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.
The huge headway of new advances like the Web of Things and wearable innovation, the medical services industry is extending rapidly these days. To guarantee far off persistent observing, these devices are generally used. Client/server engineering is utilized in the ongoing execution. Due of the security and protection issues raised by this, medical care frameworks are currently more helpless against different assaults. The utilization of a dispersed engineering is expected to resolve these issues and submit to security rules. Block chain has drawn in a ton of interest as a modern innovation to address the security issues in IoT-based frameworks in light of its conveyed nature and its security ensures. With the new presentation of block chain and IoT, the medical care area is supposed to develop altogether and experience an expansion in monetary potential as well as security, protection, effectiveness, and straightforwardness. The client/server engineering is the underpinning of the ongoing execution. In this paper, various protection and security gives that make medical services frameworks more powerless against different assaults.
Recently Internet of things (IoT)-based healthcare system has expanded significantly, however, they are restricted by the absence of an intrusion detection mechanism (IDS). Modern technologies like blockchain (BC), edge computing (EC), and machine learning (ML) provide a robust security solution that is well-suited to protecting patients' medical information. In this study, we offer an intelligent intrusion detection mechanism FIDANN that protects the confidentiality of medical data by completing the intrusion detection task by utilising Dwarf mongoose-optimized artificial neural networks (DMO-ANN) through a federated learning (FL) technique. In the context of recent developments in blockchain technology, such as the elimination of contaminating attacks and the provision of complete visibility and data integrity over the decentralized system with minimal additional effort. Using the model at the edges secures the cloud from attacks by limiting information from its gateway with less computing time and processing power as FL works with fewer datasets. The findings demonstrate that our suggested models perform better when dealing with the diversity of data produced by IoT devices.
शौनक साहू, प्रो. दिनेश कुमार तिवारी, Ankita Ankita, Brunda S P · 5 authors
Abstract: Electronic voting, or e-voting, has been used in various forms since the 1970s. B. Increase efficiency and reduce errors. However, wide adoption of such systems remains a challenge, especially in terms of improving resilience to potential failures. Blockchain is a disruptive technology of our time and promises to improve the overall resilience of electronic voting systems. The democratic system is fundamentally based on the right to vote that Allow individuals within the community to express their opinions. While voter turnout has declined in recent years, concerns about the integrity, security, and accessibility of the current voting system have increased. Electronic voting was introduced to address these concerns. However, it is not cost-effective and requires full oversight by a central authority. Blockchain is an emerging decentralized and decentralized technology that promises to improve many aspects of many industries. Extending e-voting to blockchain technology could be a solution to alleviating current concerns about e-voting. In this paper, I proposed a voting system that leverages the Ethereum blockchain and smart contracts to achieve voter management and verifiable voting records.
The term blockchain is mainly regarded as the distributed transaction which is mainly comprised of different blocks, and each set tends to represent the data that are being associated with the previous blocks. The blockchain is mainly managed through peer-to-peer networks which comparatively involves in adhering to the protocol of authenticating various blocks to form the blockchain. The usage of blockchain technology has been increasingly used in different fields, and healthcare services are now using blockchain for better patient delivery, detecting disease, and other aspects. The scope of the proposed study is that this study has exploited the function of a blockchain-enabled big data network to support medical professionals in giving better treatment modalities and delivering better patient care. The application of a new generation of smart block chains such as Ethereum and NEM is now offering better services and features in creating blockchain-based healthcare data management and hence support healthcare centers, medical practitioners, nurses, radiologists, and patients for better healthcare management. The application of blockchain technology in big data networks supports adding more value as it results in enhanced data quality, accessibility, and support in creating better security and safety of data and information, which is highly essential in the medical industry. Blockchain technology enables big data technologies enabled in supporting medical practitioners in addressing various healthcare ailments; one of the major diseases impacting many people around the world is diabetes. Patients with such ailments tend to generate more data and information related to the disease and health-related aspects. Hence, this information requires being maintained and analyzed, so that superior healthcare services can be provided. This study is more involved in the investigation of blockchain technology through a big data network enabled in offering better care for elderly individuals who have been affected due to diabetes, the researchers propose to choose a questionnaire method to collect the data from nearly 169 respondents, and these data were then analyzed using SPSS data package. The analyst used percentage analysis, correlation analysis, and chi-square test to analyze the data which has been collated by the researchers. The results and discussion show in detail the major aspects of blockchain technology in supporting healthcare professionals for better diabetes care management for elderly individuals.
S. K. UmaMaheswaran, G. Lakshmi Vara Prasad, Батырхан Омаров, Dalael Saad Abdul-Zahra · 7 authors
According to the benefits in safeguarding and transferring medical information, illness assessment, evaluation of “Magnetic Resonance Mapping” images, and certain other disciplines, blockchain and machine learning (ML) technology has significantly piqued attention in the healthcare domains. Formerly, those chores have been performed out along with individuals; eventually, individuals acquired attraction because to its precision and efficiency. The proposed study will examine the activities and possible capabilities of learning algorithms and blockchain in the healthcare professions focusing on these fascinating facts. Primary and secondary data analysis has been executed, with primary analysis method consisting of a survey of 150 randomly picked medicine professionals with expertise in machine learning and blockchain. They gave their answers that were being subsequently transferred to figures and employed as response variable in SPSS examining. The length of time where learning and blockchain have been used in medicine is really the independent factor. To better understand the primary and small hurdles of integrating machine learning and blockchain, a correlation investigation was done. Thereafter, secondary methodology is employed to validate the primary study results.
Deep learning (DL) is a new approach that provides exceptional speed in healthcare activities with greater accuracy. In this regard, “convolutional neural network” or CNN and blockchain are two important parts that together fasten the disease detection procedures securely. CNN can detect and predict diseases like lung cancer and help determine food quality, and blockchain is responsible for data. This research is going to analyze the extension of blockchain with the help of CNN for lung cancer prediction and making food safer. CNN algorithm has been trained with a huge number of images by altering the filters, features, epoch values, padding value, kernel size, and resolution. Subsequently, the CNN accuracy has been measured to understand how these factors affect the accuracy. A linear regression analysis has been carried out in IBM SPSS where the independent variables selected are image dataset augmentation, epochs, features, pixel size (90 × 90 to 512 × 512), kernel size (0–7), filters (10–40), and padding. The dependent variable is the accuracy of CNN. Findings suggested that a larger number of epochs improve the CNN accuracy; however, when more than 12 epochs are considered, the accuracy may decrease. A greater pixel/resolution also improves the accuracy of cancer and food image detection. When images are provided with excellent features and filters, the CNN accuracy improves. The main objective of this research is to comprehend how the independent variables affect the accuracy (dependent), but the reading may not be fully exact, and thus, the researcher has conceded out a minor task, which delivered evidence supportive of the analysis and against the analysis. As a result, it can be determined that image augmentation and a large number of images develop the CNN accuracy in lung cancer prediction and food safety determination when features and filters are applied correctly. A total of 10–12 epochs are desirable for CNN to receive 99% accuracy with 1 padding.
Blockchain-based cyber-physical systems (CPSs) and the blockchain Internet of things (BIoT) are two major focuses of the modern technological revolution. Currently we have security attacks like distributed denial-of-service (DDoS), address resolution protocol (ARP) spoofing attacks, various phishing and configuration threats, network congestion, etc. on the existing CPS and IoT architectures. This study conducts a complete survey on the flaws of the present centralized IoT system’s peer-to-peer (P2P) communication and the CPS architecture’s machine-to-machine (M2M) communication. Both these architectures could use the inherent consensus algorithms and cryptographic advantages of blockchain technology. To show how blockchain technology can resolve the flaws of the existing CPS and IoT architectures while maintaining confidentiality, integrity, and availability (the CIA triad), we conduct a holistic survey here on this topic and discuss the research focus in the domain of the BIoT. Then we analyse the similarities and dissimilarities of blockchain technology in IoT and CPS architectures. Finally, it is well understood that one should explore whether blockchain technology will give advantages to CPS and IoT applications through a decision support system (DSS) with a relevant mathematical model, so here we provide the DSS with such a model for this purpose.
Ahmed S. Almasoud, Abdelzahir Abdelmaboud, Faisal S. Alsubaei, Manar Ahmed Hamza · 8 authors
Cyber-Physical System (CPS) involves the combination of physical processes with computation and communication systems. The recent advancements made in cloud computing, Wireless Sensor Network (WSN), healthcare sensors, etc. tend to develop CPS as a proficient model for healthcare applications especially, home patient care. Though several techniques have been proposed earlier related to CPS structures, only a handful of studies has focused on the design of CPS models for health care sector. So, the proposal for a dedicated CPS model for healthcare sector necessitates a significant interest to ensure data privacy. To overcome the challenges, the current research paper designs a Deep Learning-based Intrusion Detection and Image Classification for Secure CPS (DLIDIC-SCPS) model for healthcare sector. The aim of the proposed DLIDIC-SCPS model is to achieve secure image transmission and image classification process for CPS in healthcare sector. Primarily, data acquisition takes place with the help of sensors and detection of intrusions is performed using Fuzzy Deep Neural Network (FDNN) technique. Besides, Multiple Share Creation (MSC) approach is used to create several shares of medical image so as to accomplish security. Also, blockchain is employed as a distributed data storage entity to create a ledger that provides access to the client. For image classification, Inception v3 with Fuzzy Wavelet Neural Network (FWNN) is utilized that diagnose the disease from the applied medical image. Finally, Salp Swarm Algorithm (SSA) is utilized to fine tune the parameters involved in WNN model, thereby boosting its classification performance. A wide range of simulations was carried out to highlight the superiority of the proposed DLIDIC-SCPS technique. The simulation outcomes confirm that DLIDIC-SCPS approach demonstrates promising results in terms of security, privacy, and image classification outcomes over recent state-of-the-art techniques.
G. Naga Nithin, Bhaskara S. Egala, Ashok Kumar Pradhan
The COVID-19 outbreak highlighted the smart healthcare infrastructure requirement to speed up vaccination and treatment. Present vaccination supply chain models are fragmented in nature, and they are suitable for a pandemic like COVID-19. Most of these vaccination supply chain models are cloud-centric and depend on humans. Due to this, the transparency in the supply chain and vaccination process is questionable. Moreover, we con’t trace where the vaccination programs are facing issues in real-time. Furthermore, traditional supply chain models are vulnerable to a single point of failure and lack people-centric service capabilities. This paper has proposed a novel supply chain model for COVID-19 using robust technologies such as Blockchain and the Internet of Things. Besides, it automates the entire vaccination supplication chain, and it records management without compromising data integrity. We have evaluated our proposed model using Ethereum based decentralized application (DApp) to showcase its real-time capabilities. The DApp contains two divisions to deal with internal (intra) and worldwide (inter) use cases. From the system analysis, it is clear that it provides digital records integrity, availability, and system scalability by eliminating a single point of failure. Finally, the proposed system eliminates human interference in digital record management, which is prone to errors and alternation.
Conventional crop insurance systems are complex and often not economically feasible. Farmers are often reluctant to be covered for their crops due to lack of trust in insurance firms and the fear of delayed or non-payment of claims. In this paper, a blockchain based crop insurance solution is suggested. The solution suggested in this paper is an affordable, efficient, low cost crop insurance solution which will ensure many farmers are insured and benefiting from timely crop insurance. Currently the cost of administering insurance is an essential barrier to accessing this facility. With the proper use of blockchain based on ethereum this expense can be reduced dramatically. We have conducted various tests on platforms such as Google Cloud and found that the least throughput is 165 transactions. Upon analysis we have found that the time taken by the block formation is directly proportional to the timing of processing. The end-to-end average latency of the system was achieved as 31.2 s, which was quite effective for the infrastructure what we are using. Upon conducting acceptance testing, we found that the system suggested in the paper is effective and we are planning to release the application on open source platforms for future improvements.
V Vignesh, S. Harihara Gopalan, M.S. Kiran Mohan, R S Ramya · 5 authors
Abstract Protection measures are essential to present day blockchain innovation ever, since they can exist short of empowered outsider, which implies that there may not be a disclosed trustworthy individual or group responsible for frameworks. Security of the present frameworks depends on estimating the firmness assumptions and large numbers of the benchmark cryptographic functions proven to be powerless for crucial monetary and a variety of applications against the approach of undeniable quantum machines. Upgrading blockchain innovation with the future of quantum states in a shared manner will enhance the degree of protection and security by-laws of physical science, which is never feasible from non-quantum data hypothetical perspectives. In this article, we propose a quantum-built way to deal with harness of security for a democratic application with the execution, utilizing Hyperledger Sawtooth.
Cross-contamination, counterfeit ingredients, false packaging, and labelling are all issues that contribute to food fraud which is a major concern undermining the integrity of the food supply chain and consumers health. Therefore, there is a need for an on-demand traceable, transparent food supply chain. This is a universal problem and blockchain presents itself as a means to maintain traceable, transparent food supply. This paper presents an innovative consensus algorithm and simulates the usage of it to identify the precision and recall of fraudulent food detection. This protocol aims to solve the issue of malicious leader node selection in common voting-based consensus protocols while achieving efficiency. Thus, providing a single version of truth for foods in a long food supply chain, preventing information asymmetries.
The error assessment is made on the classical Grey Model (GM(1,1)) and the variants of Grey Lotka-Volterra dynamical system namely the Grey Lotka-Volterra Model (GLVM), the Fractional Grey Lotka-Volterra Model (FGLVM) and the Variable-order Fractional Grey Lotka-Volterra Model (VFGLVM) for modeling the transaction counts of three selected cryptocurrencies in 2-and 3-dimensional framework. Bitcoin, Litecoin and Ripple. The cryptocurrencies of interest are Bitcoin, Litecoin and Ripple. The 2-dimensional models use Bitcoin and Litecoin transactions from April, 28, 2013 to February, 10, 2018. The 3-dimensional model uses transactions of Bitcoin, Litecoin and Ripple from August, 7, 2013 to February, 10, 2018. The error sequence patterns and the the Mean Absolute Percentage Error (MAPE) suggest a relatively higher accuracy of the VFLVM in 2- and 3-dimensional study.
Data security and privacy are one of the key concerns in the Internet of Things (IoT). Usage of IOT is increasing in the society day-by-day, and security challenges are becoming more and more severe. From a data perspective, IOT data security plays a major role. Some of the sensitive data such as criminal record, military information, the medical record of the patients, etc. Due to the size and other features of IOT, it is almost impossible to create an efficient centralized authentication system. The proposed system focused on IoT security for distributed medical record to provide perimeter security to the patient. Building trust in distributed environments without the need for authorities is a technological advance that has the potential to change many industries, the IOT is one among them. Furthermore, it protects data integrity and availability. It improves the accessibility of data by using the indexing method along with the blockchain. Moreover, it facilitate the utility of tracking the previous history of the patient record using the hyper ledger with authorization.
Ubiquitous sensing enabled by Wireless Sensor Network (WSN) technologies cuts across many areas of modern day living.This offers the ability to measure, infer and understand environmental indicators, from delicate ecologies and natural resources to urban environments.The proliferation of these devices in a communicating-actuating network creates the Internet of Things (IoT), wherein, sensors and actuators blend seamlessly with the environment around us, and the information is shared across platforms in order to develop a common operating picture (COP).Fuelled by the recent adaptation of a variety of enabling device technologies such as RFID tags and readers, near field communication (NFC) devices and embedded sensor and actuator nodes, the IoT has stepped out of its infancy and is the next revolutionary technology in transforming the Internet into a fully integrated Future Internet.As we move from www (static pages web) to web2 (social networking web) to web3 (ubiquitous computing web), the need for data-on-demand using sophisticated intuitive queries increases significantly.This paper gives very interesting understanding with IoT discussed with making as simple as possible not with the intention to reach concept only up to readers but to become understandable and friendly at students level with some text and basic models.
Recent interest around blockchains and Emerging smart contract systems over blockchain technology which allows mutually distrustful parties to transact safely without trusted third parties provided requirements good fit for the Smart Contracts sector. In the event of contractual breaches or cancellations, the decentralized blockchain ensures that honest parties get their just compensation. Blockchains permit us to have a distributed peer-to-peer network wherever non-trusting members can interact with each other without depending on an intermediary and be able to verify the transaction. All transactions, together with the flow of cash are exposed on the blockchain. A smart contract is used to 1) Facilitates for sharing of services and resources managing to the creation of a marketplace of services between devices and 2) permits us to automate in an exceedingly cryptographically verifiable manner many existing, long workflows My conclusion is that the smart contract over blockchain combination is powerful and can cause vital transformations across many industries, making new ways for new business models and innovative distributed applications.