Article

A Blockchain-Based Secure Healthcare Scheme with the Assistance of Unmanned Aerial Vehicle in Internet of Things

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Abstract

This paper introduces a blockchain-based secure healthcare scheme in which health data (HD) are collected from users via an unmanned aerial vehicle (UAV) and stored on the nearest server. In the proposed scheme, a UAV first establishes a relation with body sensor hives (BSHs) via a token and then shares a shared key with BSHs to enable low-power secure communication. After retrieving the HD, the UAV decrypts the encrypted HD (encrypted by a BSH) using the shared key and exercises a two-phase authentication mechanism. Upon successful validation, the UAV transmits the HD to the nearest server to store it securely in blockchain. A security analysis is discussed to show the feasibility of the proposed secure healthcare scheme. Finally, the performance of the proposed scheme is investigated through simulation and implementation. The security and the performance analysis demonstrate that the proposed scheme supports better assistance to BSHs while maintaining security.

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... Another category of the selected articles is related to the access control and includes two subcategories namely authorization (Pal et al., 2019), (Yang et al., 2019), , (Xu et al., 2019) and authentication (Aghili et al., 2019), (Arfaoui et al., 2019), (He and Zeadally, 2015), (Yeh, 2016), (Al-Turjman and Alturjman, 2018), (Deebak et al., 2019), (Huang et al., 2019), (Karimian et al., 2019), (Hou and Yeh, 2015), (Kumar and Gandhi, 2017), (Zhou and Piramuthu, 2018), (Jia et al., 2018), (Karthigaiveni and Indrani, 2019), (Merabet et al., 2019), (Sharma and Kalra, 2019), (Benadda et al., 2018), (Vaishnavi and Sethukarasi, 2020), (Alzahrani, 2020), (Sun et al., 2020), , (Xu, 2020), (Alladi and ChamolaNaren, 2020), (Sun et al., 2020), (Sahoo et al., 2020), (Fotouhi et al., 2020), (Islam and Young Shin, 2020). Pal et al. (Pal et al., 2019) introduced a policy-based access control to protect constrained resources in HIoT from unauthorized access. ...
... Fotouhi et al. (Fotouhi et al., 2020) proposed an authentication scheme based on the hash chain for WBANs in HIoT that provides security and authenticity with low computational and storage cost. Finally, Islam and Young Shin (Islam and Young Shin, 2020) proposed a secure healthcare design based on blockchain that provides some security features. ...
... Therefore, to reduce the risk of hacking essential data and to increase data protection such as a person's behavior pattern, habits, sleeping order, locations, and physical conditions over time-trust and privacy are very challenging as open issues. • Power management: Based on the studied literature, energy consumption (Wu et al., 2017), (Wu et al., 2018), (Niitsuet al., 2018), (Tekeste et al., 2019), (Hallforset al., 2018), (Ray et al., 2019d), (Yang et al., 2016), (He et al., 2017) Sensor-based and resource-based approaches Central South University, China (Chen et al., 2018), (Tang et al., 2019) Sensor-based and security-based approaches COMSATS Institute of Information Technology, Pakistan , Application-based approaches ESCP Business School, France (Zhou and Piramuthu, 2018), ( Jia et al., 2018) Security Security-based approaches Monash University, Australia (Wu et al., 2017), (Wu et al., 2018) Sensor-based approaches National Dong Hwa University, Taiwan (Yeh, 2016), (Hou and Yeh, 2015) Security-based approaches National Institute of Standards and Technology, USA (Laplante et al., 2018), ( Laplante et al., 2018) Application-based approaches Pennsylvania State University, USA (Laplante et al., 2018), ( Laplante et al., 2018) Application-based approaches Singapore Approaches University, Singapore Sensor-based approaches Widener University, USA (Laplante et al., 2018), ( Laplante et al., 2018) Application-based approaches Shahed University, Iran (Akhbarifar et al., 2020), ( Fotouhi et al., 2020) Communicationbased and resourcebased approaches National University of Singapore, Singapore (Sengupta and Bhunia, 2020), (Gope et al., 2020) Application-based and resource-based approaches Beirut Arab University, Lebanon (Muthuet al., 2020), (Huifeng et al., 2020) Sensor-based approaches (Elstset al., 2018), (Chen et al., 2018), (Abdelmoneem et al., 2020), (Awanet al., 2019), (Sengupta and Bhunia, 2020), (Minet al., 2019), (Bharathiet al., 2020), (Catarinucciet al., 2015), (Abdellatif et al., 2018), (Aktas et al., 2018), (Chehri and Mouftah, 2020), (Qiu et al., 2017), (Chanak and Banerjee, 2020), (Sharavana Kumar and Sarma Dhulipala, 2020), (Tuliet al., 2020), (Rahmaniet al., 2018), (Ramírez López et al., 2019), , (Vedaeiet al., 2020), (Boussada et al., 2019), (Tao et al., 2019), (Rani et al., 2019), (Hamza et al., 2020), (Yang et al., 2019), (Aghili et al., 2019), (Karimian et al., 2019), (Benadda et al., 2018), , (Xu, 2020), (Islam and Young Shin, 2020), (Li and Jing, 2019), (Gope and Hwang, 2016), (Ullah et al., 2020b) is the main open issue to decrease high operational costs and massive carbon production in HIoT systems. In addition, a typical HIoT network includes small devices with limited battery power. ...
Article
Internet of Things (IoT) is an ever-expanding ecosystem that integrates software, hardware, physical objects, and computing devices to communicate, collect, and exchange data. The IoT provides a seamless platform to facilitate interactions between humans and a variety of physical and virtual things, including personalized healthcare domains. Lack of access to medical resources, growth of the elderly population with chronic diseases and their needs for remote monitoring, an increase in medical costs, and the desire for telemedicine in developing countries, make the IoT an interesting subject in healthcare systems. The IoT has a potential to decrease the strain on sanitary systems besides providing tailored health services to improve the quality of life. Therefore, this paper aims to identify, compare systematically, and classify existing investigations taxonomically in the Healthcare IoT (HIoT) systems by reviewing 146 articles between 2015 and 2020. Additionally, we present a comprehensive taxonomy in the HIoT, analyze the articles technically, and classify them into five categories, including sensor-based, resource-based, communication-based, application-based, and security-based approaches. Furthermore, the benefits and limitations of the selected methods, with a comprehensive comparison in terms of evaluation techniques, evaluation tools, and evaluation metrics, are included. Finally, based on the reviewed studies, power management, trust and privacy, fog computing, and resource management as leading open issues; tactile Internet, social networks, big data analytics, SDN/NFV, Internet of nano things, and blockchain as important future trends; and interoperability, real-testbed implementation, scalability, and mobility as challenges are worth more studying and researching in HIoT systems.
... To bridge this gap, a blockchain-based secure data sharing framework needs to be designed. Researchers from both industry and academia proposed several data sharing frameworks for SDNs [4][5][6][7][8][9]. However, there are several limitations in those proposed systems such as follows: (i) Scalability-Most of the frameworks are designed to share data only within the organization or a certain location and thus, are not scalable beyond the boundary [5,8]; (ii) Access control-Most of the solutions focus on authenticity, confidentiality and integrity of the systems [4][5][6] whereas permitting or restricting access to the information (authorization) based on the type of users and their roles is also critical for secure data communication; (iii) Application specific-The frameworks are designed either to defend against particular attacks [5,9] or to facilitate data sharing for a particular group of entities (e.g. ...
... Researchers from both industry and academia proposed several data sharing frameworks for SDNs [4][5][6][7][8][9]. However, there are several limitations in those proposed systems such as follows: (i) Scalability-Most of the frameworks are designed to share data only within the organization or a certain location and thus, are not scalable beyond the boundary [5,8]; (ii) Access control-Most of the solutions focus on authenticity, confidentiality and integrity of the systems [4][5][6] whereas permitting or restricting access to the information (authorization) based on the type of users and their roles is also critical for secure data communication; (iii) Application specific-The frameworks are designed either to defend against particular attacks [5,9] or to facilitate data sharing for a particular group of entities (e.g. researchers) [7] and thus, failed to a provide a holistic solution for data sharing among different entities such as patients, health professionals, researchers and health insurers; (iv) Formal Security Analysis-Most of the papers provide an informal security analysis [6,8], however, it is important to formally analyze the protocols to discover flaws that failed to be detected by informal approaches. ...
... However, there are several limitations in those proposed systems such as follows: (i) Scalability-Most of the frameworks are designed to share data only within the organization or a certain location and thus, are not scalable beyond the boundary [5,8]; (ii) Access control-Most of the solutions focus on authenticity, confidentiality and integrity of the systems [4][5][6] whereas permitting or restricting access to the information (authorization) based on the type of users and their roles is also critical for secure data communication; (iii) Application specific-The frameworks are designed either to defend against particular attacks [5,9] or to facilitate data sharing for a particular group of entities (e.g. researchers) [7] and thus, failed to a provide a holistic solution for data sharing among different entities such as patients, health professionals, researchers and health insurers; (iv) Formal Security Analysis-Most of the papers provide an informal security analysis [6,8], however, it is important to formally analyze the protocols to discover flaws that failed to be detected by informal approaches. ...
Article
In the past few years, blockchain has proven its necessity and unprecedented prospects in providing a secure environment for information exchange between two parties. The integration of the Internet of Things (IoT) with blockchain has enabled a digital transformation in many areas such as healthcare, supply chain, and financial services. Like blockchain, the programmable Software-Defined Network (SDN) is also achieving popularity due to its ability to reduce network management complexity. It is evident that incorporating SDNs with IoT-based healthcare systems can significantly improve healthcare management services. However, there are a number of challenges such as data confidentiality, user-centric design, integrity and privacy that makes it difficult to share sensitive information among different parties in a healthcare system. To overcome these challenges, we propose an architectural framework that incorporates blockchain with Software-Defined Wireless Body Area Networks (SDWBANs) to facilitate secure data sharing. We have also designed and integrated a smart contract based fine-grained access control policy to ensure that only data owners will have full control over their health data. The experimental outcomes show that the proposed model achieves good throughput and incurs a very low overhead in terms of latency compared to traditional cloud-based systems.
... A comparative study of the proposed framework and other closely related frameworks is conducted. Various frameworks, for example, Liu [57], Aujla and Jindal's framework [58], and Islam and Shin's framework [59] are analysed and compared. The details of comparisons are given in Table 2. ...
... From [58], and Islam and Shin [59] do not provide required security and functionality features like "provides session-key agreement," "provides session key security under CK adversary model," "availability of password update phase," "availability of biometric update phase," "availability of dynamic controller node (personal server) addition phase," "availability of dynamic smart healthcare device addition," "provides formal security verification using AVISPA/ SCYTHER tool," and "provides formal security analysis under Real-or-Random (RoR) model." Moreover, Garg et al.' scheme [23] does not support feature like AI-based data analysis. ...
... Liu et al. [54] Garg et al. [23] Saha et al. [55] Xiang et al. [56] Xu et al. [57] Aujla and Jindal [58] Islam and Shin [59] Proposed framework ...
Article
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The Artificial Intelligence of Things (AIoT) is the amalgamation of Artificial Intelligence (AI) methods and the Internet of Things (IoT) infrastructure, which are deployed there to improve the overall performance of the system. AIoT can be deployed to achieve more efficient IoT operations; thereby can improve human-machine interactions and provide better data analysis. AI methods can be used to transform IoT data into useful information for the better decision-making processes, and it further increases the overall usability of the system. AIoT frameworks are very useful and applicable in a variety of applications, like security and surveillance system, smart home, intelligent transportation system, smart farming, secure and safe healthcare monitoring, industrial automation and control, eCommerce, logistics operations and control, and many more. However, AIoT frameworks may have issues related to data security and privacy as they are vulnerable to various types of information security-related attacks. These issues further cause the serious consequences, like the unauthorized data leakage and data update. Blockchain is a specific type of database. It is a digital ledger of transactions, which is duplicated and distributed across the entire network of computer systems. It stores data in the form of some blocks, which are then chained together. Blockchain is tamper proof and provides more security as compared to the traditional security mechanisms. Hence, blockchain can be integrated in various AIoT applications to provide more security. A generalized blockchain-envisioned secure authentication framework for AIoT has been proposed. The adversary model of blockchain-envisioned secure authentication framework for AIoT is also highlighted that covers most of the potential threats of a kind of communication environment. Various applications of the proposed framework are also discussed. Furthermore, different issues and challenges of the proposed framework are highlighted. In the end, we also provide some future research directions relevant to the proposed framework. 1. Introduction AIoT is the combination of Artificial Intelligence (AI) methods and Internet of Things (IoT) infrastructure. As we know, IoT is about different “Things” (i.e., smart IoT devices), which are connected to various users through the Internet [1–3]. AI provides methods to train the devices so that they can understand the novel data based on the training procedure that they have completed. AIoT works for a common goal, which is the generation of useful data about the world through IoT devices and drawing of useful insights from the collected data through some AI methods [4–9]. Artificial Intelligence (AI) refers to any human-like intelligence manifested by a machine, i.e., a computer and a robot. It is the ability of a machine, which mimics like the learning capabilities of the human, i.e., learning from the experience, object recognition, decision-making, and problem solving. It is an interdisciplinary science with multiple methods and tools, especially the advancements, which happen due to machine learning and deep learning creating a paradigm shift in various sectors of the tech industry [10–14]. 1.1. Common AI Technologies The following are the common AI technologies [1–3, 15–19]: (i)Speech recognition: speech recognition mechanism is used to convert and transform human speech in some useful format so that a computer application can process it. The “transcription and transformation of human language” into some useful format is in demand these days.(ii)Natural language processing (NLP): it focuses on the interactions between computers and human languages. Text analysis methods are used to analyse the structure of sentences and their interpretation through the ML algorithms. NLP is also helpful for the fraud detection systems. Automated assistants and applications derive unstructured data through NLP.(iii)Image recognition: it is the process of identification and detection of features in a video or an image file. It further facilitates the process of image searches for example, detecting license plates and diagnosis of diseases.(iv)Machine learning platforms: it is a subdiscipline of computer science and the important part of AI. The motive is to develop new mechanisms to enable the learning of computer systems to make them more intelligent. With the deployment of various algorithms, application programming interface (APIs), training tools, big data analytics, and machine learning platforms become popular these days, which are used for the purpose of categorization and predictions. The organizations like Amazon, Fractal Analytics, Google, and Microsoft provide various ML platforms as per the requirements of the customers.(v)Decision management: due to the AI logic and capabilities, machines can be used for training and maintenance. For adding value to the business and to make it more profitable, decision management system is being used. With the deployment of ML-based mechanisms, these systems execute automated decision.(vi)Deep learning platforms: the deep learning (DL) techniques use artificial neural networks. DL is another form of ML, which duplicates the neural network of human brain to process the data and draw patterns from this. These patterns are further used in the decision-making process. Some of the applications of DL are speech recognition system, image recognition system, and prediction system, which can predict about any phenomena of the digital sphere. Some of the DL platforms providers are Deep Instinct, Ersatz Labs, Fluid AI, and MathWorks.(vii)Robotic process automation: robotic process automation depicts the functioning of corporate processes, which automate the process through the mimicking of human activities and tasks. However, it is essential to mention that AI is not there to replace the humans, but to support and complement their skills and associated tasks. The organizations like automation anywhere, blue prism, and WorkFusion are working in this domain(viii)Cyber security: it is a computer defense mechanism, which detects and defends the various information security-related attacks happening in the cyber space. Neural networks, which have the ability to process sequences, can be deployed with ML techniques to create learning technologies for the mitigation of cyber attacks.(ix)Marketing automation: these days, AI is also going famous for marketing automation, especially to predict about the market trends, offers, and customers’ mood. That happens because of the advantages it put into the domain.(x)Virtual agents: a virtual agent can be a computer agent or a program, which has the ability of interaction with humans. It is used in customer service’s system via chat bots. The organizations like Apple, Google, Amazon, and Microsoft provide support through virtual agents. 1.2. Categories of Machine Learning Algorithms The different categories of machine learning algorithms are given below. 1.2.1. Supervised Learning Algorithms This class of algorithm uses labeled data to learn (training). There is a mapping function that turns input variables into the output variable . In other words, it solves function as per the following equation: Supervised learning algorithms are further divided into three categories, i.e., classification, regression, and ensembling. (1)Classification: in this method, variables are in the form of certain categories, and then, there is a prediction about the outcome of the given sample. A classification model might look at the input data and try to predict labels for example, in case of cyber attack detection, threat, or normal flow.(2)Regression: there are another categories of algorithms, which come under regression, which is used to predict the outcome of the given sample, in case when output variables are in the form of real values. A regression method may be used to process input data for the prediction of amount of rainfall and temperature in a specific week of a month.(3)Ensembling: for this particular category, a combination of different algorithms is used to produce better results, i.e., “Bagging with Random Forests” and “Boosting with AdaBoost.” “Linear Regression, Logistic Regression, CART, Naive-Bayes, and -Nearest Neighbors (KNN)” are examples of supervised learning algorithms. 1.2.2. Unsupervised Learning Algorithms These algorithms are used when only one input variable () is there and no corresponding output variables. The unlabeled training data is used to model the underlying structure of the data. Unsupervised learning algorithms are further divide into three categories, i.e., association, clustering, and dimensionality reduction. Their details are as follows: (1)Association: this method is used to find out the “probability of the cooccurrence of items in a collection.” Most of the time this technique is used in market-basket analysis. For example, it can be used to find out if a customer purchases shirt, he/she is 80% likely to also purchase trouser.(2)Clustering: this method is used to group samples such that objects in a cluster are more similar to each other than to the objects in the other clusters, i.e., K-means and clustering algorithm.(3)Dimensionality reduction: in unsupervised learning, there is another approach called as dimensionality reduction, which is used to reduce the number of variables of a dataset without omitting the important information. This can be done through “feature extraction methods” and “feature selection methods.” Feature selection mechanism selects a subset of the original variables whereas feature extraction does data transformation from a “high-dimensional space” to a “low-dimensional space.” Algorithm Principal Component Analysis (PCA) comes under feature extraction approach. Algorithms like Apriori, -means, and Principal Component Analysis (PCA) are examples of unsupervised learning. 1.2.3. Reinforcement Learning It is the another category of ML algorithms, which allows an agent to decide the next best action to be performed on the basis of its current state via learning behaviors, which will maximize a reward. These methods learn optimal actions in a trial and error way, for example, a video game in which the player has to move to certain places at certain times to earn more points. The player may correct his/her move on the basis of previous loses attempts. Examples of reinforcement learning algorithms are Q-Learning and State-Action-Reward-State-Action (SARSA). 1.2.4. Deep Learning Deep learning is another category of ML algorithms, which are inspired by the structure and function of the human brain. They are based on artificial neural networks and representation learning. They are concerned with building much larger and more complex neural networks. Deep learning algorithms are concerned with very large datasets of labelled analog data, i.e., image, text, audio, and video. Some of the popular deep learning algorithms are Generative Adversarial Network (GAN), Convolutional Neural Network (CNN), Recurrent Neural Networks (RNNs), and Long Short-Term Memory Networks (LSTMs). Here, learning can be performed in a supervised or unsupervised way. The different categories of machine learning along with algorithms are also depicted in Figure 1.
... ere is also a growing interest in introducing unmanned aerial vehicles (UAVs) as smart objects for collecting health data. In fact, UAVs can collect health data, encrypt them, and transmit them to authenticated body sensor hives using low-power secure communications [132]. ...
... Fog and edge computing, blockchainbased and SDN-enabled V2X communication, and Internet of drones can complete the available range of smart M-IoT services that include smart health, smart homes, smart cities, smart factories, smart agriculture, and smart transportation. As a result, more diverse smart services should be proposed, and the convergence of various fields will be promoted [101,102,132,221,302]. ...
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The smart mobile Internet-of-things (IoT) network lays the foundation of the fourth industrial revolution, the era of hyperconnectivity, hyperintelligence, and hyperconvergence. As this revolution gains momentum, the security of smart mobile IoT networks becomes an essential research topic. This study aimed to provide comprehensive insights on IoT security. To this end, we conducted a systematic mapping study of the literature to identify evolving trends in IoT security and determine research subjects. We reviewed the literature from January 2009 to August 2020 to identify influential researchers and trends of keywords. We additionally performed structural topic modeling to identify current research topics and the most promising ones via topic trend estimation. We synthesized and interpreted the results of the systematic mapping study to devise future research directions. The results obtained from this study are useful to understand current trends in IoT security and provide insights into research and development of IoT security.
... The proposed DezCom implemented on Robot Operation System (ROS) with the Tendermint consensus algorithms help. For securing data acquisition, the authors of [38][39][40] used blockchain technology for securing data gathered from IoT devices environment by drone technology. In [38], the findings showed that the proposed technologies' performance improves security, connectivity, and energy consumption. ...
... In [38], the findings showed that the proposed technologies' performance improves security, connectivity, and energy consumption. While [39] used blockchain technology for securing healthcare data gathered from IoT devices by drone. Blockchain technology, AI are applied for securing the drones collaboration [41], while the optimal techniques are used to ensure multi-drone collaboration task allocation with low energy consumption in a high level of security [42] and enable trustworthy communication among drones [43]. ...
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Currently, drones represent a promising technology for combating Coronavirus disease 2019 (COVID-19) due to the transport of goods, medical supplies to a given target location in the quarantine areas experiencing an epidemic outbreak. Drone missions will increasingly rely on drone collaboration, which requires the drones to reduce communication complexity and be controlled in a decentralized fashion. Blockchain technology becomes a must in industrial applications because it provides decentralized data, accessibility, immutability, and irreversibility. Therefore, Blockchain makes data public for all drones and enables drones to log information concerning world states, time, location, resources, delivery data, and drone relation to all neighbors drones. This paper introduces decentralized independent multi-drones to accomplish the task collaboratively. Improving blockchain with a consensus algorithm can improve network partitioning and scalability in order to combat COVID-19. The multi-drones task is to combat COVID-19 via monitoring and detecting, social distancing, sanitization, data analysis, delivering goods and medical supplies, and announcement while avoiding collisions with one another. We discuss End to End (E2E) delivery application of combination blockchain and multi-drone in combating COVID-19 and beyond future pandemics. Furthermore, the challenges and opportunities of our proposed framework are highlighted.
... The healthcare system based on blockchain (BHEALTH) is presented by Anik et al. in [127], wherein HD is gathered from a network of body sensors (BoS) and broadcast to the neighbor server by a UAV. In BHEALTH, a body sensor hive (BSH) is utilized to collect HD in one place from BoSs. ...
... UAV [127] Healthcare scheme security based on blockchain with UAVs in the IoT Defense with two-phase authentication Supports superior assistance to BSHs while keeping security BHEALTH does not regard as the confidentiality problem of the HD which needs more examination UAV [128] UAV and Drone privacy security using blockchain methodology Defense against cyberattacks ...
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Most natural disasters are consequences of hurricanes, floods, volcano eruptions, and earthquakes, and can severely disturb traditional communications networks and interrupt infrastructure of physical interconnection. After a disaster, communication failures are one of the essential causes of sufferers. To deal with this problem, offering “connectivity from the sky” is a novel and creative development. Aerial communications have been examined through the assessment and the design of the stratospheric platform capable of providing numerous types of wireless services. Drones, low and high-altitude platforms, airships, aircraft, and unmanned aerial vehicles (UAVs) are regarded as applicants for organizing aerial communications supplementing the infrastructure of global interaction. Aerial communication devices are vulnerable to being physically hijacked, destroyed, or lost. Therefore, security is a crucial issue in aerial communication networks. The blockchain technology is a potential solution candidate to tackle this issue. Blockchain is a decentralized and disseminated ledger, guards the distributed information using methods of cryptography, for example, public-key encryption and hash functions. It can use for guaranteeing the reliability of the data stored and for enhancing the transparency and security of aerial communication networks. This paper presents a survey on the integration of Blockchain with Aerial Communications (BAC). First, we study aerial communication networks and their current security issues, blockchain and its advantages, the feasibility and opportunity of applying the blockchain to resolve the current security issue in aerial communication networks. Next, we discuss current related solutions for applying the blockchain to resolve the current security issue in aerial communication networks in detail. We classify the solutions, compare and analyze their advantages and disadvantages. Finally, we recommend some research directions for future investigations.
... Basic user information is securely stored in a blockchain using smart contracts. Blockchain synchronizes the health data, secures the data with encryption, verifies the users and allows the UAV to store the data in the server [80], [81]. ...
... Edge computing was applied to a blockchain by providing two edge nodes, a resolution edge node, and a cache node. Resolution edge nodes provide The framework divides the network into multiple channels and each channel secures the data related to specific application collected from edge devices Smart healthcare [80] BHealth Blockchain, smart contract and MEC ...
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In recent years, blockchain networks have attracted significant attention in many research areas beyond cryptocur-rency, one of them being the Edge of Things (EoT) that is enabled by the combination of edge computing and the Internet of Things (IoT). In this context, blockchain networks enabled with unique features such as decentralization, immutability, and traceability, have the potential to reshape and transform the conventional EoT systems with higher security levels. Particularly, the convergence of blockchain and EoT leads to a new paradigm, called BEoT that has been regarded as a promising enabler for future services and applications. In this paper, we present a state-of-the-art review of recent developments in BEoT technology and discover its great opportunities in many application domains. We start our survey by providing an updated introduction to blockchain and EoT along with their recent advances. Subsequently, we discuss the use of BEoT in a wide range of industrial applications, from smart transportation, smart city, smart healthcare to smart home and smart grid. Security challenges in BEoT paradigm are also discussed and analyzed, with some key services such as access authentication, data privacy preservation, attack detection, and trust management. Finally, some key research challenges and future directions are also highlighted to instigate further research in this promising area.
... Review of Islam and Shin's scheme 42 Islam and Shin 42 proposed a "blockchain enabled scheme for the security of healthcare data. Some of the important features of Islam and Shin's scheme 42 are given below: ...
... In this section, we compared the performance of our proposed generalized framework (BIPHRS), and the schemes of Liu et al, 1 Garg et al, 4 Saha et al, 38 Xiang et al, 39 Xu et al, 40 Aujla and Jindal, 41 and Islam and Shin. 42 The details of comparative study are given in Table 1. During the comparative study, we consider the following important security and functionality features (SFF): ...
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The information system of healthcare operates through various frameworks, like wireless body area network, telecare medical information system, and mobile or electronic healthcare. All these systems need to maintain the personal health records (PHRs) for various users (ie, patients, doctors, and nurses). In such systems, we need to process and store the health related sensitive data (ie, PHRs). In this article, we aim to provide a robust security mechanism to secure exchange and storage of healthcare data, especially PHRs. We present a generic architecture of blockchain-enabled secure communication mechanism for Internet of Things-driven personal health records (BIPHRS). We then discuss various threats and security attacks of healthcare system along with different available security mechanisms. The conducted security analysis and detailed comparative study of the state of art blockchain enabled security schemes for PHR systems show that the proposed BIPHRS provides a better security and more functionality features as compared to other similar existing approaches.
... Basic user information is securely stored in a blockchain using smart contracts. Blockchain synchronizes the health data, secures the data with encryption, verifies the users and allows the UAV to store the data in the server [80], [81]. ...
... The asymmetric cryptography model was proposed to address security challenges between terminals and nodes. The experimental results show the algorithm's efficiency in terms of effective communication and computing costs, while The framework divides the network into multiple channels and each channel secures the data related to specific application collected from edge devices Smart healthcare [80] BHealth Blockchain, smart contract and MEC ...
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In recent years, blockchain networks have attracted significant attention in many research areas beyond cryptocurrency, one of them being the Edge of Things (EoT) that is enabled by the combination of edge computing and the Internet of Things (IoT). In this context, blockchain networks enabled with unique features such as decentralization, immutability, and traceability, have the potential to reshape and transform the conventional EoT systems with higher security levels. Particularly, the convergence of blockchain and EoT leads to a new paradigm, called BEoT that has been regarded as a promising enabler for future services and applications. In this paper, we present a state-of-the-art review of recent developments in BEoT technology and discover its great opportunities in many application domains. We start our survey by providing an updated introduction to blockchain and EoT along with their recent advances. Subsequently, we discuss the use of BEoT in a wide range of industrial applications, from smart transportation, smart city, smart healthcare to smart home and smart grid. Security challenges in BEoT paradigm are also discussed and analyzed, with some key services such as access authentication, data privacy preservation, attack detection, and trust management. Finally, some key research challenges and future directions are also highlighted to instigate further research in this promising area.
... The proposed DezCom implemented on Robot Operation System (ROS) with the Tendermint consensus algorithms help. For securing data acquisition, the authors of [38][39][40] used blockchain technology for securing data gathered from IoT devices environment by drone technology. In [38], the findings showed that the proposed technologies' performance improves security, connectivity, and energy consumption. ...
... In [38], the findings showed that the proposed technologies' performance improves security, connectivity, and energy consumption. While [39] used blockchain technology for securing healthcare data gathered from IoT devices by drone. Blockchain technology, AI are applied for securing the drones collaboration [41], while the optimal techniques are used to ensure multi-drone collaboration task allocation with low energy consumption in a high level of security [42] and enable trustworthy communication among drones [43]. ...
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Currently, drones represent a promising technology for combating Coronavirus disease 2019 (COVID-19) due to the transport of goods, medical supplies to a given target location in the quarantine areas experiencing an epidemic outbreak. Drone missions will increasingly rely on drone collaboration, which requires the drones to reduce communication complexity and be controlled in a decentralized fashion. Blockchain technology becomes a must in industrial applications because it provides decentralized data, accessibility, immutability, and irreversibility. Therefore, Blockchain makes data public for all drones and enables drones to log information concerning world states, time, location, resources, delivery data, and drone relation to all neighbors drones. This paper introduces decentralized independent multi-drones to accomplish the task collaboratively. Improving blockchain with a consensus algorithm can improve network partitioning and scalability in order to combat COVID-19. The multi-drones task is to combat COVID-19 via monitoring and detecting, social distancing, sanitization, data analysis, delivering goods and medical supplies, and announcement while avoiding collisions with one another. We discuss End to End (E2E) delivery application of combination blockchain and multi-drone in combating COVID-19 and beyond future pandemics. Furthermore, the challenges and opportunities of our proposed framework are highlighted.
... The proposed DezCom implemented on Robot Operation System (ROS) with the Tendermint consensus algorithms help. For securing data acquisition, the authors of [38][39][40] used blockchain technology for securing data gathered from IoT devices environment by drone technology. In [38], the findings showed that the proposed technologies' performance improves security, connectivity, and energy consumption. ...
... In [38], the findings showed that the proposed technologies' performance improves security, connectivity, and energy consumption. While [39] used blockchain technology for securing healthcare data gathered from IoT devices by drone. Blockchain technology, AI are applied for securing the drones collaboration [41], while the optimal techniques are used to ensure multi-drone collaboration task allocation with low energy consumption in a high level of security [42] and enable trustworthy communication among drones [43]. ...
Preprint
Full-text available
Currently, drones represent a promising technology for combating Coronavirus disease 2019 (COVID-19) due to the transport of goods, medical supplies to a given target location in the quarantine areas experiencing an epidemic outbreak. Drone missions will increasingly rely on drone collaboration, which requires the drones to reduce communication complexity and be controlled in a decentralized fashion. Blockchain technology becomes a must in industrial applications because it provides decentralized data, accessibility, immutability, and irreversibility. Therefore, Blockchain makes data public for all drones and enables drones to log information concerning world states, time, location, resources, delivery data, and drone relation to all neighbors drones. This paper introduces decentralized independent multi-drones to accomplish the task collaboratively. Improving blockchain with a consensus algorithm can improve network partitioning and scalability in order to combat COVID-19. The multi-drones task is to combat COVID-19 via monitoring and detecting, social distancing, sanitization, data analysis, delivering goods and medical supplies, and announcement while avoiding collisions with one another. We discuss End to End (E2E) delivery application of combination blockchain and multi-drone in combating COVID-19 and beyond future pandemics. Furthermore, the challenges and opportunities of our proposed framework are highlighted.
... The proposed DezCom implemented on Robot Operation System (ROS) with the Tendermint consensus algorithms help. For securing data acquisition, the authors of [38][39][40] used blockchain technology for securing data gathered from IoT devices environment by drone technology. In [38], the findings showed that the proposed technologies' performance improves security, connectivity, and energy consumption. ...
... In [38], the findings showed that the proposed technologies' performance improves security, connectivity, and energy consumption. While [39] used blockchain technology for securing healthcare data gathered from IoT devices by drone. Blockchain technology, AI are applied for securing the drones collaboration [41], while the optimal techniques are used to ensure multi-drone collaboration task allocation with low energy consumption in a high level of security [42] and enable trustworthy communication among drones [43]. ...
Article
Currently, drones represent a promising technology for combating Coronavirus disease 2019 (COVID-19) due to the transport of goods, medical supplies to a given target location in the quarantine areas experiencing an epidemic outbreak. Drone missions will increasingly rely on drone collaboration, which requires the drones to reduce communication complexity and be controlled in a decentralized fashion. Blockchain technology becomes a must in industrial applications because it provides decentralized data, accessibility, immutability, and irreversibility. Therefore, Blockchain makes data public for all drones and enables drones to log information concerning world states, time, location, resources, delivery data, and drone relation to all neighbors drones. This paper introduces decentralized independent multi-drones to accomplish the task collaboratively. Improving blockchain with a consensus algorithm can improve network partitioning and scalability in order to combat COVID-19. The multi-drones task is to combat COVID-19 via monitoring and detecting, social distancing, sanitization, data analysis, delivering goods and medical supplies, and announcement while avoiding collisions with one another. We discuss End to End (E2E) delivery application of combination blockchain and multi-drone in combating COVID-19 and beyond future pandemics. Furthermore, the challenges and opportunities of our proposed framework are highlighted.
... Blockchain is a network in which every participant holds the same copy of the data [14]. Blockchain promises properties such as pseudonymity, security, immutability, and distributed [15]. Blockchain adopted asymmetric encryption in which the public is used as an identity and the private key is used to verify the data [16]. ...
Conference Paper
In the modern era, the internet of vehicles (IoV) is being utilized in commercial applications and extensively explored in research. However, internal fault in IoV can cause accidents on the road. Moreover, privacy concerns can hamper the internal data sharing to build a model to detect the anomaly. Federated learning (FL) and blockchain are emerging technologies that can assist in mitigating these challenges. FL-based anomaly detection is introduced to prevent road accidents with the help of blockchain. An environment is built to conduct experiments to prove the feasibility of the proposed scheme. The performance analysis demonstrates that our presented scheme outperforms the traditional scheme while having privacy concerns.
... However, communication and data might be hampered by an attacker [5]. Blockchain is a revolutionary technology that introduces trust in the unknown environment and provides secure data and communication [6,7]. After considering the aforementioned challenges, this paper presents an HEC assisted disaster recovery scheme in which emergency services are provided in the disaster-affected areas using UxV and blockchain. ...
Conference Paper
Natural disasters visited countries every year more or less and left devastating situations behind, which affect both the economy and health. However, instantaneous actions can lessen casualties in the affected areas. Unmanned any vehicle (UxV) is a concept where unmanned vehicles come together and perform missions cooperatively. UxV can assist in rehabilitating the affected area. Multi-access edge computing (MEC) can assist UxVs in real-time. However, disaster might jeopardize MEC structure. Home edge computing (HEC) is a paradigm that stays closer to the end devices and enables an offline computation environment. HEC can fill up the gap and assist in maintaining the mission. Besides, networks and data are surrounded by security and privacy issues. This paper introduces a blockchain-based HEC assisted disaster rehabilitation and recovery scheme to restore everyday life using UxV. A proof of concept is considered for proving the feasibility.
... The most critical process is to convert the data into meaningful information. UAV can be used to detect vehicles using a deep learning (DL) model, but it requires considerable computational capability that reduces the operation time of UAV because of battery consumption [19]. ...
Article
In this paper, an automated real-time traffic management scheme is proposed by using unmanned aerial vehicles (UAV) in an effective and secured way. However, owing to the low computational capability and limited battery capacity of a UAV, multi-access edge computing (MEC) is applied to enhance the performance of an automated UAV-based traffic management scheme. Additionally, blockchain technology is introduced in the automated traffic management scheme to store the traffic record for providing network repudiation and avoiding any third-party interference with the network. An algorithm is developed based on the concept of a pairwise compatibility graph for the UAV-assisted automated traffic management scheme wherein a deep learning (DL) model is used for vehicle detection. Moreover, a two-phase authentication mechanism is proposed for a faster and secure verification process of the registered devices in the proposed scheme. Finally, a result analysis is conducted based on the security analysis and performance analysis to verify the effectiveness of the proposed scheme.
... The greatest challenge in the electronic and all-pervasive healthcare is securing the security of all internet-enabled devices [3]. Current times, several networks have been designed to make use mobile devices to provide mobilecentric services to consumers. ...
Article
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A secure, smart and peer-to-peer transactions framework can be developed by Blockchain. Blockchain has enormous potential to turn health care systems as a horizontal technology, which has changed many fields of industry. The aim of this article is to critically review 50 papers published between 2015 and 2020 on blockchain-based health systems. 36 of these were journal papers; 7 were from conferences, 4 were from various symposiums; 3 were from seminars and 1 chapter was written in the book. Three key questions will be answered in this report. Firstly, what are the emerging trends of blockchain application development in healthcare from a technical perspective? Secondly, in what ways will the systematic analysis presented here contribute to a better understanding of the potential for incorporating blockchain-based technologies into the healthcare domain? Third, what are the important challenges in adopting blockchain as a solution in the healthcare domain? The descriptive analysis contains in this article shows the statistical statistics on the strategies of these 50 papers reveal that many of the blockchain systems proposed are using privately held blockchain and Ethereum platforms. We also address possible emerging trends of blockchain application such as blockchain integration with artificial intelligence, cloud based solutions and parallel block chain architecture.
... UAVs have been used and explored in many fields, such as smart real estate [9,15], smart cities [55], healthcare [56], and others. In the disaster management field, UAVs have been explored for post-disaster management using IoT [57], energy-efficient task scheduling and physiological assessment [58], public safety in disaster and crisis management [59], flood management, and others [4]. ...
Article
Full-text available
Floods have been a major cause of destruction, instigating fatalities and massive damage to the infrastructure and overall economy of the affected country. Flood-related devastation results in the loss of homes, buildings, and critical infrastructure leaving no means of communication or travel for the people stuck in such disasters. Thus, it is essential to develop systems that can detect floods in a region to provide timely aid and relief to stranded people, save their livelihoods, homes, and buildings, and protect key city infrastructure. Flood prediction and warning systems have been implemented in developed countries, but the manufacturing cost of such systems is too high for developing countries. Remote sensing, satellite imagery, global positioning system, and geographical information systems are currently used for flood detection to assess the flood-related damages. These techniques use neural networks, machine learning, or deep learning methods. However, unmanned aerial vehicles (UAVs) coupled with convolution neural networks have not been explored in these contexts to instigate a swift disaster management response to minimize damage to infrastructure. Accordingly, this paper uses UAV-based aerial imagery as a flood detection method based on Convolutional Neural Network (CNN) to extract flood-related features from the images of the disaster zone. This method is effective in assessing the damage to local infrastructures in the disaster zones. The study area is based on a flood-prone region of the Indus River in Pakistan, where both pre-and post-disaster images are collected through UAVs. For the training phase,2150 image patches are created by resizing and cropping the source images. These patches in the training dataset train the CNN model to detect and extract the regions where a flood-related change has occurred. The model is tested against both pre-and post-disaster images to validate it, which has positive flood detection results with an accuracy of 91%. Disaster management organizations can use this model to assess the damages to critical city infrastructure and other assets worldwide to instigate proper disaster responses and minimize the damages. This can help with the smart governance of the cities where all emergent disasters are addressed promptly.
... Not considered the channel characteristics for data exchange between the patients and the doctors. Islam et al. [123] 2020 ...
Article
Nowadays, increasing urbanization has necessitated the social, environmental, and economic development of cities to enhance the Quality of Life (QoL) significantly and introduces the ``Smart City" concept. It integrates Information and Communication Tools (ICT), Internet of Things (IoT), and other technologies to resolve urban challenges. The key goal is to make the most acceptable use of available resources and technologies to develop smart cities. An IoT-enabled application plays a crucial role here, but it has various security, privacy, latency, and reliability issues with a single-point-of-failure problem. The evolving technology blockchain can handle the aforementioned security and privacy issues and provide high-quality services due to several features like transparency, trust-free, decentralization, immutability, and others. The 6G communication network takes care of latency and reliability issues in the smart city with their unique characteristics such as latency ($10-100 \mu s$) and reliability (99.99999\%). Motivated by these facts, in this paper, we presented a comprehensive review for blockchain technology and IoT together functional to smart cities. First, state-of-art-the works and contextual information are introduced. Then, we proposed a blockchain-based decentralized architecture for IoT-integrated smart cities covering different application perspectives, such as smart grid, Intelligent Transportation System (ITS), and healthcare 5.0 underlying 6G communication networks. Next, we describe the challenges of the proposed architecture respective to each application, as mentioned above. Finally, we collated the open research issues and future direction to efficiently integrate blockchain into IoT-envisioned smart cities.
... In order to improve the surgical treatment effect of nerve block patients and promote the rehabilitation process of patients, nerve block anesthesia patients are given routine care and psychological care based on routine care, respectively. Ultrasound-guided peripheral nerve block anesthesia types of subclavian brachial plexus block should be performed using a frequency of 4-7 MHz arc probe [18], and the probe is placed in the downward depressed position of the clavicle 1 cm away from the rostral prominence position of the patient. e patient's brachial plexus nerve is clearly observed to show a grape-like shape of low-density ring-shaped hyperechoic, and the phenomenon of anesthetic drug wrapping the nerve is visible after performing the block. ...
Article
Full-text available
In the process of surgical treatment, the introduction of ultrasound technology to implement nerve block anesthesia can make the operations of patients with fractures under visualization and it can also significantly improve the anesthesia effect. With this technology, it is possible to minimize the anesthesia operation causing accidental injury and lay a good foundation for the smooth operation of surgical treatment. Blockchain technology is a new decentralized infrastructure and distributed computing paradigm. This technology has great development opportunities in the medical field and is expected to play an important role in the construction of Internet medical ecology. This study aims to investigate the effect of ultrasound-guided nerve block anesthesia on fracture treatment in the context of blockchain. This method has high application value and potential in medical data sharing, reducing treatment costs, improving the medical claims system, strengthening medical management, and optimizing medical decision-making using blockchain technology. This study also addresses the uniqueness and complexity of ultrasound-guided nerve block anesthesia itself and analyzes the effect of the proposed method. The analysis shows that using the internet-based blockchain ultrasound-guided subacromial nerve block anesthesia for fracture patients is effective, and the patient's vital signs are stable, and the block is effective.
... Additionally, it is explained in [38] how a blockchainbased healthcare system (referred to as BHEALTH) can make use of UAVs. The healthcare data structure that has been elaborated in this case relies on elements like an Enterprise Server running in a private cloud, along with other elements like a mobile core network connected to a MEC server that, at the same time, is connected to a Ground Control Station (GCS) used to command a collection of UAVs. ...
Article
Full-text available
Security attacks on Cyber-Physical Systems with operations that involve Unmanned Aerial Vehicles (UAVs) are a matter of great concern due to their major impact in the deployed systems, and a deal-breaker for their utilization; if a system is not perceived as secure, either it will not be used or its capabilities will be underutilized, regardless of how good they could be. This happens with particular intensity in missions with UAVs, as they can be hacked to tamper with their collected data or taken away by unauthorized parties. Development of security countermeasures is extensive both in theoretical and practical implementations, but the integration of these measures can be difficult, and performance might be affected because of it. This manuscript puts forward a SEDIBLOFRA (Secure, Distributed, Blockchain-based Framework) for remote maneuvering of UAVs, based on several distributed systems technologies that pile up to provide complementary functionalities. Asymmetric cryptography encrypts the data. Publish/Subscribe communications offer a way to enhance data delivery. Finally, blockchain provides a way to keep all the transferred data in a redundant and immutable manner. The proposed framework is also extensible to other kinds of unmanned vehicles, like Unmanned Ground Vehicles or Autonomous Underwater Vehicles.
... It was verified that the proposed solution is more efficient in terms of performance than other schemes. The authors of [34] established an association with body sensors using tokens, and afterward, a secret key is shared to provide data security. The proposed solution encrypts and decrypts the health data with two phases of the authentication method using the private key. ...
Article
Full-text available
Internet of Things (IoT) performs a vital role in providing connectivity between computing devices, processes, and things. It significantly increases the communication facilities and giving up-to-date information to distributed networks. On the other hand, the techniques of artificial intelligence offer numerous and valuable services in emerging fields. An IoT-based healthcare solution facilitates patients, hospitals, and professionals to observe real-time and critical data. In the literature, most of the solution suffers from data intermission, high ethical standards, and trustworthiness communication. Moreover, network interruption with recurrent expose of sensitive and personal health data decreases the reliance on network systems. Therefore, this paper intends to propose an IoT solution for AI-enabled privacy-preserving with big data transferring using blockchain. Firstly, the proposed algorithm uses a graph-modeling to develop a scalable and reliable system for gathering and transmitting data. In addition, it extracts the subset of nodes using the artificial intelligence approach and achieves efficient services for the healthcare system. Secondly, symmetric based digital certificates are utilized to offer authentic and confidential transmission with communication resources using blockchain. The proposed algorithm is explored with existing solutions through multiple simulations and proved improvement in terms of realistic parameters.
... IoT technologies lead the modern world into tremendous technological growth in terms of data management, communication, and information sharing [1]. With these developments, the modern world has gained massive advantages by utilizing technological equipment especially Bluetooth devices, WSN technology, Wi-Fi, Li-Fi, and RFID. ...
Article
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The health system in today’s real world is significant but difficult and overcrowded. These hurdles can be diminished using improved health record management and blockchain technology. These technologies can handle medical data to provide security by monitoring and maintaining patient records. The processing of medical data and patient records is essential to analyze the earlier prescribed medicines and to understand the severity of diseases. Blockchain technology can improve the security, performance, and transparency of sharing the medical records of the current healthcare system. This paper proposed a novel framework for personal health record (PHR) management using IBM cloud data lake and blockchain platform for an effective healthcare management process. The problem in the blockchain-based healthcare management system can be minimized with the utilization of the proposed technique. Significantly, the traditional blockchain system usually decreases the latency. Therefore, the proposed technique focuses on improving latency and throughput. The result of the proposed system is calculated based on various matrices, such as F1 Score, Recall, and Confusion matrices. Therefore, the proposed work scored high accuracy and provided better results than existing techniques.
... Taking advantages of recent advancement and development in information and communication technology, unmanned aerial vehicles have been employed to perform some special tasks in real-world applications [10]. In [11], Islam and Shin proposed a blockchain-based solution for safe healthcare, which uses the unmanned aerial vehicle (UAV) to collect health data (HD) from users. Liu et al. [1] presented a detailed survey on the opportunities and challenges of IoE supported by unmanned aerial vehicles. ...
Article
Full-text available
In unmanned aerial vehicle networks (UAVNs), unmanned aerial vehicles with restricted computing and communication capabilities can perform tasks in collaborative manner. However, communications in UAVN confront many security issues, for example, malicious entities may launch impersonate attacks. In UAVN, the command center (CMC) needs to perform mutual authentication with unmanned aerial vehicles in clusters. The aggregator (AGT) can verify the authenticity of authentication request from CMC; then, the attested authentication request is broadcasted to the reconnaissance unmanned aerial vehicle (UAV) in the same cluster. The authentication responses from UAVs can be verified and aggregated by AGT before being sent to CMC for validation. Also, existing solutions cannot resist malicious key generation center (KGC). To address these issues, this paper proposes a pairing-free authentication scheme (CLAS) for UAVNs based on the certificateless signature technology, which supports batch verification at both AGT and CMC sides so that the verification efficiency can be improved greatly. Security analysis shows that our CLAS scheme can guarantee the unforgeability for (attested) authentication request and (aggregate) responses in all phases. Performance analysis indicates that our CLAS scheme enjoys practical efficiency.
... The interoperability of Blockchain technology will enable doctors to conveniently view the detailed medical records to help diagnose their diagnosis and develop a better and more precise operation. [114][115][116][117][118] 14 Minimise data transformation time and cost ...
Article
Full-text available
Blockchain is an emerging technology being applied for creating innovative solutions in various sectors, including healthcare. A Blockchain network is used in the healthcare system to preserve and exchange patient data through hospitals, diagnostic laboratories, pharmacy firms, and physicians. Blockchain applications can accurately identify severe mistakes and even dangerous ones in the medical field. Thus, it can improve the performance, security, and transparency of sharing medical data in the health care system. This technology is helpful to medical institutions to gain insight and enhance the analysis of medical records. In this paper, we studied Blockchain technology and its significant benefits in healthcare. Various Capabilities, Enablers, and Unified Work-Flow Process of Blockchain Technology to support healthcare globally are discussed diagrammatically. Finally, the paper identifies and debates fourteen significant applications of Blockchain for healthcare. Blockchain plays a decisive part in handling deception in clinical trials; here, the potential of this technology offer is to improve data efficiency for healthcare. It can help avoid the fear of data manipulation in healthcare and supports a unique data storage pattern at the highest level of security. It provides versatility, interconnection, accountability, and authentication for data access. For different purposes, health records must be kept safe and confidential. Blockchain helps for the decentralised protection of data in healthcare and avoids specific threats.
... The Internet of Drones (IoDs) is a network in which a maintains controlled airspace of drones (which are known as Unmanned Aerial Vehicle (UAV) to contribute to diverse application areas [5], such as battlefield [6], healthcare [7], smart factory, etc. IoD gains a lot of popularity due to its prominent functionalities (e.g., access to any location) [8]. Initially, IoD was introduced for military purposes, later, civilians accept it abruptly in various applications, such as package delivery, search and rescue, agriculture, and surveillance [9]. ...
Conference Paper
The modern era is filled with smart entities (e.g., smart vehicles) that have both sense and actuate capabilities. These entities can collect lots of data during their functional period and these data can be utilized for the wellbeing of citizens. However, these data are very sensitive raising issues like privacy. Moreover, network scarcity, bandwidth consumption, etc. can worsen the circumstance. Federated learning (FL), internet of drones (IoD), and dew computing (DC) are revolutionary technologies that can be engaged to mitigate the aforementioned challenges. An FL-based computing paradigm is initiated over the dew computing to process road-related data to bring efficiency in the applications (e.g., finding parking locations) utilizing IoD. An experimental environment is established containing a traffic dataset as a proof of concept. The experimental results exhibit the feasibility of the proposed scheme.
... In another related study, [31], patient data through remote patient monitoring is used to detect and forecast the status of a patient's health condition using IoT. Islam et al. in [42] used UAV to collect data from patients and, using blockchain, the security of data is ensured, thus human involvement is reduced. In another related paper, Islam et al. in [43] proposed a system that ensures low human engagement for monitoring the outbreak with a drone based automatic pandemic tracking system. ...
Preprint
The ever-evolving and contagious nature of the Coronavirus (COVID-19) has immobilized the world around us. As the daily number of infected cases increases, the containment of the spread of this virus is proving to be an overwhelming task. Healthcare facilities around the world are over-burdened with an ominous responsibility to combat an ever-worsening scenario. To aid the healthcare system, Internet of Things (IoT) technology provides a better solution-tracing, testing of COVID patients efficiently is gaining rapid pace. This study discusses the role of IoT technology in health-care during the SARS-CoV-2 pandemics. The study overviews different research, platforms, services, products where IoT is used to combat the COVID-19 pandemic. Further, we intelligently integrate IoT and healthcare for COVID-19 related applications. Again, we focus on a wide range of IoT applications in regards to SARS-CoV-2 tracing, testing, and treatment. Finally, we effectively consider further challenges, issues, and some direction regarding IoT in order to uplift the healthcare system during COVID-19 and future pandemics.
... In another related study, [31], patient data through remote patient monitoring is used to detect and forecast the status of a patient's health condition using IoT. Islam et al. in [42] used UAV to collect data from patients and, using blockchain, the security of data is ensured, thus human involvement is reduced. In another related paper, Islam et al. in [43] proposed a system that ensures low human engagement for monitoring the outbreak with a drone based automatic pandemic tracking system. ...
Article
Full-text available
The ever-evolving and contagious nature of the Coronavirus (COVID-19) has immobilized the world around us. As the daily number of infected cases increases, the containment of the spread of this virus is proving to be an overwhelming task. Healthcare facilities around the world are overburdened with an ominous responsibility to combat an ever-worsening scenario. To aid the healthcare system, Internet of Things (IoT) technology provides a better solution—tracing, testing of COVID patients efficiently is gaining rapid pace. This study discusses the role of IoT technology in healthcare during the SARS-CoV-2 pandemics. The study overviews different research, platforms, services, products where IoT is used to combat the COVID-19 pandemic. Further, we intelligently integrate IoT and healthcare for COVID-19 related applications. Again, we focus on a wide range of IoT applications in regards to SARS-CoV-2 tracing, testing, and treatment. Finally, we effectively consider further challenges, issues, and some direction regarding IoT in order to uplift the healthcare system during COVID-19 and future pandemics.
... Blockchain is used in various domains to provide security to the models developed in the respective domains. Studies have revealed that the major domains in which the blockchain technology such as Cybersecurity, Helathcare, Internet of Things [3]. This work concentrates on studying the various state of art models pertaining to the usage of the blockchain technology in Health care in order to improve the security in various means.It is also observed that there is a trend towards usage of healthcare data in the cloud environment. ...
Chapter
Full-text available
Security is a major concern in every technology that is introduced newly to facilitate the existing mechanism for better maintenance and handling. This is also the case in electronic health records. The data of the hospitals and the associated patients gets digital in the past few decades. The data is stored in the cloud for various reasons such as convenience of the participating entities to access it, easy maintenance. But, with this there also arises various security concerns. It has been observed from the reason studies that blockchain is used as the means of securing the healthcare data in the cloud environment.This study discusses the following. 1) Applications of blockchain in cloud environment, 2) Applications of blockchain in securing healthcare data 3) General issues and security concerns in blockchain technology and what features of block chain makes it suitable for securing health care a nd what features restricts it from using.This work helps the future researchers in getting a deep understanding of the in and out of applying blockchain in cloud and healthcare environment.
... Similarly, Islam et al. [88] proposed the same idea as [87] of implementing the UAV with MEC. Although the idea is the same, the way of implementation is quite different. ...
Article
Full-text available
In this era of modern digital technologies, the Internet of Vehicles (IoVs) is omnipresent and can be used for varied purposes. However , these devices have scalability, security, and connection issues. To address the IoV security issues, BC technology is a viable solution. BC offers decentralization, transparency, immutability, and privacy, which can be useful to IoVs. The 5G technologies have not been fully commercialized and the researchers have started exploring the 6G technologies. The 6G technologies can help provide ultra-low latency communication between the devices. It also supports communication in heterogeneous networks like IoVs in various application scenarios such as healthcare, smart city, and traffic management. Motivated from the above discussion, we present a survey on the adoption of BC in IoVs underlying 6G communication. We have also explored various privacy and security concerns in IoVs, which can be perfectly addressed via BC technology. The 6G communication takes care of latency, reliability, and connectivity issues. We have categorized the existing literature based on the taxonomy and presented a comparative study of all the existing state-of-the-art approaches based on their merits and demerits. Finally, we have highlighted some of the open issues and research challenges that opens the doors for beginners who are willing to start work in this amazing area.
... Unfortunately, predators and attackers are already leveraging this scenario, and since January 2020, more than 16,000 unique coronavirus-related domains have been registered in coronavirus-themed malicious websites. Hackers are marketing ransomware and intrusion tools through COVID-19 darknet discount codes, many of which are targeted at accessing company data from home workers' laptops [7]. ...
Chapter
Drone-based dynamic model and control techniques vary from classical linear proportional integral derivative (CPID) to complex non-linear multiconstrained and multi-objective schemes such as backstepping, sliding window mode, size-based models and operation-based models etc. These approaches can be classified as per their usage. Thus, some will be efficient for indoor operations and others will be useful for outdoor operations. The performance of both types of drone-based smart healthcare systems can be measured in terms of stabilizing the attitude for both indoor and outdoor operations as per requirements. Further, gain-based drone-scheduling is commonly used in flight controllers. In COIVD19 pandemic situations, the gains can be measured using an alternative way. Here, different parameters like medication advantage to COVID-19 pandemic areas, identifying the COVID-19 hotspots, sanitizing requirements and potentials, finding the COVID-19 chain etc. could be considered in gain measurement for the deployment of drone-based COVID-19’s smart healthcare. This work proposes a multi-constraint and multi-objective gain-based simulation-optimization approach for scheduling the linear and non-linear dynamic and controllable drone-movement models. The proposed model considered the identity-based lower and upper limits of control interface Further, this interface is having the provision to include some human factors in its execution. The performance of the overall system is measured using performance and security metrics. In performance, drone-based smart healthcare systems’ efficiency, accuracy, and effectiveness are measured. The measurements are analyzed by varying optimizationparameters. In the security, lightweight cryptography primitives and protocols are analyzed for performance measurements. These lightweight cryptography primitives and protocols ensure secure data storage, transmission and processing at any device. Further, the scope of centralized and distributed systems of dronescooperations for COVID-19 monitoring, sanitization, cleaning, and control room will be explored to have time-saving and autonomous drone-based smart healthcare systems.
... This scheme was designed to help control the spread of viruses by ensuring that people follow the guidelines and performing surveillance checks (e.g., face coverings, temperature measurements, and social distancing). Similarly, the work by [21] proposed the use of blockchain technology along with unmanned aerial vehicles (UAVs) for patient data collection within healthcare. It uses UAVs to collect data and a blockchain to store the collected data. ...
Article
Full-text available
In this study, a new blockchain protocol and a novel architecture that integrate the advantages offered by edge computing, artificial intelligence (AI), IoT end-devices, and blockchain were designed, developed, and validated. This new architecture has the ability to monitor the environment, collect data, analyze it, process it using an AI-expert engine, provide predictions and actionable outcomes, and finally share it on a public blockchain platform. For the use-case implementation, the pandemic caused by the wide and rapid spread of the novel coronavirus COVID-19 was used to test and evaluate the proposed system. Recently, various authors traced the spread of viruses in sewage water and studied how it can be used as a tracking system. Early warning notifications can allow governments and organizations to take appropriate actions at the earliest stages possible. The system was validated experimentally using 14 Raspberry Pis, and the results and analyses proved that the system is able to utilize low-cost and low-power flexible IoT hardware at the processing layer to detect COVID-19 and predict its spread using the AI engine, with an accuracy of 95%, and share the outcome over the blockchain platform. This is accomplished when the platform is secured by the honesty-based distributed proof of authority (HDPoA) and without any substantial impact on the devices’ power sources, as there was only a power consumption increase of 7% when the Raspberry Pi was used for blockchain mining and 14% when used to produce an AI prediction.
... The authors in [10] have proposed the BHEALTH, a blockchain-based architecture to secure UAV-based healthcare systems. Then, Aggarwal et al. [11] presented a blockchain-based Healthcare 4.0 architecture with UAV Path Planning. ...
Article
Full-text available
The sudden demand rises in security made researchers come up with solutions that provide instantaneous safety better than the state of the art solutions. The quest for securing data began in the Spartan era. People are now looking to expand this field of research by attacking the existing paradigms and inventing new algorithms that prove to be better than their vulnerable counterparts. Unmanned aerial vehicles (UAVs) are very much prevailing due to their sleek design and flexible mobility in many sectors such as agriculture, army, healthcare, monitoring and surveillance, and many more. We discuss the growth and demand of drone technology along with its importance in this article. The paper also throws some light on the ongoing security issues in real-time scenarios and the role of quantum cryptography in securing the information over the traditional solutions. Motivated by this, we present a survey on quantum cryptography's importance, role, and benefits in securing UAV communications underlying beyond 5G networks. A novel quantum cryptography-based layered architectural solution is also proposed to achieve high data security and efficient transmission. This paper also presents a case study on the battlefield application on the Internet of military things. The performance of the proposed case study system is evaluated by considering the latency, security, and reliability. INDEX TERMS Unmanned aerial vehicle, quantum computing, quantum cryptography, military, blockchain.
... Nassar et al. [171] implemented DITrust chain using Ethereum and Ripple for securing trust in IoT healthcare systems. Islam et al. [172] propounded a blockchain-based healthcare scheme for assisting Unmanned Aerial Vehicles (UAV) in providing security to health data collected from users using UAV and stored on the nearest server in the UAV path. Miyachi et al. [173] presented hOCBS, a privacypreserving blockchain-based framework for leveraging healthcare using on-chain and off-chain system design. ...
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This is a monumental reference for the theory and practice of computer security. Comprehensive in scope, this text covers applied and practical elements, theory, and the reasons for the design of applications and security techniques. It covers both the management and the engineering issues of computer security. It provides excellent examples of ideas and mechanisms that demonstrate how disparate techniques and principles are combined in widely-used systems. This book is acclaimed for its scope, clear and lucid writing, and its combination of formal and theoretical aspects with real systems, technologies, techniques, and policies.
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The unmanned aerial vehicle (UAV) is a promising enabler of the Internet of Things (IoT) vision, due to its agile maneuverability. In this paper, we explore the potential gain of UAV-aided data collection in a generalized IoT scenario. Particularly, a composite channel model including both large-scale and small-scale fading is used to depict typical propagation environments. Moreover, rigorous energy constraints are considered to characterize IoT devices as practically as possible. A multi-antenna UAV is employed, which can communicate with a cluster of single-antenna IoT devices to form a virtual MIMO link. We formulate a whole-trajectory-oriented optimization problem, where the transmission duration and the transmit power of all devices are jointly designed to maximize the data collection efficiency for the whole flight. Different from previous studies, only the slowly-varying large-scale channel state information (CSI) is assumed available, to coincide with the fact that practically it is quite difficult to predictively acquire the random small-scale channel fading prior to the UAV flight. We propose an iterative scheme to overcome the non-convexity of the formulated problem. The presented scheme can provide a significant performance gain over traditional schemes and converges quickly.
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Understanding of any computing environment requires familiarity with its underlying technologies. Internet of Things (IoT), being a new era of computing in the digital world, aims for the development of large number of smart devices that would support a variety of applications and services. These devices are resource‐constrained, and the services they would provide are going to impose specific requirements, among which security is the most prominent one. Therefore, in order to comprehend and conform these requirements, there is a need to illuminate the underlying architecture of IoT and its associated elements. This comprehensive survey focuses on the security architecture of IoT and provides a detailed taxonomy of major challenges associated with the field and the key technologies, including Radio Frequency Identification (RFID) and Wireless Sensor Networks (WSN), that are enabling factors in the development of IoT. The paper also discusses some of the protocols suitable for IoT infrastructure and open source tools and platforms for its development. Finally, a brief outline of major open issues, along with their potential solutions and future research directions, is given.
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Mobile Cloud Computing is a new technology which refers to an infrastructure where both data storage and data processing operate outside of the mobile device. Another recent technology is Internet of Things. Internet of Things is a new technology which is growing rapidly in the field of telecommunications. More specifically, IoT related with wireless telecommunications. The main goal of the interaction and cooperation between things and objects which sent through the wireless networks is to fulfill the objective set to them as a combined entity. In addition, there is a rapid development of both technologies, Cloud Computing and Internet of Things, regard the field of wireless communications. In this paper, we present a survey of IoT and Cloud Computing with a focus on the security issues of both technologies. Specifically, we combine the two aforementioned technologies (i.e Cloud Computing and IoT) in order to examine the common features, and in order to discover the benefits of their integration. Concluding, we present the contribution of Cloud Computing to the IoT technology. Thus, it shows how the Cloud Computing technology improves the function of the IoT. Finally, we survey the security challenges of the integration of IoT and Cloud Computing.
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Internet usage has become a facet of everyday life, especially as more technological advances have made it easier to connect to the web from virtually anywhere in the developed world. However, with this increased usage comes heightened threats to security within digital environments. The Handbook of Research on Modern Cryptographic Solutions for Computer and Cyber Security identifies emergent research and techniques being utilized in the field of cryptology and cyber threat prevention. Featuring theoretical perspectives, best practices, and future research directions, this handbook of research is a vital resource for professionals, researchers, faculty members, scientists, graduate students, scholars, and software developers interested in threat identification and prevention.
IoT based remote health monitoring system for patients and elderly people
  • M Hamim
  • S Paul
  • S I Hoque
  • M N Rahman
  • I Baqee
Hamim M, Paul S, Hoque SI, Rahman MN, Baqee I. IoT based remote health monitoring system for patients and elderly people. In: Proceedings of the international conference on robotics, electrical and signal processing techniques (ICREST); 2019. p. 533-8. doi: 10.1109/ICREST.2019.8644514.
Real-time secure health surveillance for smarter health communities
  • A Alabdulatif
  • I Khalil
  • Arm Forkan
  • M Atiquzzaman
Alabdulatif A, Khalil I, Forkan ARM, Atiquzzaman M. Real-time secure health surveillance for smarter health communities. IEEE Commun Mag 2019;57(1):122-9. doi: 10.1109/MCOM.2017.1700547.