Journal of Theoretical and Applied Information Technology
Digital identity management that incorporates blockchain technology provides a safe and effective way to enhance safety systems. Typical issues with older methods of managing identities include data breaches, identity theft, and unauthorized access. This encrypted, decentralized, and irreversible blockchain method ensures 100% accurate identification verification by eliminating any weak points and consolidating power. By further automating the authentication process, smart contracts aim to boost transparency while lowering fraud risks. This paper focuses on how safety-critical settings may leverage blockchain-based digital identity management systems to provide data accessibility, integrity, and privacy. In addition to assisting corporations in meeting and exceeding security laws, blockchain, a distributed ledger technology, gives individuals more control over their data. The suggested method discourses problems like interoperability, scalability and regulatory constraints, paving the way for a more secure and reliable structure. The primary emphasis of this research is on the revolutionary potential of blockchain technology as it pertains to identity management. Therefore, current safety systems will have enhanced dependability, security and efficiency.
Rozina Chohan, Gulshan Naheed, Dr Khakoo Mal, Muhammad Jalil Afridi · 6 authors
The growing popularity of the Internet of Things (IoT) networks has called out a growing need in sound and scalable security. The blockchain technology and its features of decentralization, immutability, and transparency can offer an effective solution to manage key security vulnerabilities, namely, authentication, data integrity, and privacy. This paper discusses the use of blockchain to IoT security, namely: decentralized authentication systems, data integrity management, and the challenge of scalability of large IoT networks. The findings indicate that despite the fact that blockchain can greatly improve security by guaranteeing data integrity and scheme-level device authentication, the performance of blockchain faced with output times of heightened issuance, slow transaction processing, and network constraints only emerge as network sizes rise. It has been proven that Proof of Stake (PoS) performs better than Proof of Work (PoW) regarding energy consumption, transaction latency, and time of recovery after failures due to attacks. Nonetheless, the paper underlines that streamlining blockchain protocols can help to mitigate performance stalls during massive IoT usage. The paper shows that, despite blockchain offering a secure basis to IoT, refinements in autonomous agreements, privacy safety nets, and scalability methods are required to make it an opportunity with broad IoT implementations.
Security in supply chain management plays a critical role in today's global trade networks. This study examines the contributions of Blockchain, based on distributed ledger technology (DLT), in enhancing data integrity, traceability, and resistance to fraud in the supply chain. Blockchain's decentralized structure, by recording each transaction in immutable blocks, minimizes the risks of data manipulation and unauthorized access. Studies in the literature show that, thanks to this technology, transparency and auditability have been strengthened, thus increasing trust in the supply chain. However, scalability issues, high energy consumption, and integration challenges with different stakeholder systems are the main barriers limiting the widespread adoption of the technology. The study suggests that these limitations could be overcome with hybrid DLT architectures and formal assurance methods; additionally, real-world pilot applications and regulatory framework developments could help materialize Blockchain's security and operational efficiency advantages. Thus, Blockchain emerges as an innovative solution with the potential to enhance both the security and efficiency of supply chain processes.
Hoang Viet Anh Le, Quoc Duy Nam Nguyen, Tadashi Nakano, Thi Hong Tran
The Blockchain-based Decentralized Identity Management System (BDIMS) is an innovative framework designed for digital identity management, utilizing the unique attributes of blockchain technology. The BDIMS categorizes entities into three distinct groups: identity providers, service providers, and end-users. The system’s efficiency in identifying and extracting information from identification cards is enhanced by the integration of artificial intelligence (AI) algorithms. These algorithms decompose the extracted fields into smaller units, facilitating optical character recognition (OCR) and user authentication processes. By employing Merkle Trees, the BDIMS ensures secure authentication with service providers without the need to disclose any personal information. This advanced system empowers users to maintain control over their private information, ensuring its protection with maximum effectiveness and security. Experimental results confirm that the BDIMS effectively mitigates identity fraud while maintaining the confidentiality and integrity of sensitive data.
Maintaining integrity and traceability throughout the pharmaceutical cold chain logistics is critical to preserving the efficacy of temperature-sensitive products. Traditional tracking systems lack transparency and accurate monitoring, increasing risks of counterfeiting and adulteration that harm patient health. This paper proposes a blockchain-based cold storage management system that uses smart contracts and IoT sensors to securely monitor real-time temperature and quality parameters for pharmaceutical products. Optimized smart contracts automate processes and enforce predefined conditions, ensuring accountability and reducing transaction cost. Our approach leverages IPFS decentralized storage for transaction data, generating unique SHA-256 cryptographic hashes stored on the blockchain to optimize security and reduce gas costs. Transactions are validated through proof-of-stake consensus. The system provides a secure and transparent solution for pharmaceutical cold storage management while enhancing patient safety and contributing significantly to the medical sector.
This paper proposes the design of electronic medical record system supported by multimedia communication based on blockchain technology. Blockchain technology ensures the secure storage and sharing of patient information through distributed ledger and smart contract algorithm. In this system, smart contracts are used to automatically execute cross-institutional data access control and audit functions to ensure the transparency and compliance of data access. At the same time, this paper introduces multimedia communication technology to support the efficient transmission and sharing of medical data, especially in diagnostic images, videos and voice. Simulation results show that the electronic medical record system based on blockchain has significantly improved data processing efficiency, security and reliability compared with traditional systems.
This research presents the design and implementation of a novel E-banking application based on blockchain technology and enhanced cryptographic practices to enable secure, transparent, and efficient financial transactions. The system deploys an integrated Python-based blockchain for distributed storage of user data, with SHA-256 hashing and Merkle root trees employed to secure transaction integrity and immutability. The sensitive user data which is also stored in local databases is also encrypted with Advanced Encryption Standard (AES), and user login security is reinforced with two-factor authentication from Google Authenticator. The application supports main functions such as user enrollment, loading cryptocurrency, peer-to-peer transactions, and monitoring transaction history, all backed by cryptographic protection such as salted hash password protection and PIN verification. A Solidity smart contract then extends the functionality of the system on the Ethereum blockchain, to enable secure deposit and transfer procedures with real-time balance updating. This integration employs local cryptographic protection with the benefits of blockchain technology’s distributed ledger, to deliver a robust architecture for contemporary electronic banking. The results demonstrate the scalability and tamperproof platform, addressing the solution to privacy and trust in E-banking, and it promises to pave the way for decentralized financial systems.
Anurag Shrivastava, RVS Praveen, Raed H. C. Alfilh, Navdeep Singh · 6 authors
This evolution of the union of blockchain and artificial intelligence (AI) is enabling a completely new paradigm of trust, security, and decentralization of AI models. Blockchain has an immutable ledger and decentralized consensus mechanisms which address critical challenges in AI like data integrity, transparency, and bias mitigation. AI can improve blockchain performance and scalability with the use of optimized consensus algorithms, fraud detection, and smart automation. Helping establish a more safe, explainable, and resilient foundations of AI systems, particularly in fields in which verifiable decisions matter, like as finance, healthcare, and supply chain management. This paper discusses the fusion of blockchain and AI, their complementary strengths, potential applications, and challenges.
Jayshree Chhetri, Amit Kumar Uniyal, Prasenjeet Samanta
Blockchain technology is becoming increasingly significant as an enabler of sustainability and green market strategy through providing resolutions in supply chain transparency, carbon footprint tracking, decentralized finance, and circular economy initiatives. Industry-specific applications like IBM Food Trust (to track food), Power Ledger (to trade renewable energy), KlimaDAO (to tokenize carbon credit markets) illustrate blockchain's quantifiable impact in real applications. Such systems have established enhanced transparency, efficiency, and faith in sustainability processes. Additionally, the convergence with Artificial Intelligence (AI), Internet of Things (IoT), and Big Data analytics further boosts its application for environmental tracking in real-time as well as ESG adherence. This study highlights the need for energyefficient blockchain architecture, regulation transparency, and cross-industrial collaboration for unlocking the full potential of blockchain in facilitating sustainable business models.
The advent of blockchain technology presents trans- formative opportunities for the healthcare sector, characterized by its potential to enhance data security, interoperability, and patient-centric care. This review paper synthesizes current literature on the integration of blockchain within healthcare systems, exploring its capabilities in addressing prevalent challenges such as data breaches, fragmented patient records, and inefficient supply chain management. We identify major benefits in using a comprehensive analysis of different use cases such as EHRs, clinical trials, and pharmaceutical supply chains for improved data integrity, transparency, and operational efficiency. The review will also look at consensus mechanisms, including Proof of Stake (PoS), Practical Byzantine Fault Tolerance (PBFT) and Proof of Authority (PoA), and the primary frameworks: Hyperledger Fabric, Ethereum and VeChain with a view to healthcare use cases. Barriers to implementation discussed in the paper include regulatory concerns, technological complexity, and stakeholder collaboration. This paper aims to guide healthcare practitioners, policymakers, and technologists an overview of leveraging blockchain technology in order to foster a more secure, efficient, and patient- centered healthcare ecosystem by identifying emerging trends and proposing a framework for future research.
Shilpa Kottapally, Sr. Software Development Engineer, Adjudication - Rxclaim developement Application, CVS Health, 2100 E lake cook road , Buffalo grove Illinois 60047, USA
International Journal of Computer Sciences and Engineering (A UGC Approved and indexed with DOI, ICI and Approved, DPI Digital Library) is one of the leading and growing open access, peer-reviewed, monthly, and scientific research journal for scientists, engineers, research scholars, and academicians, which gains a foothold in Asia and opens to the world, aims to publish original, theoretical and practical advances in Computer Science,Information Technology, Engineering (Software, Mechanical, Civil, Electronics & Electrical), and all interdisciplinary streams of Computing Sciences. It intends to disseminate original, scientific, theoretical or applied research in the field of Computer Sciences and allied fields. It provides a platform for publishing results and research with a strong empirical component. It aims to bridge the significant gap between research and practice by promoting the publication of original, novel, industry-relevant research.
Mohammad Sharif Uddin, Md. Alamgir Hossain, Tanvir Mahmud, Suman G. Das
The integration of blockchain with the Internet of Medical Things (IoMT) has emerged as a transformative approach in healthcare, offering enhanced security, privacy, and transparency in managing sensitive patient data. This paper explores the potential of blockchain technology in addressing critical challenges within IoMT-based healthcare systems, including data integrity, interoperability, and decentralization. By reviewing architectural frameworks, real-world applications, and scalability solutions, the study outlines how cryptographic methods, smart contracts, and decentralized storage mechanisms can optimize healthcare services. This highlights ongoing challenges such as standardization, storage demands, and performance trade-offs while proposing advanced cryptographic and architectural solutions. The findings provide a comprehensive roadmap for developing secure and scalable blockchain-integrated IoMT systems that can support real-time, privacy-preserving medical data management.
This study aims at the optimization of the blockchain security modeling algorithms in digital economy smart contracts. From a theoretical perspective, this study proposes a smart contract security enhancement method based on blockchain technology. First., the existing blockchain security mechanism is comprehensively analyzed by reviewing the latest research results. The model focuses on the access control vulnerabilities, consensus mechanism risks and data tampering issues of smart contracts. On this basis, this study designs an optimization algorithm that combines sliding window segmentation, time series feature extraction and multi-layer security strategy. Such fusion operations can improve the security and anti-attack capabilities of smart contracts. In addition, the echo state network (ECHOSN) is introduced to conduct smart contract risk assessment. This operation further enhances the stability of smart contracts. The experiment is verified using real blockchain network data SmartBugs. The results show that the optimization algorithm is significantly better than the traditional method in reducing the risk of data tampering. The accuracy (99.24%) and F1 value (93.67%) can meet the accuracy requirements in real scenarios.
In recent years, several research and development initiatives have focused on developing secure and trustworthy systems for the healthcare industry via pervasive and mobile healthcare (mHealth) solutions. State-of-the-art mHealth solutions primarily rely on centralized storage, such as cloud computing servers, which may escalate the maintenance costs, require ever-increasing storage infrastructure, and pose privacy and security risks to the health-critical data produced, consumed, and transmitted over ad hoc networks. To overcome these limitations, we conducted this study intending to synergize mobile computing (devices to process health-critical data) and blockchain technology (infrastructure to secure storage and retrieval of health-critical data), specifically addressing data security and privacy using a blockchain mHealth system. The research employs an incremental method by (i) developing a framework that acts as a blueprint to architect blockchain-enabled mHealth systems, (ii) implementing a suite of algorithms as a proof-of-concept to automate the framework, and (iii) experimental evaluations to validate the scalability, computation, and energy efficiency of the proposed solution. The proposed framework has been implemented as a frontend using a mobile application interface that exploits the backend via the InterPlanetary File System (IPFS) system and Ethereum blockchain for secure management of mHealth data. We use a case-study-based approach demonstrating how health units, medics, and patients can securely access and distribute health-critical data. For evaluation, we deployed a smart contract prototype on the Ethereum TESTNET network in a Windows environment to test the proposed framework. Results of the evaluation indicate (a) scalability with query response time (range: 10–41 ms), (b) computational performance (CPU utilization: 1.5% – 2.5%), and (c) energy efficiency (gas consumption: 40000 units for 1000 bytes). The proposed solution – framework, algorithms, and experimental evaluation – aims to advance state-of-the-art architecting and implementing cybersecurity mHealth solutions using blockchain technology.
Herman Zahid, Adil Zulfiqar, Muhammad Adnan, Muhammad Sajid Iqbal · 7 authors
This review explores the transformative architecture of Smart Grid 3.0 by integrating cutting-edge technologies. It presents novel architectural frameworks to transform nanogrid, microgrid, and VPP topologies to their Grid 3.0 counterparts. This study systematically analyzes the application of advanced algorithms and technologies across all hierarchical subsystems—nanogrid 3.0, microgrid 3.0, VPP 3.0, and Smart Grid 3.0. These digital technologies have transformative capabilities. The digital twins can perform real-time monitoring, simulation, and predictive analysis; blockchain ensures secure, decentralized energy transactions; and the metaverse creates immersive, interactive environments for system management. This review also explores the role of AI in power grid which is to optimize energy scheduling, fault detection, and energy management. This paper adds to the literature by systematically addressing subsystems of Smart Grid 3.0, including energy generation, transmission, distribution, communication, and storage. Challenges such as interoperability, scalability, data integrity, and cybersecurity are discussed, and solutions are proposed which highlights the need of interdisciplinary approach. These include cyber-attack detection and mitigation mechanisms, advanced simulation tools, and robust policy frameworks. A thorough review of literature enabled this paper to present practical implementation strategies and real-world examples of digital technologies integrated smart grids. By integrating these technologies across hierarchical energy systems, this study establishes a foundation for future research in transforming conventional smart grid infrastructure into a resilient, efficient, and interconnected cyber-physical energy network called Smart Grid 3.0 as the peak of this evolution so far.
The integration of blockchain with 6G networks offers secure, decentralized solutions for emerging consumer applications by addressing key challenges such as device reliability, interoperability, and security. Classical blockchains rely on cryptographic primitives for data integrity and trust, but these are vulnerable to quantum attacks and face scalability challenges in ultra-dense environments. To address these issues, we propose a quantum blockchain framework based on temporally entangled GHZ states, enabling inherent quantum encoding of block linkage and integrity. A four-qubit blockchain data structure is designed and implemented using IBM Q quantum processors, with a quantum hash circuit developed to link consecutive blocks securely. The system’s resilience is validated against two representative quantum attacks, CNOT and Ping Pong, demonstrating its ability to maintain tamper resistance in noisy environments. The experimental results achieved a fidelity of 65.79% and offered greater structural security than classical hash-based chains under similar conditions. This enables secure, scalable, and quantum-resilient blockchain integration for 6G consumer applications such as telemedicine, IoT device authentication, decentralized finance, and immersive edge services.
Background: With the enhanced data amount being created, it is significant to various organizations and their processing, and managing big data becomes a significant challenge for the managers of the data. The development of inexpensive and new computing systems and cloud computing sectors gave qualified industries to gather and retrieve the data very precisely however securely delivering data across the network with fewer overheads is a demanding work. In the decentralized framework, the big data sharing puts a burden on the internal nodes among the receiver and sender and also creates the congestion in network. The internal nodes that exist to redirect information may have inadequate buffer ability to momentarily take the information and again deliver it to the upcoming nodes that may create the occasional fault in the transmission of data and defeat frequently. Hence, the next node selection to deliver the data is tiresome work, thereby resulting in an enhancement in the total receiving period to allocate the information. Methods: multi-node data repetition. Blockchain is involved in offering a transparency to the application of transmission. A simultaneous multi-threading framework confirms quick data channeling to various network receivers in a very short time. Therefore, an advanced method to securely store and transfer the big data in a timely manner is developed in this work. A deep learning-based smart contract is initially designed. The dilated weighted recurrent neural network (DW-RNN) is used to design the smart contract for the Ethereum blockchain. With the aid of the DW-RNN model, the authentication of the user is verified before accessing the data in the Ethereum blockchain. If the authentication of the user is verified, then the smart contracts are assigned to the authorized user. The model uses elliptic Curve ElGamal cryptography (EC-EC), which is a combination of elliptic curve cryptography (ECC) and ElGamal encryption for better security, to make sure that big data transfers on the Ethereum blockchain are safe. The modified Al-Biruni earth radius search optimization (MBERSO) algorithm is used to make the best keys for this EC-EC encryption scheme. This algorithm manages keys efficiently and securely, which improves data security during blockchain operations. Results: smart contracts.
Lanlan Sun, Yinzhen Wei, Zongshan Wang, Hengjun Liu
Privacy protection, establishment of trust, and quality assurance are known as very vital issues faced by the data sharing systems nowadays. This paper introduces a new framework that addresses these core limitations to integrate distributed ledger technology and machine learning practices. The suggested system will have a consortium blockchain design with incorporated neural network modules to provide automatic data validation and anomaly-detecting features. Smart contractbased governance leads to the safety of sensitive information due to the protection laid by multi-layered encryption protocols and transparency in operations. Evaluation of performance makes use of three different domains namely: their medical information systems, financial transaction networks and sensor data networks. The security is enhanced by $23.5 \%$, quality assessment is more accurate by $\mathbf{9 4. 2 \%}$, and the sustained processing capacity values 2,847 transactions per second according to the comparative assessment. The model provides the basis of cross-organizational cooperation with data as well as regulation and operation efficiency needs in distributed computing environments.
In the contemporary digital age, education is no longer limited to traditional educational environments. Many educational institutions shifted to depend on the smart learning process but expressed concern about this solution due to its various challenges in securing the learning process and learners' data. By virtue of the most recent technologies like blockchain and artificial intelligence, which played a significant role in solving many challenges that faced the educational sector and overcoming issues like fake certificates, manipulation, tracking learners' activities, and predicting learners' academic performance. The study proposed a smart framework based on blockchain and deep learning to enhance smart learning processes and provide solutions for challenges in the field. The framework is intended to store the learner's data on the blockchain through the interplanetary file system and reap the benefits of securing the learner's data and ensuring its integrity, as well as ensuring the confidentiality and authentication of the users through the wallets that are created on the Ethereum private blockchain platform. Then apply the deep learning model to this secured data to predict the learner's performance. The smart contract functions also play a role in enabling the university to issue learners' certificates that are stored on the blockchain to be available and verifiable by all the nodes in the network. Based on the experimental results, deep neural networks were used to model the encrypted data that was stored on the blockchain and predict the learner's performance and achieved a high degree of accuracy (91.29%) and low loss (about 0.18) in comparison to other studies that depended on the centralized nature of the data. As well, the university blockchain's functionality was tested, and it successfully returned all the functional requirements and showed its legitimacy.
G. Ramsudhan, G. Hrudaya, Nandhakumar B.S, R B U R G U S · 5 authors
The concern for security and privacy have skyrocketed as IoT devices in smart homes gain popularity. Unauthorized access, data tampering, and cyberattacks are growing threats. Existing centralized security models, which rely on a single structure, are vulnerable to such threats and hence a more advanced strategy is needed. This paper aims to discuss the Blockchain-Enabled Secure IoT Architecture (BESIA) which use Ethereum smart contracts, permits decentralized authentication, and cryptographic hashing to secure the architecture. To increase device communication, MQTT is used as well as TLS v1.2 encryption to enhance data protection. The approach provides access control using a novel Hierarchical Trust Model (HTM) where the device authentication and registration are fully secured using SHA-256 hashing and asymmetric cryptography. By performing security audits via MitM intrusions, ARP spoofing, and MQTT injection attacks, the systems demonstrated a 68% increase in attack resistance and 85 % decrease in unsolicited access tries after the blockchain was integrated. To conclude, this provides a prescription for a self-sustaining and scalable framework which utilizes real-time encryption and automatic attack intervention combined with the distributed ledger technology (DLT) to enhance smart home security in IoT ecosystems.