Alisha Abbasi Shaikh, Aman Ullah Khan, Mohammad Fahad Kirmani, S. Ali
The rapid digital transformation of healthcare systems has significantly improved the storage, accessibility, and management of patient information; however, it has also introduced serious challenges related to data security, privacy, and trust. Traditional centralized medical record systems are vulnerable to single points of failure, unauthorized access, and data breaches, which may compromise sensitive patient data. This paper proposes a decentralized framework for secure medical records management using blockchain technology. The system utilizes a distributed ledger to store medical data in a tamper-resistant and immutable manner, ensuring integrity and transparency. Cryptographic techniques are employed to encrypt patient data and enforce secure access control, allowing only authorized users to retrieve or update records. Additionally, smart contracts are used to automate access permissions and eliminate the need for intermediaries, improving efficiency. By removing dependence on a central authority, the proposed approach enhances reliability, security, and trust among stakeholders while ensuring privacy protection and controlled data sharing in modern healthcare environments.
Social media has become a transformative force for entrepreneurship, enabling startups to access global markets, engage directly with customers, and build brands with limited resources. This study explores the role of social media in entrepreneurial success, focusing on platform-specific strategies, consumer engagement, and challenges faced by startups. Using qualitative methods, including thematic analysis of interviews and case studies, the study identifies key themes such as data-driven decision-making, authenticity, and leveraging influencer partnerships. Findings suggest that social media acts as a critical resource for startups, offering opportunities for growth while requiring adaptability to navigate challenges like algorithm changes and content saturation. The study integrates theoretical frameworks such as the Resource-Based View (RBV) and Dynamic Capabilities Framework to contextualize the findings and provide actionable insights for entrepreneurs. Future research directions include examining emerging platforms like Web3 and AI-driven social media strategies to further advance the understanding of digital entrepreneurship.
Intherapidlyevolvingdigitallandscape,freelancing platforms face significant challenges due to a lack of transparency,trust,andcentralizedcontrol.Thispaperpresents the design and implementation of a blockchain-powered web- based project management system integrated with a visual data dashboard. The proposed system leverages Ethereum smart contractstoensuresecure,tamper-proofuserregistration,project posting, bidding,assignment, work submission, payment release, and rating. The backend is developed using Django, while blockchain integration is achieved via Web3.py, enabling secure and transparent interactions. The platform provides real-time analyticsonusers,jobstatus,fundmovement,andratingsthrough a dashboard. The solution enhances trust, transparency,and de- centralization,provingeffectiveforfreelanceprojectecosystems
Blockchain technology and decentralised finance (DeFi) are reshaping financial services by eliminating intermediaries, automating transactions through smart contracts, and expanding global access to capital. Initially designed for cryptocurrencies, blockchain has evolved into a transformative ecosystem that optimises resource management and democratises finance. This study explores the impact of blockchain and DeFi on financial services, focusing on adoption opportunities and challenges. It addresses key gaps in the literature, particularly platform interoperability, security in decentralised environments, and adoption in emerging markets. Using the PRISMA 2020 methodology, the research ensures a rigorous selection and critical evaluation of scientific articles to identify trends, barriers, and potential developments. Findings indicate that blockchain and DeFi can enhance financial inclusion, improve transparency, and strengthen decentralisation. However, they also present challenges such as regulatory uncertainty, technical complexity, and security risks. Overcoming these obstacles requires innovative solutions and strategic collaboration among governments, financial institutions, and technology developers. By shedding light on these dynamics, the study contributes to a deeper understanding of how blockchain and DeFi can reshape financial services, paving the way for a more inclusive, efficient, and secure financial ecosystem.
This study aimed to examine the role of blockchain technology in transforming digital marketing within the emerging Web3 environment, with a specific focus on its impact on consumer trust and marketing efficiency. The research primarily investigated the relationship between blockchain technology as the independent variable and digital marketing transformation as the dependent variable, while also considering consumer trust and marketing efficiency as key outcome variables. A quantitative research design was adopted, and data were collected from 250 respondents, including digital platform users and marketing professionals, using a structured questionnaire based on a 5-point Likert scale. Statistical analyses, including reliability, correlation, and regression, were conducted to test the proposed hypotheses and evaluate the relationships among variables. The findings revealed that blockchain technology had a significant positive impact on digital marketing transformation (β = 0.68, p < 0.001) and consumer trust (β = 0.72, p < 0.001). Digital marketing transformation significantly influenced marketing efficiency (β = 0.70, p < 0.001). The results also indicated that consumer trust played a mediating role in enhancing marketing efficiency, highlighting the importance of transparency and data security in digital environments. The study provides practical implications for organizations by emphasizing the adoption of blockchain-based marketing systems to improve transparency, reduce operational inefficiencies, and strengthen consumer trust. It also highlights the strategic importance of decentralized platforms in shaping the future of digital marketing. References Basal, M., & Şarkbay, Ö. F. (2026). Web3-driven digital marketing and consumer protection. 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Blockchain technology and smart contracts are revolutionizing legal and commercial transactions worldwide. These innovations enhance efficiency, automation, and security in contract execution while reducing reliance on intermediaries. However, their adoption presents legal challenges related to enforceability, regulatory oversight, and dispute resolution. This research examines the UAE's legal framework governing blockchain and smart contracts, analysing their recognition under contract and commercial law, as well as the roles of key regulatory UAE authorities, including the Securities and Commodities Authority (“SCA”) and the Virtual Assets Regulatory Authority (“VARA”).
Blockchain technology stands at the forefront of transforming digital communication, addressing entrenched issues like data breaches, privacy erosion, and centralized control. This systematic literature review synthesizes insights from over 50 peer-reviewed articles, industry reports, and case studies published between 2018 and 2025, focusing on blockchain's core principles and their application to secure messaging, decentralized social networks, IoT ecosystems, and telecommunications. Drawing on databases such as Google Scholar, IEEE Xplore, and Scopus, we identify key benefits—decentralization for resilience, immutability for integrity, and cryptography for confidentiality—while critically examining barriers like scalability trilemma, regulatory conflicts, and user adoption hurdles. Emerging trends, including zero-knowledge proofs and modular architectures, signal a path toward scalable Web3 paradigms. The review concludes with societal implications for trust-building and data sovereignty, proposing research directions for hybrid models that balance innovation with compliance. This work underscores blockchain's potential to foster a user-empowered, equitable communication landscape.
The rapid expansion of digital payment ecosystems has transformed global financial transactions through the convergence of Artificial Intelligence (AI) and the Internet of Things (IoT). Smart point-of-sale terminals, wearable payment devices, biometric authentication systems, and cloud-integrated banking platforms generate massive volumes of real-time transactional data, demanding intelligent, scalable, and secure processing frameworks. Conventional security architectures struggle to address evolving cyber-financial threats, including adaptive fraud schemes, adversarial attacks, identity compromise, and decentralized finance exploits. An integrated AI–IoT security paradigm offers a resilient solution by enabling real-time anomaly detection, adaptive risk scoring, device-level authentication, and continuous behavioral monitoring across distributed financial infrastructures. This book chapter presents a comprehensive exploration of AI-driven analytics, reinforcement learning–based adaptive decision models, federated learning for privacy-preserving intelligence, and lightweight deployment strategies tailored for resource-constrained IoT financial devices. A unified Zero-Trust architecture combined with blockchain-assisted auditability strengthens transaction integrity while ensuring regulatory compliance and data governance alignment. Emphasis is placed on explainable AI mechanisms to enhance transparency in automated financial decision-making and to support accountability within high-stakes payment environments. Emerging research challenges, including adversarial robustness, energy-efficient model optimization, and cross-platform interoperability, are critically examined to establish a forward-looking framework for secure digital finance. The proposed perspective advances a scalable and privacy-aware AI–IoT integrated security architecture designed to mitigate financial risk, reduce false positives, and enhance trust in decentralized and intelligent payment systems. This contribution aims to support researchers, financial technologists, and policy architects in developing next-generation digital payment infrastructures capable of sustaining security, efficiency, and transparency in an increasingly connected global economy.
Blockchain technology has been widely heralded as a transformative tool capable of establishing trust in digitized supply chains through cryptographic finance, immutability, and decentralized ledgers. However, empirical evidence and recent analyses suggest that these technological mechanisms alone are insufficient to generate holistic trust among supply chain stakeholders. This study critically examined why blockchain adoption often failed to produce sustained trust, despite enhancing transparency, traceability, and data integrity. A qualitative, theory-driven methodology was employed, analyzing peer-reviewed literature across supply chain management, financial technology, and digital governance domains. The findings revealed that trust remained deeply rooted in social, relational, and institutional dimensions, which blockchain technologies could not replace. Off-chain data dependencies, governance gaps, regulatory ambiguities, and power asymmetries emerged as key factors undermining trust formation. Furthermore, blockchain often displaced trust from human and institutional actors to opaque technical systems, reducing accountability and stakeholder confidence. The study concluded that blockchain should be conceptualized as a supportive infrastructure for trust rather than a substitute for relational and institutional mechanisms. Recommendations included integrating blockchain with hybrid governance models, legal frameworks, and inclusive participation strategies to enhance trust resilience. The study also identified future research directions focusing on cross-industry comparisons, socio-technical interactions, and emerging blockchain alternatives. These insights contribute to a more nuanced understanding of the socio-technical limits of blockchain in supply chain digitization and highlight the critical role of governance and institutional alignment in sustaining trust.
Blockchain technology has evolved from its initial application in cryptocurrencies such as Bitcoin to a versatile decentralized infrastructure supporting decentralized finance (DeFi), digital identity systems, smart contracts, and Web3 ecosystems. Despite its transformative potential, the rapid expansion of blockchain platforms has significantly increased the security attack surface, exposing networks to threats such as double-spending, Sybil attacks, smart contract vulnerabilities, transaction laundering, and large-scale financial fraud. At the same time, the emergence of quantum computing introduces a fundamental challenge to classical cryptographic mechanisms particularly Elliptic Curve Digital Signature Algorithm (ECDSA) and RSA that form the backbone of blockchain authentication and transaction verification. This paper presents a comprehensive study of Machine Learning (ML) techniques and Post-Quantum Cryptographic (PQC) frameworks for strengthening blockchain security and threat detection. The study reviews supervised, unsupervised, and deep learning models used for fraud detection, anomaly identification, smart contract vulnerability analysis, and blockchain transaction monitoring. In parallel, it examines quantum-resistant cryptographic algorithms emerging from the NIST post-quantum standardization process, including lattice-based, hash-based, and code-based schemes, and evaluates their suitability for blockchain environments. Furthermore, the paper analyzes the limitations of ML-based security mechanisms and the practical challenges of integrating PQC into decentralized infrastructures, including scalability, key size overhead, and performance trade-offs. A comparative analysis highlights that ML enhances adaptive behavioral threat detection, while PQC ensures long-term cryptographic resilience against quantum attacks. Therefore, the study emphasizes the importance of a hybrid ML–PQC security model that combines intelligent anomaly detection with quantum-resistant cryptographic protection. Finally, the paper identifies key research challenges and outlines future directions toward building scalable, adaptive, and quantum-secure blockchain ecosystems capable of supporting next-generation decentralized applications.
Vaishnavi S. Jadhav, Sakshi S. Niphade, S. S. Mahale
Secure data sharing has become a critical challenge in modern digital ecosystems due to increasing data breaches, lack of transparency, and dependence on centralized authorities. Traditional data-sharing mechanisms often suffer from single points of failure, unauthorized access, and limited trust among participating entities. Blockchain technology, with its decentralized, immutable, and cryptographically secure architecture, offers a promising solution to these challenges. This research paper explores the application of blockchain technology for secure data sharing, emphasizing its ability to ensure data integrity, confidentiality, transparency, and access control. The study examines how features such as distributed ledgers, smart contracts, and consensus mechanisms can be leveraged to manage data ownership, enforce access policies, and prevent tampering. Various blockchain-based data-sharing models are reviewed across domains such as healthcare, finance, and supply chain management. The paper also discusses key challenges, including scalability, privacy preservation, interoperability, and regulatory concerns. Finally, future research directions are highlighted to enhance the efficiency and practicality of blockchain-enabled secure datasharing systems
D. K. Shareef, Shaik Abdulla, Pulagari Maruthi Prasad, Paseddula Ajay · 5 authors
Supply chain finance (SCF) is an important tool in maintaining liquidity, confidence, and business continuity in the multi-stakeholder supply networks. Nevertheless, traditional SCF systems have weak real time inventory tracking, centralized trusting, transaction settlement lag and high vulnerability to fraud. This paper suggests an intelligent supply chain finance model based on the Blockchain -IoTdriven supply chain model by incorporating real-time inventory monitoring, secure decentralized transaction management and predictive decision support, to overcome such limitations. IoT sensors keep an eye on the level of inventory and environmental conditions, and blockchain technologies provide immutable, transparent, and resistant to alterations financial records on the form of smart contracts. A predictive analytics module is developed based on a Long Short-Term Memory (LSTM) that predicts the inventory demand and financial risk fluctuations to enable proactive decision-making. An interactive dashboard consolidates real-time and predictive knowledge to be able to make automated and data-led financial decisions. Experimental assessment proves that the developed framework has 95% accuracy when inventory, time and cost of transactions are significantly lowered, fraud cases are reduced, and the accuracy of demand forecasting is enhanced. This study validates the idea that IoT-blockchain-predictive analytics can offer a scalable, secure, and intelligent solution to next-generation supply chain finance systems.
This study presents a blockchain-based enabling autonomous nursing professional development framework, known as BCeANPDF. The framework aims to enhance transparency, security, and professional autonomy in nursing credential management. It is grounded in the principles of competency-based human resource management. Blockchain and smart contract technologies are integrated to support independent recording, verification, and management of professional and non-professional credentials by nurses. At the same time, hospital human resource administrators continue to have the authority to conduct regulatory oversight and ensure compliance. The framework employs a three-layer architecture that includes controller, service, and repository components. These components coordinate access control, data processing, and blockchain-related operations. Seven smart contracts are designed within the framework. They automate credential ownership verification, credential updates, and compliance review processes. This design strengthens data integrity and reduces administrative workload. A prototype was implemented in a private blockchain environment to evaluate system performance. The results demonstrate stable and efficient operation. The average on-chain processing time per credential was 12.3 s. Median query latency ranged from 5 to 9 ms. These findings confirm that the framework achieves scalability and responsiveness comparable to Ethereum, while preserving data privacy and immutability. By combining decentralized trust mechanisms with credential management practices, the BCeANPDF framework offers a practical approach to supporting autonomous professional development. It also facilitates flexible management of the nursing workforce. Overall, the framework contributes to the development of transparent and competency-oriented healthcare institutions without increasing operational complexity.
Jauhar Abbas, Syed Shameel Ahmed Quadri, Adeel Ansari, Seema Ansari
This study examined the impact of blockchain integration on supply chain finance (SCF) performance, transparency, and trust. With traditional SCF systems facing challenges such as delayed payments, information asymmetry, and transaction inefficiencies, blockchain technology offers decentralized, immutable, and real-time data sharing capabilities to enhance financial operations. A quantitative cross-sectional research design was employed, and data were collected from 312 professionals working in manufacturing, retail, and logistics sectors. Descriptive analysis, exploratory factor analysis, and structural equation modeling (SEM) were applied to assess relationships among blockchain adoption, SCF performance, transparency, and trust. Results indicated that blockchain adoption significantly improved SCF performance (mean = 4.08), transaction verification speed (mean = 4.02), and cost efficiency (mean = 3.95). Transparency increased as stakeholders accessed real-time and verifiable financial data (mean = 4.05), while trust among supply chain partners was strengthened (mean = 4.04) due to the system’s immutable and auditable records. These findings demonstrated that blockchain acts as a strategic enabler for enhancing operational efficiency, information sharing, and stakeholder confidence in SCF operations. The study contributes to theory and practice by providing empirical evidence of blockchain’s role in fostering performance and relational benefits in supply chains. Recommendations include strategic blockchain implementation, employee training, governance alignment, and continuous monitoring of performance metrics. Future research could explore cross-border adoption, integration with emerging technologies, and long-term impacts across different industries.
The global logistics sector is confronted with crucial data reliability challenges wherein traditional centralized systems have a 15-20% manual error rate and are highly susceptible to counterfeiting. In this regard, the current research proposes Sentinel, a decentralized supply chain tracking framework utilizing the Polygon Proof-of-Stake blockchain coupled with smart contracts in Solidity for granting immutability to data governance. It follows a hybrid architecture wherein on-chain cryptographic verification is coupled with MongoDB for high-speed off-chain data retrieval. Extensive performance testing was performed on a simulated supply chain network with 10,000 transaction cycles of creation, transfer, and delivery. It shows that Sentinel has been able to achieve 100% in data integrity, thus rejecting all 500 unauthorized ledger modifications attempted during security stress testing. In terms of efficiency, the proposed framework minimized data retrieval latency to less than 180 ms, which was an improvement of 92% compared to traditional decentralized architectures. Additionally, it minimized the transaction cost to roughly ₹0.45/unit, thus offering a cost reduction of about 99.9% compared to traditional Ethereum Layer-1 implementations.
Abstract The rapid evolution of computer technology is changing digital ecosystems, business processes, governmental operations, and how humans use computers to perform tasks. This paper is a comprehensive analysis of modern computer technology trends, including advancements in artificial intelligence; cloud computing; edge computing; the internet of things (IoT); 5G networks; blockchain; cybersecurity; quantum computing; emerging technologies such as immersive technologies and robots; big data; and sustainable computing. In this extensive review of how these advances work together to drive digital transformation, this paper synthesizes current research from academic literature with real-world applications of computer technologies from industry. The paper includes discussions regarding the emergence of generative AI and multimodal ML methods, explainable AI, and intelligent automation as new methods to generate better decision-making results and innovations within the business sector. It includes descriptions of multi-cloud/hybrid architectures, serverless computing, edge AI, and fog computing as ways to achieve low-latency scalable infrastructure; and ultimately describes use cases for using IoT with AI-enabled analytic platforms for smart cities; IIoT; and real-time data ecosystems. Cybersecurity subjects discussed in this paper include innovations such as Zero Trust Architecture, AI-based threat detection, and quantum-resistant cryptography. Emerging technology paradigms like blockchain-powered decentralized apps (DApps), Web3 environments, quantum algorithms, AR/VR/MR technologies, and smart robots are examined for potential to change organisations and challenges encountered during their adoption. 'Green computing' strategies are discussed in terms of developing low carbon power systems, creating carbon aware IT systems, and developing sustainable IT practices that reduce environmental impact. This study also explores advances in the fields of human computer interaction, accessibility technology, and ethical governance frameworks, with a focus on society's responsibility to develop inclusive and responsible technological products. The research has revealed multiple challenges that prevent sustainable technology development from progressing, including: scalability; interoperability; regulatory compliance; security threats; digital equity; and adapting to the workforce's new skill sets caused by this shift to sustainable technology. Therefore, developing sustainable technology will require multi-disciplinary co-operation; ethical guidance/path; strategic governance; and continuous innovation in technology development. By combining a technical assessment of IT technology along with a social perspective; an umbrella of knowledge will form to forecast how IT technologies will advance during the period referred to as the era of Intelligent Connected Systems.
Bayan Arab, Maizaitulaidawati Md Husin, Suzilawati Kamarudin
HRMARS - Blockchain is a promising, unique technology that enables decentralized, secure, and tamper-proof transactions. Blockchain technology is rapidly growing and being applied across various fields. Supply chain finance is an emerging financing model that optimizes financial flows between enterprises, as banks connect upstream and downstream entities. Traditional supply chain finance faces numerous challenges, such as double financing fraud and information asymmetry. Blockchain technology enhances the performance of conventional supply chain finance by improving the transparency and security of all financial transactions, thus elevating the quality of supply chain information. This improvement can lead to better overall supply chain performance and sustainability. Scholars have not thoroughly investigated the unique role of Blockchain technology in sustainable supply chain finance practices. This paper examines the effect of Blockchain-based supply chain finance systems on sustainable supply chain performance. The conceptual framework was developed based on the Resource-Based View theory (RBV) to underpin the role of Blockchain technology application in the supply chain finance to improve the supply chain performance. In addition, this paper investigates how Blockchain technology's trust and security features can enhance traditional supply chain finance practices, address challenges, and improve capital flow, ultimately contributing positively to overall supply chain performance. Finally, it emphasizes that the area of research on blockchain-based supply chain finance has potential for exploration.
The rapid growth of digital technologies has encouraged organizations to adopt management systems that prioritize transparency, security, and efficiency. Blockchain has emerged as a transformative innovation capable of reshaping conventional management processes through its decentralized and tamper-resistant architecture. This study analyzes the implementation of blockchain in enhancing transparency and security within management systems. A literature review approach was used to examine recent scholarly publications related to blockchain applications across various organizational settings. The findings indicate that blockchain significantly improves data integrity, prevents fraud, and strengthens accountability through distributed ledgers, cryptographic mechanisms, and smart contracts. However, challenges such as scalability limitations, infrastructure readiness, regulatory uncertainties, and limited technical literacy remain major obstacles. This study concludes that blockchain presents substantial benefits, but its effective implementation requires a comprehensive and strategic approach to ensure organizational readiness and long-term sustainability.
Blockchain drives digital transformation in entrepreneurship by enhancing innovation, operational efficiency, and sustainable business practices. Alongside this development, big data analytics for sentiment insights plays an essential role in understanding public perception and consumer behavior, enabling strategic and data-driven decision-making. Blockchain's decentralized structure promotes transparency, security, and trust among stakeholders, supporting scalable and accountable business ecosystems. This study systematically reviews big data-driven sentiment analysis methods applied to blockchain-based entrepreneurial contexts such as ICOs, DeFi, and Web3 startups. It maps data sources, machine learning and deep learning architectures, and sentiment analysis tasks, explaining how sentiment insights contribute to investment evaluation, market prediction, and risk mitigation. Although blockchain offers significant benefits, its integration faces major challenges including ecosystem readiness, regulatory uncertainty, and limited workforce capability. This study highlights blockchain's role in improving competitiveness and sustainability, while identifying barriers and strategic responses needed to support innovation in digital entrepreneurship.
The recent trends in the development of digital financial services have increased the demand for efficient protection of banking transactions and information. This empirical research aims to study how the blockchain revolution has impacted on the improvement of security and efficiency of banking operations. Conducting the research at the secondary level, the study relies on validated sources of data to establish the degree of impact of blockchain by means of econometric modeling on finance data security. The findings show that blockchain adoption leads to better security outcomes, including decreased fraud rates, increased compliance, and increased efficiency. This paper employs theoretical frameworks, including distributed ledger technology (DLT) and practical byzantine fault tolerance (PBFT) to carry out the evaluation and hence provide an appreciation of how blockchain is revolutionizing the financial industry. The findings of this research will be useful to institutions to implement blockchain as the foundation for safe and efficient banking solutions required by the digital world.
It is an exploration of a decentralized social media platform, which uses blockchain and Web3 technologies to scale up privacy, security, and trust within users. The architecture uses Next.js as the front-end, solido as the smart contracts, IPFS as a distributed storage, and Web3.js to connect with the blockchain. It introduces canonical social-networking features, including user registration, content upload, like, comment and share. Notably, it keeps ownership of data to users, unlike the traditional centralized social-media platforms. The irreversibility of blockchain together with encryption makes sure that the content cannot be altered and the information about users is not at risk of unauthorized access. The system eliminates the possibility of exploiting the central level of control and increases the level of transparency. The performance appraisals indicate that the suggested platform provides better privacy, higher data security, and user agency than the mainstream networks. However, the issues of scalability and mass user adoption are still present, and the research should be further developed. This paper highlights how blockchain will reinvent social media, creating a just, transparent, and user-centric digital economy. Altogether, the study advances the discussion on decentralized social networks and demonstrates that blockchain can improve the level of trust and data protection in the process of online communication.
Dr Mamata Jagannathji Rathi, Miss. Sanika Yogiraj Parankar
This research investigates the role of supply chain automation through the integration of Blockchain technology, Smart Contracts, and the Internet of Things (IoT). The study explores how decentralized ledgers can automate critical workflows, including instant payment release, real-time inventory reconciliation, and automated compliance auditing. By utilizing IoT sensors to feed environmental data into a blockchain-backed system, companies can trigger automated responses that reduce human error and operational overhead. The findings indicate that this transition accelerates "speed-to-market" and fosters a self-correcting, autonomous ecosystem capable of responding to disruptions in real-time. While the research acknowledges significant implementation barriers—such as high initial capital expenditure, cybersecurity risks, and the "SME gap"—it concludes that the evolution toward an automated, transparent, and green supply chain is essential for resilience. Ultimately, the paper argues that automation should not be viewed as a replacement for human labor, but as a tool to liberate workers for high-level system orchestration. This study provides a strategic roadmap for organizations navigating the shift from Industry 4.0 to a human-centric, sustainable Industry 6.0 framework
Abdullah Ayub Khan, Abdullah M. Baqasah, Majed Alsafyani, Hamed Alsufyani · 6 authors
The revolution in Blockchain Distributed Ledger Technology (BDLT) is changing conventional structures and creating previously unattainable opportunities across a variety of industrial fields. This study explores new developments, opportunities, and trends while tackling important issues that highlight the revolutionary potential of BDLT. For secure, automated, and dependable ecosystem management, it focuses on innovations like Denaturalized Finance (Defi), chaincode, and BDLT interface with the Internet of Things (IoT). The investigation of hybrid blockchain models, which combine the benefits of private and public blockchains, is a novel component of this research. It provides a customized strategy to guarantee improved scalability, privacy, and performance. Conversely, this study highlighted the critical function of Hyperledger, a modular framework that makes enterprise-level blockchain solutions possible. Thus, Ethereum is a flexible platform with strong chaincode capabilities that facilitate the creation of Distributed Applications (DApps). Such opportunities for advancements are evaluated closely in order to demonstrate how they contribute to practical uses and innovations unique to a given sector. To improve worldwide acceptance, the paper also presents Systematic Literature Review (SLR) in order to demonstrate the existing innovative frameworks, especially Hyperledger Technology (HT) for resolving constraints such as consensus protocols for energy efficiency and adaptive regulatory models. For technological experts, industrial developers, and third-party policymakers seeking to harness BDLT's disruptive capabilities while navigating its complexity, this paper offers new viewpoints and practical insights to help close the gap between theoretical innovation and real-world applications.
The rapid growth of blockchain technologies has enabled decentralized applications based on smart contracts and distributed consensus. However, the increasing number of attacks exploiting protocol logic and network dynamics highlights the limitations of traditional, static security mechanisms. This study proposes an adaptive cognitive security model based on a Q-learning agent to enhance the protection of blockchain protocols. The agent is designed to analyze transaction behavior, assess risk levels, and dynamically select appropriate countermeasures. The proposed approach is evaluated through a dual experimental framework combining large-scale simulation using SimPy and execution on a private blockchain environment implemented with Ganache. Experimental results show a detection rate of approximately 70%, no observed false positives, a response time close to one second, and a very low operational gas cost. These results demonstrate that reinforcement learning can effectively improve the adaptability and responsiveness of blockchain security mechanisms while preserving network performance and economic viability. The study confirms the potential of cognitive and adaptive approaches for building more resilient and autonomous blockchain security systems.