The integration of the Internet of Things (IoT) with blockchain technology is significantly transforming smart health monitoring systems. IoT enables the seamless collection of health data, while blockchain's decentralized ledger ensures the integrity and security of this data, mitigating potential breaches. This symbiosis addresses current healthcare challenges by enhancing security, transparency, and efficiency, fostering a patient-focused and reliable monitoring system. With the rise of the Medical Internet of Things (MIoT), personalized and cost-effective healthcare solutions are more accessible, thanks to technologies like Wireless Body Area Networks (WBAN), which improve data quality, and Machine Learning (ML), which effectively processes large datasets. Fog Computing has been instrumental in ensuring efficient data communication with reduced latency, and advancements in Software-Defined Networking (SDN) and Network Function Virtualization (NFV) offer simpler, adaptable networks for healthcare. However, increased data volume raises privacy and security concerns, propelling a shift towards blockchain for enhanced data protection and transparency. Innovations like blockchain-based federated learning aim to safeguard privacy without compromising model accuracy, and smart contracts on platforms like Hyperledger Fabric provide secure patient history logs and immediate access to medical records. Tools such as the Libelium e-Health toolkit further aim to revolutionize monitoring, diagnosis, and treatment processes.
Today, Internet of Things (IoT) data sharing is a big challenge for increasing the progress, efficiency, and effectiveness of any organization in the health sector through IoT-based applications. Generally, health records follow centralized abilities in the IoT. Health sector Data Security and failures of centralized servers are issues in the IoT. Peer-to-peer networks utilize distributed applications and duplicate transactions leveraging digital ledgers in the blockchain. Blochchain is recording all health information on a decentralized system that is impossible to change or hack. Blockchain technology supports IoT privacy, cryptocurrencies, healthcare, smart contracts, supply chain management, identity verification, insurance, etc. IoT-based health records contain a lot of problems like privacy, security, performance, ethics, data ownership, patient access and control, etc. In easy ways, blockchain technology exacerbates these kinds of problems. Ethereum and Hyperledger are supported as frameworks using blockchain technology. Compared to the previously specified data values, IoT-based health data has a significantly higher level of security and privacy. This study explores in detail the various approaches, workings, and technical details used in various languages.
Abstract: This paper investigates the integration of an Intrusion Detection System (IDS) within the context of blockchain technology. The objective is to enhance the security posture of blockchain networks by detecting and mitigating potential intrusions. Through a meticulous examination of the current threat landscape and the unique challenges posed by blockchain systems, this research proposes a robust IDS framework tailored to the specific requirements of decentralized and distributed ledger environments. The study employs [specific methodology/approach] to assess the effectiveness of the proposed IDS, presenting conclusive findings that contribute to the ongoing discourse on securing blockchain ecosystems. The implications of this research extend to bolstering the resilience of blockchain networks against emerging threat.
In the current landscape of vaccine distribution, the pervasive threat of illicit distributors exploiting transaction data vulnerabilities raises serious concerns about vaccine safety and authenticity. To address this challenge, this research introduces an innovative blockchain-based system aimed at countering vaccine counterfeiting and enhancing the transparency of distribution processes. Leveraging Supply Chain Management principles, the system orchestrates the complexities of vaccine distribution, offering comprehensive visibility from central government initiation to healthcare professional administration via an intuitive mobile application. Blockchain technology strengthens data security, guarding against fraudulent activities, while the integration of QR codes expedites data processing and furnishes patients with detailed vaccine information. All transactions are executed through smart contracts, ensuring trust and transparency, with completed contracts securely recorded on the Ethereum blockchain. This research presents a groundbreaking solution to combat vaccine counterfeiting, establishing a resilient and transparent framework for distribution, providing real-time monitoring, and empowering patients and stakeholders with essential vaccine details. In summary, the amalgamation of Ethereum blockchain technology and QR codes in this mobile-based vaccine tracking system offers a transformative approach to fortify the safety and integrity of vaccine distribution, ultimately benefiting society as a whole.
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From the last few years, in product manufacturing industries, counterfeit products have played an important role that would affect the companv's fame. sales. and profit. To detect fake products and identify real products, a secure system can be developed using blockchain technology, Blockchain technology is a distributed decentralized, digital ledger that is stored across multiple databases, storing all transactions as blocks connected by a chain. Due to having a digital ledger, a block cannot be changed or be hacked. By employing blockchain technology, consumers or users may certify the safety of a product without depending on other users. In this study, Quick Response (QR) codes and bar codes have been used to provide robust techniques to detect counterfeit products. where QR code of the product is associated as a block to a blockchain. The proposed system stores product details and generate a unique QR code associated with that product as a block in the database to detect the counterfeit product. The unique QR codes have been created throughout the procedure and it is matched with the entries stored in the blockchain database. If the generated unique QR code is matched against entries in the blockchain database, it will give a notification to the user otherwise fake product notification will be given to the user. The proposed system outperforms the existing systems in terms of security as well as computational time.
Julio César Pérez García, An Braeken, Abderrahim Benslimane
Group communications play a crucial role in enhancing the quality of service (QoS) of Internet of Things (IoT) networks, enabling efficient information dissemination while minimizing resource utilization. However, ensuring information security and privacy in IoT group communications necessitates the implementation of an efficient and lightweight key management scheme due to the limited capabilities of most IoT devices. This paper presents a novel key management protocol for group communications that employs distributed Blockchain technology in IoT networks. The proposed scheme considers nodes belonging to multiple groups. By utilizing an asymmetric key shared among group members, secure communication is established between outsiders and group members while preserving anonymity inside the group. A distinguishing feature of the protocol is its combination of group member anonymity and automatic key revocation facilitated by a Smart Contract. Furthermore, simulation results demonstrate the efficiency of the proposed scheme, consuming less than 300 mJ of energy and taking less than 7 seconds to establish a group key among 1000 nodes, outperforming several existing approaches in the literature in terms of computation and communication costs.
The Internet of Things (IoT) system is a complex environment where various entities and devices communicate. IoT is used in fields like transportation, healthcare, and monitoring, linking smart devices with sensors through the Internet to collect data from the physical world. To protect this sensitive data from hackers, an IoT platform or architecture that ensures end-to-end privacy and security is essential. Although there are many security and privacy solutions for IoT that offer basic security needs like confidentiality, integrity, and authentication, traditional solutions fall short for the large-scale IoT paradigm due to its heterogeneous nature and resource-constrained devices. Hence, this research focuses on decentralized architectures. Block chain (BC) technology is gaining attention for addressing security and authoritarian issues. In this approach, a block chain smart contract is updated with an attack detection contract.
Cognitive radio (CR) is the best way to improve the efficiency of spectrum consumption for wireless multimedia communications. Spectrum sensing, which allows legitimate secondary users (SU) to find vacant bands in the spectrum, plays a vital role in CR networks. When cooperative sensing is used in CR networks, spectrum availability must be taken into account. In many ways, the shared cooperative spectrum sensing (CSS) data among SU. The presence of a malicious user (MU) in the system and sending false sensing data can degrade the performance of cooperative CR. The sharp rise in mobile data traffic causes congestion in the licensed band for the transmission of signals. Handling this security issue in real time, on top of spectrum sharing, is a challenge in such networks. In order to manage the spectrum and identify MU, blockchain-based CSS is developed in this article. To gauge the efficiency of the proposed topology, performance metrics like sensitivity, node selection, throughput measurement, and energy efficiency are used. This work suggests a unique, easier-to-use CSS method with MU suppression that outperforms the current one. According to simulation studies, the suggested topology can increase the likelihood of MU detection by roughly 15% when 40% of system users are malicious.
Ananth S Dev, Anand V Pranav, R. Kamalesh, M. Jeevanantham · 5 authors
Blockchain is a new discipline founded on the concept of a digitally distributed ledger and consensus algorithm this eliminates all risks associated with intermediaries. Its early applications were in the banking industry, but since then, it’s been expanded to almost everything major research areas, including education, banking, IoT, supply chain, governance, defence, and healthcare. Interoperability, security, authenticity, transparency, and simplified transactions and healthcare stakeholders made a demand on it by (research organizations, patients, providers, supply chain bearers and payers,). By employing a patient-centric approach and eliminating the third party, blockchain technology, which is established over the internet, can utilize current data in healthcare in a peer-to-peer and that are interoperable one. Here we have produced a survey paper on block chain’s significant role and how it operates in the healthcare sector.
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.
Counterfeit drugs pose a significant and increasingly urgent global problem, jeopardizing the health of consumers and the general population. As drugs pass through various stages in the supply chain, from suppliers to manufacturers to distributors and retailers, the original manufacturers lose track of how their products are used, while consumers remain unaware of the legitimacy of the drugs they receive. This issue leads to substantial economic losses for manufacturing companies and countries. Ensuring the verification of medicine authenticity and monitoring temperature conditions would enable medical professionals and patients to discard ineffective or expired medicines. This article suggests leveraging blockchain technology to combat drug counterfeiting and enhance traceability, security, and visibility in the pharmaceutical supply chain. An experimental system built on Ethereum was implemented and its cost-effectiveness was evaluated. The study utilized a virtual IoT device through the Cooja simulator to monitor the storage conditions of medicines.
Many organizations use tendering including government to obtain goods and services from the providers of the service and manufacturing companies. There has been an advance evolution in the process from traditional hardcopy based to modern electronic based tendering. Since in the present scenario internet is being used there are many security implications that can be associated with it. Blockchain having decentralization of information and other features like immutability can be used as a step to mitigate the implications. In this paper, a distributed e-tendering system based on IoT, smart contracts and hybrid cryptography is explored. The design consists of sections based on the way the tendering and bidding organization participates like creation and publication of tender by the tendering organization, bidding process by the bidder, evaluations of the proposed bid, selection of the best one to declare the winner and finally to track the development of the procurement process and give stakeholders real-time updates IoT devices are used. Maintaining transparency, traceability, fairness, and security is kept in mind throughout the process which is the main motive of this paper.
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%.
In response to the safety concerns surrounding the IoT, an attribute-based encryption and access control scheme (ABE-ACS) has been proposed. This scheme can be more effectively implemented through the use of cutting-edge technology and incorporating attribute-based encryption (ABE) and attribute-based access control (ABAC) models with features as the point of origin. Facing Edge-IoT is a heterogeneous network made up of certain nodes with more powerful computers and the majority of resource-constrained IoT devices. The authors provide a lightweight with an upgrade to the proof-of-work consensus to address the issues of excessive resource consumption and challenging deployment of existing platforms. To protect the confidentiality of the access control policies, the limits of the tree are utilised for transformation and allocation stored. Six smart contracts are created for devices and data to implement the ABAC and punishment mechanism, which outsources ABE to edge nodes for privacy and integrity. Thus, the plan implements device-controlled access and Edge-IoT privacy protection for data.
Many facets of contemporary life may be drastically altered by the confluence of AI, IoT, Big Data, and Blockchain. When combined, these technologies hold the promise of providing robust, safe, and efficient solutions to complex problems. To better serve customers, streamline internal operations, and maximise available resources, AI could examine the mountains of data produced by Internet of Things (IoT) devices. Businesses now have the power to make data-driven choices in real time because to Big Data technology's ability to store, handle, and understand this data. By making transactions transparent and immutable on a distributed ledger, blockchain technology may improve the safety of these systems. Safer and more efficient methods of data exchange and cooperation may also be simpler to implement through decentralised networks. The impacts of integrating blockchain, big data, the internet of things (IoT), and AI are investigated in-depth in this paper. The objective is to comprehend the potential benefits and challenges brought on by the combination of these cutting-edge technologies. Manufacturing, healthcare, transportation, and the financial industry are among those studied in order to assess the revolutionary consequences of integrating AI, IoT, Big Data, and the Blockchain. The study's findings add to our understanding of the synergistic potential of artificial intelligence (AI), the internet of things (IoT), big data (Big Data), and blockchain technologies, and they provide direction to firms seeking to use this potential.
Electronic health records (HERs) contain highly sensitive and private data. In the current centralized system, patient healthcare data is not secure and that raises serious concerns. The privacy of personal healthcare data can be protected through permissioned blockchain technology. Hyperledger Fabric is a permissioned blockchain architecture that allows the building of a private blockchain for enterprise solutions. This study focuses on using a Hyperledger Fabric distributed blockchain network to manage electronic health records securely and efficiently. In recent years, several permissioned blockchain-integrated solutions for electronic health records have emerged; each promises to revolutionize how transactions are processed and privacy methods are implemented. However, only a few articles have discussed Hyperledger Fabric&s;s privacy-preserving mechanisms to preserve transaction linkability and data privacy inside the network. Our suggested architecture seeks to deliver Hyperledger Fabric blockchain-based healthcare solutions that securely store, manage, and transfer patient-sensitive data while maintaining the privacy of healthcare actors’ sensitive data. Furthermore, the proposed architecture uses proxy re-encryption mechanisms and IPFS with Arweave to enhance the privacy, immutability, and permanence of the data.
Abstract The integration of blockchain and machine learning has emerged as a promising paradigm that can revolutionize various industries and applications. Blockchain’s 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.
Millions of individuals around the world have been impacted by the ongoing coronavirus outbreak, known as the COVID-19 pandemic. Blockchain, Artificial Intelligence (AI), and other cutting-edge digital and innovative technologies have all offered promising solutions in such situations. AI provides advanced and innovative techniques for classifying and detecting symptoms caused by the coronavirus. Additionally, Blockchain may be utilized in healthcare in a variety of ways thanks to its highly open, secure standards, which permit a significant drop in healthcare costs and opens up new ways for patients to access medical services. Likewise, these techniques and solutions facilitate medical experts in the early diagnosis of diseases and later in treatments and sustaining pharmaceutical manufacturing. Therefore, in this work, a smart blockchain and AI-enabled system is presented for the healthcare sector that helps to combat the coronavirus pandemic. To further incorporate Blockchain technology, a new deep learning-based architecture is designed to identify the virus in radiological images. As a result, the developed system may offer reliable data-gathering platforms and promising security solutions, guaranteeing the high quality of COVID-19 data analytics. We created a multi-layer sequential deep learning architecture using a benchmark data set. In order to make the suggested deep learning architecture for the analysis of radiological images more understandable and interpretable, we also implemented the Gradient-weighted Class Activation Mapping (Grad-CAM) based colour visualization approach to all of the tests. As a result, the architecture achieves a classification accuracy rate of 0.96, thus producing excellent results.
The role of record keeping and information sharing in the health sector cannot be overemphasized.Such records comprise an individual's health history and other information that facilitates healthcare decisions, therefore easy access to a patient's health information is an important aspect of health-service delivery that must be regulated and monitored because of the sensitivity of the information.Some approaches adopted in many hospitals face challenges of missing files or records, lack of information sharing between healthcare providers, insecure records, and also inaccessibility of patient's health information for healthcare providers that are needed to make informed health decisions.To overcome these challenges, this work proposes an Electronic Health Record (EHR) using Blockchain to store information as well as enhance data privacy and data security.The proposed solution includes Ethereum and smart contracts to establish a medical record system to ensure the privacy of patients.Also, there exists the privilege to deal with and authorize personal medical records in the proposed framework.The practical findings demonstrate that our proposed system offers a practical approach for trustworthy data exchanges in healthcare while safeguarding private health data from dangers.When compared to the current data sharing models, the system evaluation and security exploration show performance gains in the design, minimize delays in patient data retrieval, and high levels of security and data privacy.
This paper examines factors affecting the adoption of cryptocurrency across 158 countries worldwide. To this end, we collected cryptocurrency adoption data from Chainalysis’s reports and macroeconomic data from the World Development Indicators platform. We find that greater import volumes, larger population size, more sufficient levels of the labor force, higher unemployment rate, and a higher level of electricity access are associated with a greater level of cryptocurrency adoption. On the other hand, a higher level of government spending and a greater level of domestic savings are associated with a lower level of cryptocurrency adoption. In addition, we also find that the population size and level of the labor force have a negative impact on the three subcomponents of the cryptocurrency adoption index including (i) centralized service value received (CeFi); (ii) the volume of exchange trading (P2P); and (iii) the received DeFi value (DeFi). We find that while the import volumes and level of electricity access have an opposite relationship with the centralized service value received and the DeFi value received, GDP has a negative effect on the DeFi value received. Meanwhile, greater government spending and higher domestic savings are associated with a greater level of exchange trade volume P2P. In terms of urbanization, whereas it shows a positive impact on the exchange trade volume P2P, it has the opposite effect on the DeFi value received.
Non-Fungible Tokens (NFT) are blockchain-based tokens that individually stand for a particular asset, such as a piece of media or digital data. A digital or physical asset can have an NFT as an irrevocable certificate of ownership and authenticity (Wang et al., 2021). Digital forms of certifications can consider using NFT and blockchain technology (Franceschet, 2021). Technological advancement made it possible for people to create fraud certificates, such as university degrees that the buyers do not actually possess. This is unethical and alarming. The current credentials from certificates are difficult to verify as legitimate, which encourages educational fraud. Blockchain technology with NFTs empowers a solution to certificate fraudulence. In this study, the demand of a handful of Malaysians towards buying fraud certificates and the ideas behind those that supply such certificates are scrutinized. Potential use cases and challenges on how NFTs can be used to combat certificate fraudulence and enhance education systems are studied by gathering information from past literatures and conducting interviews with people involved in certification fraud. The ethnography approach applied focuses on the occurrence of fake certificates in society that involves using certificates to seek employment or permit for incomes. Convenience sampling is applied to access the perspectives of respondents, who are also aware of NFT technology. The lack of coordination in Malaysia between multiple parties such as certificate issuers, companies hiring employees and government authorities allows certification fraud to occur. An increase of NFT public penetration and blockchain technology can counter this issue.