. Proposed solutions to address issues related to data quality, privacy, and bias management include advanced cryptographic techniques, federated learning, and blockchain technology. Robust data governance measures, such as GA4GH standards, DUO versioning, and attribute-based access control, are essential for ensuring data integrity, security, and ethical use. The study also emphasized the critical role of Data Management Plans (DMPs), meticulous metadata curation, and advanced cryptographic techniques in mitigating risks related to data security and identifiability. Despite advancements, significant challenges persisted in balancing data ownership with research accessibility, integrating heterogeneous data sources, ensuring platform interoperability, and maintaining data quality. Ongoing risks of unauthorized access and data breaches underscored the need for continuous innovation in data management practices and stricter adherence to legal and ethical standards.ConclusionsThese findings explored the current practices and challenges in data stewardship, offering a roadmap for strengthening the governance, security, and ethical use of AI in genomics and microscopy. While robust governance frameworks and ethical practices have established a foundation for data integrity and transparency, there remains an urgent need for collaborative efforts to develop interoperable platforms and transparent data-sharing policies. Additionally, evolving legal and ethical frameworks will be crucial to addressing emerging challenges posed by AI technologies. Fostering transparency, accountability, and ethical responsibility within the research community will be key to ensuring trust and driving ethically sound scientific advancements.

This review chapter provides an in-depth exploration of various aspects of data security, ranging from foundational principles to advanced techniques. It sheds light on the importance of maintaining confidentiality, integrity, and availability of data and presents a comprehensive overview of technologies and methodologies that can be employed to achieve robust data security. In today's digital age, ensuring the security and protection of data has become paramount. This research chapter explores various topics related to data security, including confidentiality, integrity, and availability. It also delves into the role of blockchain technology, zero-trust architecture, secure coding practices, legal and ethical considerations, homomorphic encryption, secure multi-party computation, hash functions and digital signatures, secure communication protocols, cryptocurrency and blockchain security, as well as cryptanalysis and side-channel attacks.It highlights various techniques and technologies that can be employed to protect data confidentiality, including encryption and access control mechanisms. Blockchain technology has emerged as a groundbreaking solution for enhancing data security. Zero-trust architecture challenges traditional security models by adopting a holistic and dynamic approach to data protection. Secure coding practices and DevSecOps play a vital role in developing secure software applications. The chapter investigates the importance of integrating security measures throughout the software development lifecycle. It emphasizes the adoption of secure coding practices and the implementation of DevSecOps methodologies to build resilient and secure software systems. Legal and ethical considerations are crucial when addressing data security. Homomorphic encryption and secure multi-party computation are advanced cryptographic techniques that allow data to be processed securely while encrypted. The chapter examines the principles and applications of these techniques, highlighting their significance in scenarios where privacy is paramount. Hash functions and digital signatures form the backbone of data authentication and integrity. The chapter discusses the properties and applications of hash functions and digital signatures in verifying the integrity and authenticity of data. Secure communication protocols are essential for protecting data during transmission. The chapter explores various secure communication protocols, such as Transport Layer Security (TLS), and examines their role in ensuring data confidentiality, integrity, and authenticity. Cryptocurrency and blockchain security focus on the secure storage and transfer of digital assets. The research chapter investigates the security considerations specific to cryptocurrencies and explores how block chain technology can mitigate vulnerabilities and ensure the trustworthiness of transactions. Cryptanalysis and side-channel attacks are threats to cryptographic systems. The chapter discusses these attack techniques, highlighting their potential risks and the measures that can be taken to counter them.

The integration of blockchain technology in biomedical diagnostics offers a promising solution to the challenges of data security and privacy in infectious disease surveillance. As the digitalization of healthcare systems accelerates, the need to protect sensitive health information becomes increasingly critical. Blockchain, with its decentralized and immutable nature, provides a robust framework for ensuring the integrity and confidentiality of biomedical data. This abstract explores how blockchain technology can be leveraged to enhance data security and privacy in the context of infectious disease surveillance, where rapid and accurate data sharing is essential for effective public health responses. Infectious disease surveillance relies on the collection, analysis, and dissemination of large volumes of data, often shared across multiple institutions and geographical regions. Traditional systems for managing this data are vulnerable to breaches, unauthorized access, and data tampering, which can compromise public health efforts and patient privacy. Blockchain technology addresses these vulnerabilities by enabling secure, transparent, and tamper-proof data exchanges. Each transaction or data entry is recorded in a distributed ledger, accessible only to authorized participants, thus ensuring that the data remains secure and unaltered. Moreover, blockchain’s inherent transparency allows for real-time monitoring and auditing of data flows, which is crucial in the timely detection and response to infectious disease outbreaks. The use of smart contracts within blockchain networks further enhances the automation and efficiency of data management, ensuring that data is only accessed and shared according to predefined rules and conditions. This not only safeguards patient privacy but also builds trust among stakeholders, including patients, healthcare providers, and public health authorities. In conclusion, the integration of blockchain technology in biomedical diagnostics presents a transformative approach to addressing the critical issues of data security and privacy in infectious disease surveillance. By leveraging blockchain's unique features, healthcare systems can ensure that sensitive diagnostic data is protected, thus supporting more effective and secure public health interventions in the fight against infectious diseases. Keywords: Blockchain, Biomedical Diagnostics, Data Security, Privacy, Infectious Disease Surveillance.

Introduction: Blockchain is a rapidly evolving data security practice which employs a growing list of records linked using cryptographic hash of the block proceeding, a timestamp and transaction data. Electronic medical records (EMR) are gaining popularity in health sector. Most of these EMRs are based on relational databases. Data tampering is a known issue found in relational data base approach and it is fairly simple to alter a relational data base record with the administrative privileges. This research explores the potentials of blockchain technology with its resistant to modification of the data, as a tamper protection mechanism for medical records. Methods: A blockchain-based program was developed using Proof-of-Work, to maintain the integrity of the digital record independent of access permissions. This was preceded by a series of interviews with clinicians and EMR administers to understand the possible data tampering in association with paper-based and electronic medical records in the State health sector of Sri Lanka. The blockchain algorithm was applied to the Hospital Health Information Management System (HHIMS) clinical database. A security audit was used to assess the tamper-protection capabilities of the relational database. Results: It was possible to incorporate the blockchain algorithm to the relational database of Hospital HHIMS successfully. An independent blockchain-based data repository was created in association with the native data base of HHIMS. With this approach, a ‘block’ is being created for each new record added to HHIMS database. Hence, the blockchain generated was instrumental in verifying the authenticity of EMR transactions. Conclusion: With the increasing penetration of EMR in health sector, the integrity of the digital stored clinical data is becoming a vital necessity. In centralized database administration, possibility of tampering is high. Clinical data can be counted as ‘high risk’ for such occurrences. The blockchain technology found to be capable of making relational data base tamper-protected by verifying the authenticity of the transactions and data being stored in HHIMS.

Blockchain technology is one of the many disruptive technologies of the Fourth Industrial Revolution that will irrevocably change the way we live and work. These technologies are well embedded in the areas of global finance, health care and defence, to name a few. This review focuses on the relevance of blockchain technology to health care. Blockchain technology will be the unifying platform for sharing patient data currently inaccessible due to the siloed architecture of legacy software systems, and as a result potentially be the basis for precision or individualized patient treatment. It will also strengthen digital security of sensitive patient data that is presently a lucrative target for cyber criminals. In the current COVID-19 environment, clinicians will rely more on telehealth to reduce person-to-person contact. This service can be delivered by the clinical team with confidence in the veracity of the patient data made accessible through the blockchain platform. Smart contracts written on the blockchain platform will reduce the possibility of international humanitarian aid to low- and middle-income countries being misspent. The pharmaceutical supply chain industry is adopting blockchain technology to ensure supply chain provenance. Similarly, the health insurance industry recognizes how the blockchain ecosystem can improve services to its members and expedite reimbursements to clinicians.