Abdul Razzaq

Context: The blockchain technology has become a secure, transparent, and decentralized infrastructure in data handling and its potential in the education sector has gained more and more attention especially in securing academic records, preventing credential fraud, and enhancing confidence in the verification procedures. Nonetheless, regardless of this interest, there is a lack of synthesis of the way in which blockchain is being implemented into real educational environment and the challenge that hinder its use. Objectives: The objective of this study is to conduct a systematic review of applications of blockchain in education, determine the main areas of its implementation, evaluate the advantages and limitations mentioned in the literature, and offer recommendations to subsequent research and real‐world implementation. Methods: The systematic literature review was carried out according to the methodology suggested by Okoli and Schabram. A total of 64 peer‐reviewed studies published between 2017 and 2025 were analyzed. Results: The results showed that blockchain is mostly utilized in credential and certificate management, microcredential and credit transfer, competency and assessment tracking, and secure collaborative e‐learning, with other applications in copyright protection and decentralized examination systems. Compared with conventional educational technologies, blockchain enables tamper‐evident records, independently verifiable credentials, and reduced verification costs through cryptographic auditability and decentralized trust. Contributions: This review provides a consolidated evidence base on blockchain‐enabled education, highlighting realistic implementation opportunities, such as QR‐hash diplomas and inter‐institution credit exchanges, while emphasizing the need for privacy‐preserving architectures and shared governance standards. The findings support researchers, practitioners, and policymakers to assess and promote safe, reliable, and effective blockchain‐based learning ecosystems.

Infectious disease network dismantling is crucial for controlling disease spread in social and biological systems. One effective strategy is dismantling the network of disease transmission by identifying and targeting key individuals or behavioral hubs. Existing approaches often assume complete and accurate network data. This data is rarely available in real-world scenarios. This lack of data poses challenges in mitigating infectious disease spread. In, addition, these approaches overlook the effects of missing or hidden links, and consequently, many non-essential individuals are unnecessarily targeted, leading to suboptimal control of the epidemic spread. In this chapter, we introduce the Infectious Disease Network Dismantling Algorithm (IDND), which leverages missing link prediction and node centrality context to identify minimal critical nodes for efficient dismantling. Specifically, this work explores how to mitigate the spread of a pandemic by focusing interventions on a small subset of individuals, despite having partial knowledge of the network.

Context: Metaverse is an emerging technology that synchronizes physical and virtual things. It is used to communicate and simulate the virtual world with the physical world through human actions in real-life scenarios. Combining blockchain and metaverse technologies produces an archetype shift in the educational technology domain regarding online certification, largely due to the impact of synchronizing educational technologies. The combined technology elevates the security measure, ensures transparency, enhances accountability, and reduces costs for the online certification process. Proposed Solution: The suggested solution (MetaEduTech) accelerates the certificate verification process by (i) extenuating the risks of misuse by leveraging decentralized storage of the InterPlanetary File System (IPFS), (ii) securing the certificate, and (iii) providing the metaverse environment for certification. We perform experiments and evaluate the MetaEduTech solution by deploying a blockchain-based smart contract model on Ethereum on the Microsoft Windows platform. Results and Implications: The evaluation results show (i) the efficiency of the query response (5 ms–50 ms), (ii) and the performance of the query execution (CPU utilization between 2%–6%). The findings in this research underscore the effectiveness of the proposed solution with the potential to modernize the certification exam process. The proposed solution and its evaluation can provide insights into how to address the persistent issues surrounding certificate authenticity related to academic verification in a metaverse environment.

Advances in the healthcare sector need to secure efficient and decentralized systems to handle the large number of images and test reports. Traditional cloud-based healthcare systems pose crucial challenges, such as higher maintenance costs, significant storage demand, and, most importantly, privacy concerns. This chapter introduced the comprehensive patient-centric system for decentralized storage, secure medical data sharing, integrating blockchain technology and distributed file systems. The healthcare system leverages the IPFS and Ethereum blockchain to empowering scalable privacy protection of globally available storage of medical metadata. The framework enhances the accessibility and usability of incorporating a mobile offering for the patients, hospitals, and other stakeholders to interact with the decentralized system through the blockchain-integrated mobile application.This chapter provides an innovative approach to addressing the healthcare centralized data management limitations while ensuring patient privacy and data security.

Metaverse—a three‐dimensional computational environment—combines physical and virtual reality to enable social relationships and immersive experiences by mimicking real‐world scenarios. Metaverse is considered the third wave of the internet revolution (exploiting Web 3.0), leveraging upcoming technologies such as extended reality and artificial intelligence shaping a new era of human–‐machine interactions. In recent years, increased research and development on educational technologies (EduTech) based on blockchain technology has seen substantial growth of metaverse‐based solutions within the higher education context. This research aims to synergize blockchain technology and metaverse environments to conduct online exams (metaExam) in a trustworthy, reliable, and secure way. The synergy between blockchain and the metaverse brings various benefits, such as improved security, cost effectiveness, and increased efficiency in the online examination process. One of the central features of the proposed solution metaExam is to leverage cryptographic protocols via blockchain to control data access, making verification faster and protecting against misuse. Exam scores and grades are stored on a blockchain ledger using a digital signature method to enhance security. We validated the proposed solution by testing a prototype on the Ethereum platform using the Sepolia Testnet network using Microsoft Windows environment. Evaluation results indicate (i) query response time (10–50 ms), (ii) and query execution performance (CPU utilization between 1%–5%) offering computationally feasible solution. This research contributes by integrating blockchain and metaverse technologies to offer a solution metaExam that can offer improved security and immersive user experience for exam management. The proposed solution and its validation can provide insights into transforming online exams, offering a fresh perspective on addressing concerns about exam grade authenticity and verifying academic credentials in EduTech.

A rising number of educational solutions based on blockchain technology have been designed. Students and other authorities responsible for verifying certificates are very concerned about the authenticity of academic credentials, either because the institutions that issue them no longer exist or because they do not keep adequate records. Blockchain technology has much to offer in education, including its high level of security, improved data access control, low cost, improved accountability, identity authentication, transparency, increased trust, and improved efficiency in managing student records. We proposed a decentralized blockchain‐based secure platform for the storage of academic certificates and student assessments with double encryption. Apart from speeding up the verification process, it will increase the safety of personal education data and assessments of all kinds of misuse. The data would only be accessed using a stakeholder's private key, and storing documents on a blockchain would increase security. We proposed a framework to offer a secure channel for educational resources. We are storing documents over blockchain utilizing an IPFS distributed data server. We give a thorough explanation of the system development, design, and evaluation of the suggested solution in terms of security and cost. Finally, we put the proposed framework to the test by deploying a smart contract prototype on the Ethereum TESTNET network in a Windows environment. The study's findings revealed that the proposed method is effective and feasible.

Scalability is one of the system’s characteristics highlighted in the recent literature, and it is directly related to issues that are encountered in state-of-the-practice technology. The scalability of a system is challenging because monolithic legacy systems are hard to scale due to the high level of component dependencies. To the best of our knowledge, there is no published work available that can identify the components from a monolithic legacy system in the context of dependent and independent components and scale them accordingly. The main contribution of this paper is the proposal of a novel approach for the exclusive identification of dependent and independent monolithic legacy system components. The proposed approach also helps to remove the dependency among components of monolithic legacy systems. As a result, it establishes a precise method that identifies all the components of an application and removes the dependency among components, helping to increase the scalability of the resulting application. This approach was validated by several experiments, and the key findings were the identification of dependent and independent components, the identification of relationships among components, and the identification of the abstract level architecture of the monolithic legacy system. In future work, the proposed method will be enhanced toward the recovery of the whole system’s architecture.

The use of blockchain technology is expanding in various industries, including finance, supply chain management, food, energy, IoT, and healthcare. The article aims to address the challenges of complex medical procedures, large-scale medical data management, and cost optimization in the healthcare industry. By employing blockchain technology, the article aims to enhance data security and privacy while ensuring the integrity and efficiency of the healthcare system. This article focuses on the application of blockchain technology in the healthcare system by reviewing the existing literature and proposing multiple workflows for better data management. These workflows were implemented using the Ethereum blockchain platform and involve complex medical procedures such as surgery and clinical trials, as well as managing a large amount of medical data. The feasibility of the proposed system is analyzed in terms of associated costs, and a model-driven engineering approach is used to recover the architecture of traditional healthcare systems. The aim is to provide stakeholders in the healthcare system with better healthcare services and cost optimization. The solution being proposed automates interactions between different parties involved. Smart contracts were created using Solidity language, and their functions were tested using the Remix IDE. This paper illustrates that our smart contract code was designed to avoid common security vulnerabilities and attacks. To test the framework, a prototype of the smart contract was deployed on an Ethereum TESTNET blockchain in a Windows environment. This study found that the proposed approach is both practical and efficient.

As Internet of Things (IoT)-based systems become more prevalent in the era of data-driven intelligence, they are prone to some unprecedented challenges in terms of data security and systems scalability in an era of context-sensitive data. The current advances in IoT-driven data sensing and sharing rely on third-party sources of information (TTPs) that gather data from one party, then transmit it to the other. As a result of TTPs’ involvement, such IoT systems suffer from many issues including but not limited to security, transparency, trust, and immutability as a result of the involvement of the company. Moreover, a multitude of technical impediments, such as the computation and storage poverty of IoTs, privacy concerns, and energy efficiency, enhances the challenges for IoTs. To address these issues of IoT security, we propose a blockchain-enabled open IoT data-sharing framework based on the potential of the interplanetary file system (IPFS). We have used a case study-based approach to evaluate the proposed solution. It is submitted that the proposed scenario is implemented by building smart contracts in Solidity and deploying them on the local Ethereum test network, using the Solidity programming language. With the implementation of smart contracts on the blockchain for access roles in IoT data sensing, the proposed solution advocates for a blockchain-based approach to data security for IoT systems that makes use of smart contracts for access roles.