This research explores the application of blockchain technology in securing Electronic Health Records (EHRs) while integrating IoT sensors for real-time patient monitoring. The primary goal is to address critical healthcare industry challenges, including security, privacy, data integrity, and accessibility. Our system focuses on enhancing EHR security and reliability through blockchain's decentralized and tamper-resistant features. Additionally, IoT sensors provide real-time monitoring of vital signs, enabling prompt interventions. This study not only delves into technical aspects but also considers practical implementation in healthcare, contributing to improved data security and patient care.
B. Sindhusaranya, R. Yamini, Manimekalai Dr.M.A.P., Geetha Dr.K.
The proliferation of Internet and Communication Technologies (ICTs) has ushered in a period often referred to as Industry 5.0. The subsequent development is accompanied by the healthcare industry coining Healthcare 5.0. Healthcare 5.0 incorporates the Internet of Things (IoT), enabling medical imaging technologies to facilitate early diagnosis of diseases and enhance the quality of healthcare facilities' service. Nevertheless, the healthcare sector is currently experiencing a delay in adopting Artificial Intelligence (AI) and big data technologies compared to other sectors under the umbrella of Industry 5.0. This delay may be attributed to the prevailing concerns about data privacy within the healthcare domain. In recent times, there has been a noticeable increase in the use of Machine Learning (ML) enabled adaptive Internet of Medical Things (IoMT) systems with different technologies for medical applications. ML is an essential component of the IoMT system, as it optimizes the trade-off between delay and energy consumption. The issue of data fraud in classical learning models inside the distributed IoMT system for medical applications remains a significant research challenge in practical settings. This paper proposes Federated Learning and Blockchain-Enabled Privacy-Preserving (FL-BEPP) for Fraud Prevention and Security (FPS) in the IoMT framework. The system incorporates numerous dynamic strategies. This research examines the medical applications that exhibit hard constraints, such as deadlines, and soft constraints, such as resource consumption, when executed on distributed fog and cloud nodes. The primary objective of FL-BEPP is to effectively detect and safeguard the confidentiality and integrity of data across many tiers, including local fog nodes and faraway clouds. This is achieved by minimizing power use and delay while simultaneously meeting the time constraints associated with healthcare workloads.
Shi Dong, Khushnood Abbas, Mengyuan Li, Joarder Kamruzzaman
In recent years, with the rise of digital currency, its underlying technology, blockchain, has become increasingly well-known. This technology has several key characteristics, including decentralization, time-stamped data, consensus mechanism, traceability, programmability, security, and credibility, and block data is essentially tamper-proof. Due to these characteristics, blockchain can address the shortcomings of traditional financial institutions. As a result, this emerging technology has garnered significant attention from financial intermediaries, technology-based companies, and government agencies. This article offers an overview of the fundamentals of blockchain technology and its various applications. The introduction defines blockchain and explains its fundamental working principles, emphasizing features such as decentralization, immutability, and transparency. The article then traces the evolution of blockchain, from its inception in cryptocurrency to its development as a versatile tool with diverse potential applications. The main body of the article explores fundamentals of block chain systems, its limitations, various applications, applicability etc . Finally, the study concludes by discussing the present state of blockchain technology and its future potential, as well as the challenges that must be surmounted to unlock its full potential.
Katarzyna BuĹkowska, Magdalena ZieliĹska, Maciej BuĹkowski
Implementing blockchain technology in waste management is a novel approach to environmental sustainability and accountability challenges in our modern world. Blockchain, a technology that enables decentralized and immutable ledgers, is now being re-imagined as a tool to revolutionize waste management. This innovative approach aims to improve waste management transparency, traceability, and efficiency, resulting in significant environmental and economic benefits. In traditional waste management systems, the tracking and disposal of waste materials are not transparent and can be vulnerable to fraud, mismanagement, and inefficiency. Blockchain technology provides a secure and transparent platform for recording every step in the waste management lifecycle, from waste generation to collection, transportation, recycling, or disposal. Every transaction in the blockchain is recorded in a tamper-proof manner, enabling real-time monitoring and verification of waste-related data. This paper introduces the concept of using blockchain technology in waste management. The main goal of this work is to show the implementation of blockchain technology in an existing waste management company, using smart contracts in the recycling process to provide transparency. Also, the digital product passport was redefined in terms of circular economy and waste recycling.
Sangeeta Gupta, Premkumar Chithaluru, May El Barachi, Manoj Kumar
Abstract In the current landscape, staying abreast of the latest technological advancements is a formidable challenge, especially given the deluge of data inundating the internet. The realization has dawned that effectively managing the surge in emerging data necessitates the integration of multiple technologies. In pursuit of this objective, the Internet of Things (IoT), renowned for its sensorâbased data capture capabilities, is frequently coupled with blockchain technology to ensure secure data storage and access. This amalgamation, in turn, leverages the cloud environment when data volume surpasses a machine's processing capacity, thus mitigating infrastructure and maintenance costs. This study endeavors to optimize data storage within the blocks of the blockchain (BCT) by storing an index that points to the actual data. This innovative approach not only conserves storage space but also enhances operational efficiency. Furthermore, it simplifies the task of identifying malicious or faulty nodes deployed at different locations for data capture within the prescribed time frame. To exemplify this implementation, a case study is presented, focusing on securing user votes through the creation of contracts. The results showcased underscore the preference for a permissioned blockchain, such as Fabric, over a permissionless one, like Ethereum, particularly in the context of security considerations. The findings reveal that as the number of operations (in this case, votes cast) increases, Ethereum's performance deteriorates, while Fabric exhibits exceptional robustness. Additionally, the study analyzes sensor data simulated via IoT nodes before and after the application of security algorithms to underscore the significance of the proposed Secure CloudâBased Blockchain (SCB2) model. The analysis encompasses various facets, including the creation, validation, and computation times of transactions and blocks within a node, and positions the model favorably in comparison to existing literature.
Abstract The modern world has its foundation built on data. Data is generated all the time, and many aspects of the society and economy are built upon it. In today's world, data is employed in better decisionâmaking, innovation, and improving the efficiency of systems. It becomes essential to protect it from being tampered with or misused. Encryptions based on cryptographic systems are used in mainstream data protection these days. There have been newer iterations of mechanisms based on new techniques using blockchain and the zero trust model and even systems that employ fog computing along with content delivery networks. The advent of computation through quantum technologies also helped in developing data security with postâquantum mechanisms. The critical conditions for the working of these mechanisms hinder their adoption primarily. This also leads current systems to lack one or more of these technologies. Thus, the importance of a unified system that can employ quantum technologies effectively becomes prominent and requires a definitive investigation. In this article, a QuantumâIoTâbased data protection scheme that can be of value to Industry 4.0 is analyzed. Light is also shed on innovations in quantum computing that can help solve not just current problems but also the future.
The Internet of Things (IoT) technology in various applications used in data processing systems requires high security because more data must be saved in cloud monitoring systems. Even though numerous procedures are in place to increase the security and dependability of data in IoT applications, the majority of outside users can decode any transferred data at any time. Therefore, it is essential to include data blocks that, under any circumstance, other external users cannot understand. The major significance of proposed method is to incorporate an offloading technique for data processing that is carried out by using block chain technique where complete security is assured for each data. Since a problem methodology is designed with respect to clusters a load balancing technique is incorporated with data weights where parametric evaluations are made in real time to determine the consistency of each data that is monitored with IoT. The examined outcomes with five scenarios process that projected model on offloading analysis with block chain proves to be more secured thereby increasing the accuracy of data processing for each IoT applications to 89%.
The Internet of Things (IoT) has expanded because of the development of information technology. IoT impacts several fields, including the medical profession, smart cities, and data management. The development of sustainable medical systems is significantly aided by the Internet of Medical Things (IoMT). IoMT has a big impact on healthcare since it makes it easier to monitor and validate data about patients before storing it in the cloud. Keeping all data confidential and secured is essential since the IoMT is a big-data platform that is expanding quickly.This paper will apply this technical advancement to the realm of health, namely e-health. The research provides an IoMT-based monitoring tool for personal health surveillance. Block chain technology may resolve present interoperability issues in health-related systems and offer technological solutions that allow the electronic transfer of medical records to medical organizations and medical specialists. However, the transmission and security of people's health data remain a major concern in IoMT devices across a wide range of product categories. This research uses block chain as a secure solution to satisfy the requirements of medical privacy and data security. In this study, a Block chain-based IoMT security System (BC-IoMT-SS) is presented based on BC technology in IoMT for the security, privacy, and management of patient information. The suggested framework is successfully implemented to fulfill the optimal privacy and safety criteria for medical data management in IoMT gadgets. Utilizing the block chain's key, a healthcare application system has been created in which the person's health data may safely generate alerts for verified healthcare practitioners. Simulation results demonstrate that the suggested BC-IoMT-SS technique produces a high precision ratio of 94%, an efficiency ratio of 94%, a shorter delay of 0.63s, and a shorter reaction time compared to other current methods.
The modern world's increasing reliance on automated systems for everyday tasks has resulted in a corresponding rise in power consumption. The demand is further augmented by increased sales of electric vehicles, smart cities, smart transportation, etc. This growing dependence underscores the critical necessity for a robust smart energy measurement and management system to ensure a continuous and efficient power supply. However, implementing such a system presents a set of challenges, particularly concerning the transparency, security, and trustworthiness of data storage and retrieval. Blockchain technology offers an innovative solution in the form of a distributed ledger, which guarantees secure and transparent transaction storage and retrieval. This research introduces a blockchain-based system, utilising Hyperledger Fabric and smart contracts, designed for the secure storage and retrieval of consumers' energy consumption data. Finally, a user-friendly web portal was designed and developed using the node.js framework, offering an accessible and intuitive interface to monitor and manage energy consumption effectively.
Blockchain technology promises to be hugely trending and empowering in education domain computing applications. The digital is becoming an integral part of modern life. So as the use of the digital world increases there are more chances of decrease is the security level. So more the use of digitization more the frauds and less the security. In some cases of personal data, leakage has brought back into the focus the security issues with the different identity sharing mechanisms. A customer is expected to provide his identity for authentication by different agencies. So the document verification process deals with the identification of the user. And in turn, provides the required security. The document verification procedures which are used by the colleges are completely dependent on the encryption. This system can be efficient by using Blockchain technology, which has the potential to automate a lot of manual processes and it is also resistant to hacks of any sort. The immutable blockchain block and its distributed ledger is the perfect complement to the process of document verification. With the addition of smart contacts, fraud detection can be automated..
Arvind Kumar Pandey, Rini Saxena, Aishwary Awasthi, M P Sunil
The Industrial Internet of Things (IIoT) paradigm's fast expansion in the amount of information created from linked devices creates new opportunities for improving the service quality and applications through sharing of data. Data security is a significant problem since training and Support Vector Machine (SVM) classifier often involves compiling tagged IoT data from several organizations. Beyond causing the suppliers to lose money, disclosing sensitive information might cause significant problems. To solve these issues, introduced a secure SVM, which is a Privacy-Preserving SVM (PP-SVM) training method using block chain-based encoded IoT data, to fill the void between ideal assumptions and practical restrictions. IoT messages are encrypted before being stored on a decentralized system because Block chain offers safe and dependable data exchange platforms across several data sources. Using a homomorphic cryptographic algorithm, Paillier, reliable modules have been developed, such as protected algebraic multiplying and protected comparison. Furthermore, a protected SVM learning algorithm that only needs two conversations during a single step has been created. According to stringent security assessment, proposed approach guarantees SVM model parameters for data professionals and secrecy of sensitive information for each data source. Extensive testing backs up effectiveness of the suggested plan.
Abstract A blockchain based platform can be decentralized, meaning that it is not controlled by a single entity or organization. This can help to cut down the risk of data manipulation or fraud, and can also make the platform more resilient to cyber-attacks or other security threats. By automating many of the processes involved in data collection and analysis, blockchain technology can assist farmers to decrease their costs and increase profitability. Architecture for blockchain powered IoT platform for autonomous drone operations in smart farming is proposed. It has three layers which include data acquistion and encryption in IoT layer and creation and management of ledger in the blockchain layer and service provider layer that include user interaction and farming software. Agriculture integrates many of the new automation technologies already in their routine. The proposed architecture enriches the functioning of farming without affecting the current framework. Overall, the blockchain powered IoT platform for autonomous drone operations in smart farming can help farmers improve their efficiency, increase transparency and security, reduce costs, and ultimately achieve more environment sustainability and profitable farming practices.
This paper discusses how the combination of Internet of Things (IoT) and Blockchain technology can create a new paradigm for supplier management in manufacturing plants. IoT enables the comprehensive digitalization of an entire manufacturing plant while providing a trove of data about the daily operations and performance of suppliers, machine performances, and other related activities. Blockchain technology provides a distributed ledger technology to store, share, and manage this data with trust and security, ensuring that all stakeholders within the supply chain are accountable and have an immutable record of their activities and performance. The paper discusses the potential opportunities and benefits that this new paradigm promises for manufacturers through improved supplier management, automated processes, reduced costs, and enhanced transparency. It also examines the challenges associated with making this system functional such as legal issues, system integration, and security concerns. Finally, the paper provides an overview of potential uses of this technology and concludes with a discussion of the future prospects of using IoT and Blockchain in supplier management.
Nowadays, Learning Management Systems (LMS) have become increasingly popular, particularly due to the COVID-19 pandemic, offering enhanced effectiveness and efficiency. Online exams have emerged as a critical feature within LMS, serving as a means to evaluate studentsâ performance and assess their understanding of the course material. These exams play a crucial role in determining studentsâ eligibility for progression to the next grade or level of study. It is imperative that online exam results meet the standards of reliability and transparency. Any lack of reliability, such as the vulnerability to hacking, can have detrimental effects on studentsâ overall grades. Traditional online exam systems typically store data in centralized locations like MySQL databases, leaving them susceptible to unauthorized access by malicious individuals who may alter studentsâ exam results. This paper aims to propose a blockchain-based framework that facilitates the secure and peer-to-peer conduct and evaluation of academic exams. The framework employs hashing techniques to ensure the integrity of the data and utilizes proof of stake mechanisms to enhance security. Blockchain technology has proven to be effective in safeguarding data integrity by virtue of its decentralized data storage approach and the use of cryptographic hashing for every block within the chain. This paper demonstrates how online exams can be developed using blockchain technology, with each question asked and answered being directly stored on the blockchain. To achieve this, we have developed a module that integrates with the Moodle learning management system. Through a comparative analysis of the default centralized storage approach in Moodle, our module modifies the exam resultsâ storage method, ensuring secure and tamper-proof data storage on the blockchain network. By leveraging the blockchain network, the data associated with exam results is reliably secured, ensuring its integrity, and making it immune to manipulation. Our results indicate that the data stored through the blockchain achieved complete accuracy, with no discrepancies observed when compared to the standard approach employed by the Moodle LMS for storing results. The blockchain network provides a reliable and immutable platform that prevents unauthorized alterations or manipulations of student data. In conclusion, our blockchain-based framework offers a robust solution for enhancing the security and reliability of online exam results. By leveraging the decentralized and tamper-proof nature of blockchain technology, we can ensure the integrity and transparency of student data, ultimately providing a more trustworthy and accurate assessment of their academic performance.
Abstract The integration of blockchain and machine learning has emerged as a promising paradigm that can revolutionize various industries and applications. Blockchainâs decentralized and immutable nature, coupled with the analytical capabilities of machine learning, presents new opportunities for secure and transparent data sharing, collaborative model training, and intelligent decision-making. This research paper explores the concept of synergistic integration of blockchain and machine learning, providing an overview of the underlying technologies, related work, and existing frameworks. It proposes a novel Decentralized Intelli- gent Learning Network (DILN) framework that combines the strengths of both technologies to create a decentralized and efficient ecosystem for collaborative machine learning applications. The paper presents case studies in healthcare, finance, supply chain management, IoT, and academic research to showcase the potential impact of this integration. Furthermore, it discusses technical approaches, challenges, and ethical considerations to address in the deployment of decentralized intelligent systems. The research paper concludes by encourag- ing further research and development in the field to unlock the full potential of this transformative technology.
Smart agriculture is quickly becoming into a big financial sector with broad global implications.The main forces behind this technical, ecological, and economical movement are the demand for greater food quality, real-time weather and soil condition monitoring, and these.In order to produce not just better agricultural goods, This study explores the exciting notion of fusing IoT, smart contract, and smart agricultural technology, but also enhancing the agriculture logistics and related supply chain, resulting in several advantages for all parties concerned.On the basis of numerical and optionally categorical data, This study explores the exciting notion of fusing IoT, smart contract, and smart agricultural technology.Additionally, Solidity provides an example implementation of one such measure, It is also demonstrated how to create smart contracts for the Ethereum Virtual Machine using a high-level language.Lastly, some digitalization of agricultural assets, A crucial step for smart contracts based on tangible objects is also covered
Industry 5.0 is seen as the next stage of the industrial revolution. However, the centralized management of the vast amount of data in Industry 5.0 poses significant security challenges. Because blockchain can provide a stable decentralized network for data in Industry 5.0, blockchain technology becomes an ideal solution for the security of data in Industry 5.0. However, with the explosion of data in Industry 5.0, the rapidly growing storage requirements are putting unbearable pressure on nodes and users, making it especially important to address the scalability of the blockchain. While using light nodes can alleviate storage pressure on nodes, it can also lead to data availability attacks. To address the above issues, this paper proposes a blockchain-based trusted data storage mechanism for Industry 5.0. The mechanism combines sharding and two-layer Merkle tree structures, and employs random low-density parity codes to code the tree. It enables light nodes to verify the authenticity of data and solve data availability attacks while improving the throughput of the blockchain. In addition, by using erasure codes to construct low-storage blockchain nodes, the network load of the nodes is effectively reduced, which solves the scalability issues of the blockchain.
The IoT (Internet of Things) encompasses numerous networks and connected devices. One of the primary concerns surrounding IoT, according to researchers and security experts, is the potential risks to privacy and cybersecurity. Deep learning offers significant capabilities for self-adjustment, self-organization, and generalization. Recognizing this, advanced deep learning algorithms are employed in this research to address the privacy and security issues plaguing the IoT landscape. To address these concerns, a novel model called BC-Trans Network is proposed, leveraging the strengths of both Blockchain technology and a transformer component. The transformer plays a vital role in identifying abnormal data, enabling the system to take proactive measures against potential threats. In addition Hash-2 is introduced for the verification of IoT users, adding an extra layer of security to the authentication process. The Blockchain model is utilized to securely store user passwords and details, ensuring a robust and tamper-proof authentication mechanism. To validate the proposed model, a publicly available dataset CSE-CIC-IDS2018 is employed. Pre-processing techniques, including feature selection using the chi-square method, are applied to refine the dataset. The transformer module then classifies the data as normal or abnormal, allowing for accurate identification of potential security breaches. To further safeguard the data and protect the privacy of users, a Fully Homomorphic Encryption (FHE) method is employed. This advanced encryption enables the encryption of categorized normal data, ensuring its confidentiality even during transmission and storage. The study's findings support IoT-cloud server security and privacy by demonstrating the effectiveness of the suggested paradigm in identifying and thwarting network threats. With detection times of 225.3 seconds, an accuracy of 99.25%, a precision of 99.53%, a recall of 99.32%, and an F1 score of 99.59%, the proposed system exhibits impressive performance. Furthermore, as the output numbers increase, the system's metrics improve, suggesting its scalability and flexibility.
As medical technology advances, there is an increasing need for healthcare providers all over the world to securely share a growing volume of data. Blockchain is a powerful technology that allows multiple parties to securely access and share data. Given the enormous challenge that healthcare systems face in digitizing and sharing health records, it is not unexpected that many are attempting to improve healthcare processes by utilizing blockchain technology. By systematically examining articles published from 2017 to 2022, this review addresses the existing gap by methodically discussing the state, research trends, and challenges of blockchain in medical data exchange. The number of articles on this issue has increased, reflecting the growing importance and interest in blockchain research for medical data exchange. Recent blockchain-based medical data sharing advances include safe healthcare management systems, health data architectures, smart contract frameworks, and encryption approaches. The evaluation examines medical data encryption, blockchain networks, and how the Internet of Things (IoT) improves hospital workflows. The findings show that blockchain can improve patient care and healthcare services by securely sharing data.
Blockchain technology has revolutionized many industries and has great potential outside of finance. This paper explores blockchain's applications and challenges in agriculture, electricity, transportation, healthcare, and finance. Blockchain technology can track agricultural product origin, quality, and safety to improve supply chain transparency in agriculture. Blockchain can also reduce intermediaries, improve payment systems, and expand financing. Blockchain can enable decentralized electricity management, peer-to-peer energy transactions, and lower transaction costs. It could boost renewable energy integration, grid efficiency, and energy access for underserved communities. Blockchain technology can improve transportation supply chain visibility and reduce fraud by providing a shared, tamper-proof ledger to track goods and prevent unauthorized access. Blockchain can secure, interoperable, and improve patient privacy in healthcare. It could let patients share their health data with providers and researchers while protecting their privacy. Blockchain implementation is also tricky. Scalability, interoperability, compliance, and data privacy Blockchain solutions must handle large amounts of data, integrate with existing systems, comply with laws and regulations, and protect sensitive data. Further research and development are necessary to explore blockchain technology's possibilities in these fields fully.
With the increasing growth rate of smart home devices and their interconnectivity via the Internet of Things (IoT), security threats to the communication network have become a concern. This paper proposes a learning engine for a smart home communication network that utilizes blockchain-based secure communication and a cloud-based data evaluation layer to segregate and rank data on the basis of three broad categories of Transactions (T), namely Smart T, Mod T, and Avoid T. The learning engine utilizes a neural network for the training and classification of the categories that helps the blockchain layer with improvisation in the decision-making process. The contributions of this paper include the application of a secure blockchain layer for user authentication and the generation of a ledger for the communication network; the utilization of the cloud-based data evaluation layer; the enhancement of an SI-based algorithm for training; and the utilization of a neural engine for the precise training and classification of categories. The proposed algorithm outperformed the Fused Real-Time Sequential Deep Extreme Learning Machine (RTS-DELM) system, the data fusion technique, and artificial intelligence Internet of Things technology in providing electronic information engineering and analyzing optimization schemes in terms of the computation complexity, false authentication rate, and qualitative parameters with a lower average computation complexity; in addition, it ensures a secure, efficient smart home communication network to enhance the lifestyle of human beings.
T. Rajendran, Shri Bharathi S V, Sridhar S, T. Anitha
Integrating the Internet into many applications has made securing usersâ data and maintaining their privacy a significant concern. In recent years, blockchains (BC) have garnered much attention due to their distinctive properties, which include decentralization, immutability, anonymity, security, and auditability. BC technology was utilized in various nonfinancial applications, like the Internet of Things (IoT), wireless sensor networks (WSN), and cloud computing. The objective of this study is to conduct an analysis of previously published research and provide a summary of the efforts put into researching BC applications for network security. In this study, many networking technologies, including IoT, Industrial IoT, Cloud, WSN, VANET, and MANET, were used in conjunction with BC technology to investigate applications for network security. This study presents an analysis of network security, along with its limitations and contributions, with an overview of the BC evolution, BC architecture, its working principle, and its application, as well as the advantages and disadvantages associated with BC. In this study, recently published articles on BC-based solutions for network security and privacy preservation that were published between 2018 and 2022 are analyzed. The surveyed articles are categorized according to the network application, methodology, and contribution. In conclusion, an analysis of the implementation of BC technology across various networks and their issues and challenges are presented.
Emerging technologies including such Internet of Things (IoT) and blockchain contribute significantly to the improvement of health services. The purpose of this chapter is to achieve and democratize services through the provision of medical care as a service. The result was the development of medical gadgets integrating healthcare sensors. It links medical equipment like the temperature controller to the cloud environment of medical doctors and staff. This study introduced the combination of IoT and Blockchain as a secure platform to reduce the scarcity of nurses. Blockchain was employed for storing and validating patient information in the proposed operating framework. A significant reduction in nursing gaps for large-scale patients has been shown. All technological specifications have been given to allow the prototyping execution of these suggested medical services simply adaptable. This article deals with Blockchain technology inclusion in Remote Medical Monitoring Devices Internet of Things (IoT) security. The document provides the advantages of Blockchain based safety methods and practical barriers in remote health monitoring via IoT devices. The study also examines several cryptographic methods appropriate for IoT implementation.
Internet of Things (IoT) fog nodes are distributed near end-user devices to mitigate the impacts of low delay, position awareness, and spatial spread, which aren't permitted by numerous IoT apps. Fog computing (FC) also speeds up reaction times by decreasing the quantity of data sent to the cloud. Despite these advantages, FC still has a lot of work to do to fulfill security and privacy standards. The constraints of the FC resources are the cause of these difficulties. In reality, FC could raise fresh concerns about privacy and security. Although the Fog security and privacy problems have been covered in several articles recently, most of these studies just touched the surface of these difficulties. This paper provides a unique solution for the authentication of data by using hyperledger fabric. The fog layer store data transferred by the IoT layer and calculate the hash value. These hash values are now stored in hyperledger fabric for authentication purposes. The proposed model results compared with lewakoâs and Fanâs scheme and found that the proposed model has 25.00 % less encryption time, 09.3 % less decryption time, 17.48 % less storage overhead, and 23.38 % less computation cost as compared to Fanâs scheme.