The Metaverse is gaining attention among academics as maturing technologies empower the promises and envisagements of a multi-purpose, integrated virtual environment. An interactive and immersive socialization experience between people is one of the promises of the Metaverse. In spite of the rapid advancements in current technologies, the computation required for a smooth, seamless and immersive socialization experience in the Metaverse is overbearing, and the accumulated user experience is essential to be considered. The computation burden calls for computation offloading, where the integration of virtual and physical world scenes is offloaded to an edge server. This paper introduces a novel Quality-of-Service (QoS) model for the accumulated experience in multi-user socialization on a multichannel wireless network. This QoS model utilizes deep reinforcement learning approaches to find the near-optimal channel resource allocation. Comprehensive experiments demonstrate that the adoption of the QoS model enhances the overall socialization experience.
Musharraf N. Alruwaill, Saraju P. Mohanty, Elias Kougianos
In smart healthcare, blockchain technology addresses existing concerns with security, privacy, and electronic healthcare records. In addition, utilizing edge devices with IoMT devices is very advantageous for addressing security, computing, and storage challenges. Symmetric and asymmetric keys are used to conceal sensitive information from unauthorized parties. Moreover, the hash function SHA256 helps for data alteration detection. The proposed system uses a blockchain-based smart healthcare system using IoMT devices for continuous patient monitoring. The edge device is used to hash and encrypt data and provide additional computational capability. A symmetric key maintains data privacy in the blockchain, allowing patients to safely share data through smart contracts while preventing unauthorized physicians from seeing it. A verification node and blockchain sign and validate patient data in the healthcare provider system using an asymmetric key. Location-based authentication is addressed to ensure the authenticity and data source.
A. Ezil Sam Leni, Rajendran Shankar, R. Thiagarajan, Vishal Ratansing Patil
The medical sector actively changes and implements innovative features in response to technical development and revolutions.Many of the most crucial elements in IoT-connected health services are safeguarding critical patient records from prospective attackers.As a result, BlockChain (BC) is gaining traction in the business sector owing to its large implementations.As a result, BC can efficiently handle everyday life activities as a distributed and decentralized technology.Compared to other industries, the medical sector is one of the most prominent areas where the BC network might be valuable.It generates a wide range of possibilities and probabilities in existing medical institutions.So, throughout this study, we address BC technology's widespread application and influence in modern medical systems, focusing on the critical requirements for such systems, such as trustworthiness, security, and safety.Furthermore, we built the shared ledger for blockchain-based healthcare providers for patient information, contractual between several other parties.The study's findings demonstrate the usefulness of BC technology in IoHT for keeping patient health data.The BDSA-IoHT eliminates 2.01 seconds of service delay and 1.9 seconds of processing time, enhancing efficiency by nearly 30%.
The effective management of medical records is essential in the ordinary and emergency operations of healthcare providers. This work uses blockchain to develop a smart contract algorithm for users of a medical record platform. This algorithm provides immutable execution and addresses authentication and reliability issues to control access to healthcare platforms. An executable distributed code is used to build the smart contract algorithm. In the proposed algorithm, management operations of the clinical history are carried out and integrated in an automated way in a distributed environment. Solidity is the programming language used to create the algorithm for a private and permissioned architecture with a proposed consensus algorithm requiring significantly less computational power using a 22% faster hash function.
Machine learning, particularly using neural networks, is now widely adopted in practice even with the IoT paradigm; however, training neural networks at the edge, on IoT devices, remains elusive, mainly due to computational requirements. Furthermore, effective training requires large quantities of data and privacy concerns restrict accessible data. Therefore, in this paper, we propose a method leveraging a blockchain and federated learning to train neural networks at the edge effectively bypassing these issues and providing additional benefits such as distributing training across multiple devices. Federated learning trains networks without storing any data and aggregates multiple networks, trained on unique data, forming a global network via a centralized server. By leveraging the decentralized nature of a blockchain, this centralized server is replaced by a P2P network, removing the need for a trusted centralized server and enabling the learning process to be distributed across participating devices. Our results show that networks trained in such a manner have negligible differences in accuracy compared to traditionally trained networks on IoT devices and are less prone to overfitting. We conclude that not only is this a viable alternative to traditional paradigms but is an improvement that contains a wealth of benefits in an ecosystem such as a hospital.
The privacy and security of patients' health records have been an ongoing issue, and researchers are in a race against technology to design a system that can help stop the compromising of patient data. Many researchers have proposed solutions; however, most solutions have not incorporated potential parameters that can ensure private and secure personal health records management, which is the focus of this study. To design and develop a solution, this research thoroughly investigated existing solutions and identified potential key contexts. These include IOTA Tangle, Distributed Ledger Technology (DLT), IPFS protocols, Application Programming Interface (API), Proxy Re-encryption (PRE), and access control, which are analysed and integrated to secure patient medical records, and Internet of Things (IoT) medical devices, to develop a patient-based access management system that gives patients full control of their health records. This research developed four prototype applications to demonstrate the proposed solution: the web appointment application, the patient application, the doctor application, and the remote medical IoT device application. The results indicate that the proposed framework can improve healthcare services by providing immutable, secure, scalable, trusted, self-managed, and traceable patient health records while giving patients full control of their own medical records.
Ian Scott, Miguel de Castro Neto, Flávio L. Pinheiro
The majority of countries are currently struggling with unsustainable levels of waste production and low levels of recycling, particularly relating to household waste, and this area is in urgent need of new solutions. In general, the waste management sector has struggled with low consumer trust, fraud, manipulation, significant manual processes, and low levels of information and control. Recent events relating to the COVID-19 pandemic have highlighted, in particular, the role of trust in effective public policy making and consumer behavioural change. Here we propose a hybrid blockchain solution called a Polkadot parachain. Polkadot is a blockchain technology that connects a network of blockchains, each called a parachain, that can be customised to the business needs of a given application. This solution provides the cost benefits, scalability, and control of a permissioned or private blockchain while providing the security, verifiability, and trust of a public blockchain. The solution is developed with a design science approach and combines three typically separate blockchain use cases: supply chain tracking, incentivisation through a payment system, and gamification to achieve a complete solution for waste management. We provide a detailed discussion on the design of this blockchain solution with the use of blockchain functionality assessed against the criteria and development approaches found in the literature. Finally, we demonstrate how such a blockchain can be implemented with the Substrate blockchain development framework.
The traditional medical information systems are plagued by issues such as data breaches, lack of privacy, and data integrity concerns. This paper presents the design and evaluation of an IOTA-based medical information system aimed at addressing these challenges. In recent years, blockchain technology has emerged as a powerful tool for securing and managing data in a decentralized manner. One area where this technology has the potential to revolutionize the way we do things is in e-medicine. E-medicine, or electronic medicine, refers to the use of technology to deliver healthcare services remotely. This includes telemedicine, online consultations, and remote monitoring of patients' health status. IOTA blockchain technology, in particular, has a lot of potential in e-medicine. IOTA is a distributed ledger technology that uses a directed acyclic graph (DAG) instead of a traditional blockchain. The main ad-vantage of this approach is that it eliminates the need for miners and makes the system more scalable, fast, and energy-efficient. IOTA is also designed to be feeless, making it an ideal choice for microtransactions. In e-medicine, IOTA can be used in several ways. One potential use case is for secure and decentralized storage of patients' medical records. Medical records are highly sensitive and contain confidential information that needs to be protected from unauthorized access. By using IOTA's tamper-proof and immutable ledger, patients can have more control over their medical records and choose who has access to them. This can be especially useful in situations where patients need to share their medical records with multiple healthcare providers or research institutions. By leveraging the unique features of IOTA, such as its feeless microtransactions, scalability, and distributed ledger technology, the proposed system enhances security, privacy, and interoperability in healthcare information management. The evaluation of the system involves performance tests, and a comparison with existing solutions.
The Industrial Internet of Things (IIoT) holds significant potential for improving efficiency, quality, and flexibility. In decentralized systems, there are no trust-based centralized authentication techniques, which are unsuitable for distributed networks or subnets, as they have a single point of failure. However, in a decentralized system, more emphasis is needed on trust management, which presents significant challenges in ensuring security and trust in industrial devices and applications. To address these issues, industrial blockchain has the potential to make use of trustless and transparent technologies for devices, applications, and systems. By using a distributed ledger, blockchains can track devices and their data exchanges, improving relationships between trading partners, and proving the supply chain. In this paper, we propose a model for cross-domain authentication between the blockchain-based infrastructure and industrial centralized networks outside the blockchain to ensure secure communication in industrial environments. Our model enables cross authentication for different sub-networks with different protocols or authentication methods while maintaining the transparency provided by the blockchain. The core concept is to build a bridge of trust that enables secure communication between different domains in the IIoT ecosystem. Our proposed model enables devices and applications in different domains to establish secure and trusted communication channels through the use of blockchain technology, providing an efficient and secure way to exchange data within the IIoT ecosystem. Our study presents a decentralized cross-domain authentication mechanism for field devices, which includes enhancements to the standard authentication system. To validate the feasibility of our approach, we developed a prototype and assessed its performance in a real-world industrial scenario. By improving the security and efficiency in industrial settings, this mechanism has the potential to inspire this important area.
With the arrival of the 5G era, the Internet of Things (IoT) has entered a new stage, and the amount of IoT data is growing rapidly. The traditional blockchain cannot handle massive amounts of data, which presents scalability challenges for blockchain technology. Existing blockchain improvement technologies such as off-chain payments, protocol improvements, and sharding techniques have performance bottlenecks and limitations in the data, which is rapidly growing. The blockchain is fundamentally a decentralized distributed ledger, and the traditional chain structure is inadequate for addressing concerns such as forks, double-spending attacks, and other factors in the current IoT landscape. In this paper, we propose a high-throughput distributed ledger based on Directed Acyclic Graph (DAG) named TEEDAG. We design a consensus algorithm based on self-referencing parallel chains combined with Trusted Execution Environment (TEE) to ensure the security of the consensus process. The experiment proves that TEEDAG demonstrates a significantly higher throughput compared to traditional blockchain solutions and offers improved security and efficiency compared to existing DAG-based distributed ledger solutions.
Maytham S. Jabor, Aqeel Salman Azez, J.C. Campelo, Alberto Bonastre
Nowadays, Wireless Sensor Networks (WSNs) are widely used for collecting, communicating, and sharing information in various applications. Due to its limited resources in terms of computation, power, battery lifetime, and memory storage for sensor nodes, it is difficult to add confidentiality and integrity security features. It is worth noting that blockchain (BC) technology is one of the most promising technologies, because it provides security, avoids centralization, and a trusted third party. However, to apply BCs in WSNs is not an easy task because BC is typically resource-hungry for energy, computation, and memory. In this paper, the additional complication of adding BC in WSNs is compensated by an energy minimization strategy, which basically depends on minimizing the processing load of generating the blockchain hash value, and encrypting and compressing the data that travel from the cluster-heads to the base station to reduce the overall traffic, leading to reduced energy per node. A specific (dedicated) circuit is designed to implement the compression technique, generate the blockchain hash values and data encryption. The compression algorithm is based on chaotic theory. A comparison of the power consumed by a WSN using a blockchain implementation with and without the dedicated circuit, illustrates that the hardware design contributes considerably to reduce the consumption of power. When simulating both approaches, the energy consumed when replacing functions by hardware decreases up to 63%.
Muhammad Umer, Saima Sadiq, Reemah Alhebshi, Maha Farouk S. Sabir · 9 authors
For the past few years, the concept of the smart house has gained popularity. The major challenges concerning a smart home include data security, privacy issues, authentication, secure identification, and automated decision-making of Internet of Things (IoT) devices. Currently, existing home automation systems address either of these challenges, however, home automation that also involves automated decision-making systems and systematic features apart from being reliable and safe is an absolute necessity. The current study proposes a deep learning-driven smart home system that integrates a Convolutional neural network (CNN) for automated decision-making such as classifying the device as "ON" and "OFF" based on its utilization at home. Additionally, to provide a decentralized, secure, and reliable mechanism to assure the authentication and identification of the IoT devices we integrated the emerging blockchain technology into this study. The proposed system is fundamentally comprised of a variety of sensors, a 5 V relay circuit, and Raspberry Pi which operates as a server and maintains the database of each device being used. Moreover, an android application is developed which communicates with the Raspberry Pi interface using the Apache server and HTTP web interface. The practicality of the proposed system for home automation is tested and evaluated in the lab and in real-time to ensure its efficacy. The current study also assures that the technology and hardware utilized in the proposed smart house system are inexpensive, widely available, and scalable. Furthermore, the need for a more comprehensive security and privacy model to be incorporated into the design phase of smart homes is highlighted by a discussion of the risks analysis' implications including cyber threats, hardware security, and cyber attacks. The experimental results emphasize the significance of the proposed system and validate its usability in the real world.
Gislainy Crisostomo Velasco, Noelí Antonia Pimentel Vaz, Sérgio T. Carvalho
The development of smart contracts presents significant challenges compared to traditional software development, such as the immutability of the blockchain. This paper presents a systematic literature review (SLR) that aims to understand the limitations and challenges faced by smart contract developers on the Ethereum Virtual Machine (EVM). Among the main challenges identified are language restrictions, infrastructure limitations, and the lack of sufficient information on interface patterns and implementation specifications. Existing proposals are difficult to understand, with complex formal verifications that require advanced technical knowledge. Additionally, the scarcity of accessible educational resources for training new smart contract developers represents a major challenge to be overcome. In this regard, the SLR seeks to identify opportunities for improvement and innovation in the field, as well as validation and evaluation strategies to make the smart contract development process more efficient and secure.
In recent years, there have been many attempts to introduce blockchain-based identity management solutions, which allow the user to take over control of his/her own identity. In this paper, the authors have reviewed in-depth existing blockchain-based identity management papers and patents published online. Based on that analysis of the literature, a system will be implemented which will come up with the current issues and try to minimize them. Being transparent, immutable, and decentralized in nature, blockchain mechanism is found to be a better technology which can reduce the corruption in the experimental scenario. The objective is to develop a decentralized system which can be used for the verification of the employees in an organization. This is done to stop or reduce the cases of identity theft and data leakage in recent time. This system will be using Ethereum blockchain platform for monitoring the information and smart contract for authentication.
Blockchain is becoming increasingly popular in the business and academic communities because it can provide security for a wide range of applications. Therefore, researchers have been motivated to exploit blockchain characteristics, such as data immutability, transparency, and resistance to single-point failures in the Internet of Things (IoT), to increase the security of the IoT ecosystem. However, many existing blockchains rely on classical cryptosystems such as the Elliptic Curve Digital Signature Algorithm (ECDSA) and SHA-256 to validate transactions, which will be compromised by Shor and Grover’s algorithms running on quantum computers in the foreseeable future. Post-Quantum Cryptosystems (PQC) are an innovative solution for resisting quantum attacks that can be applied to blockchains, resulting in the creation of a new type of blockchain known as Post-Quantum Blockchains (PQB). In this survey, we will look at the different types of PQC and their recent standard primitives to determine whether they can enable security for blockchain-based IoT applications. It also briefly introduces blockchain and outlines recent blockchain-IoT application proposals. To the best of our knowledge, this is the first study to examine how post-quantum blockchains are being developed and how they can be used to create security mechanisms for different IoT applications. Finally, this study explores the main challenges and potential research directions that arise from integrating quantum-resistance blockchains into IoT ecosystems.
Access control data will continue to be exposed to the threat of privacy leakage even if blockchain technology currently offers a new solution for the security and privacy of the internet of things (IoT). However, its usability and privacy are not completely leveraged. This paper first discusses the IoT and blockchain technology and then examines each technology's structural models in order to address the issue of information security and privacy protection for the global organization IoT based on blockchain. Second, the information security and privacy guarantee system based on blockchain is built with ZKP and TEE at its heart after problems with zero-knowledge proof (ZKP) and trusted execution environment (TEE) in information security guarantee based on blockchain are investigated. By comparing the simulation trials, the proposed system's viability is finally confirmed. The results demonstrate that the suggested algorithm's evidence generation time is 352 ms when it reaches the experiment's highest node 28, which is clearly faster than previous techniques.
The problem of resource-saving scheduling in a fog environment is considered in this paper. The objective function of the problem in question presupposes the fog nodes’ reliability function maximizing. Therefore, to create a schedule, the following is required: the history of the fog devices’ state changes and the search space, which consists of preselected nodes of the cloud-fog broker neighbourhood. The obvious approach to providing the scheduler with this information is to poll the fog nodes, yet this can consume the unacceptable time because of the QoS requirements. In this paper, the system architecture and general methods for efficient resource-saving scheduling is presented. The system is based on distributed ledger element usage, which provides the nodes with the proper awareness about the surroundings. The usage of the distributed ledger allows not only for the creation of the resource-saving schedule but also the reduction of the scheduling problem-solving time, which frees addition time that can be used for the solving of user tasks. The latter also affects the overall resource-saving via reliability. The novelty of this paper consists in the development of the hybrid ledger-based system, which integrates and arranges the elements of various ledger types to solve the newly formulated problem.
Muhammad Zalkifal Khan, Maham Nadeem, Mohammad Kaleem, Sajid Nazir
Blockchain technology is poised to transform the data storage and data interchange models. A blockchain is a distributed ledger of transactions stored across a network of nodes. This decentralized model provides immutability and traceability of the records and is known as Distributed Ledger Technology (DLT). In the implemented healthcare system, we used a decentralized blockchain based peer to peer architecture ensuring data security, availability, and reliability. We leverage the Substrate framework, part of Polkadot ecosystem for building blockchains. Once the patient logs into their profile, they are able to view their medical history along with any doctor’s prescriptions and laboratory reports. When the doctor accesses a patient’s profile, they can make new entries to the medical records and prescriptions. In addition, we show that a tamper-proof record of the healthcare assets can be securely maintained, and accessible to the authorized entities.
The Internet of Medical Things (IoMT) is a network of healthcare devices such as wearables, diagnostic equipment, and implantable devices, which are linked to the internet and can communicate with one another. Blockchain (BC) technology can design a secure, decentralized system to store and share medical data in an IoMT-based intelligent healthcare system. Patient records were stored in a tamper-proof and decentralized way using BC, which provides high privacy and security for the patients. Furthermore, BC enables efficient and secure sharing of healthcare data between patients and health professionals, enhancing healthcare quality. Therefore, in this paper, we develop an IoMT with a blockchain-based smart healthcare system using encryption with an optimal deep learning (BSHS-EODL) model. The presented BSHS-EODL method allows BC-assisted secured image transmission and diagnoses models for the IoMT environment. The proposed method includes data classification, data collection, and image encryption. Initially, the IoMT devices enable data collection processes, and the gathered images are stored in BC for security. Then, image encryption is applied for data encryption, and its key generation method can be performed via the dingo optimization algorithm (DOA). Finally, the BSHS-EODL technique performs disease diagnosis comprising SqueezeNet, Bayesian optimization (BO) based parameter tuning, and voting extreme learning machine (VELM). A comprehensive set of simulation analyses on medical datasets highlights the betterment of the BSHS-EODL method over existing techniques with a maximum accuracy of 98.51%, whereas the existing methods such as DBN, YOLO-GC, ResNet, VGG-19, and CDNN models have lower accuracies of 94.15%, 94.24%, 96.19%, 91.19%, and 95.29% respectively.
<title>Abstract</title> Blockchain Technology has grown exponentially in recent years due to its decentralized, immutable, transparent data storage, transaction sharing, and processing. With the emergence of different blockchain platforms, it is substantial to analyze and evaluate the performance of these platforms in various scenarios. The popularity of the public blockchain, i.e., Bitcoin and Ethereum, has increased manifold. But in distinction to a public blockchain, there is a permissioned and private blockchain that allows restricted involvement of users in the network. To make a well-informed decision regarding the selection of an appropriate platform for utilization, it is crucial to evaluate diverse performance metrics among the numerous available blockchain platforms. In this study, we conducted an assessment of the performance of the Hyperledger Fabric blockchain (HLF), taking into account various metrics such as resource consumption, throughput, success rate, and latency. We have incorporated parameters such as the ordering service, programming language to write chaincode/smart contracts, number of transactions, transactions per second, and organizations to evaluate the system’s performance. Along with our analysis, we also suggested potential areas of research for the future development of blockchain technology.
Blockchain oracles are an intermediary designed to connect external non-deterministic information and real-world data to the blockchain digital infrastructure. The variety of proposed solutions and purposes are of great variety and suggest that it is necessary to take into account different features of the process and specifically define the required functionalities. The purpose of this paper is to present the integration of oracles into an EOSIO blockchain-based platform for smart crop production data exchange by smart contracts. The functions of two oracles are presented. Their integration is described at the design level and at the implementation of the smart contracts. The design level is illustrated by workflow diagrams of internal processes between oracle applications and the blockchain smart contract and by external processes in the oracles’ smart contracts. The implementation level is illustrated by oracle application configuration files and elements of C++ smart contracts, such as constant and variable declarations, multi-index tables, internal contract functions, and actions called by other contracts and external programs. As results of the oracles’ operation, a report on the detected emergency failures and an estimate of the cost of ram resource are presented.
Rayan A. Alsemmeari, Mohamed Yehia Dahab, Abdulaziz A. Alsulami, Badraddin Alturki · 5 authors
The growth of the Internet of Things (IoT) devices in the healthcare sector enables the new era of the Internet of Medical Things (IoMT). However, IoT devices are susceptible to various cybersecurity attacks and threats, which lead to negative consequences. Cyberattacks can damage not just the IoMT devices in use but also human life. Currently, several security solutions have been proposed to enhance the security of the IoMT, employing machine learning (ML) and blockchain. ML can be used to develop detection and classification methods to identify cyberattacks targeting IoMT devices in the healthcare sector. Furthermore, blockchain technology enables a decentralized approach to the healthcare system, eliminating some disadvantages of a centralized system, such as a single point of failure. This paper proposes a resilient security framework integrating a Tri-layered Neural Network (TNN) and blockchain technology in the healthcare domain. The TNN detects malicious data measured by medical sensors to find fraudulent data. As a result, cyberattacks are detected and discarded from the IoMT system before data is processed at the fog layer. Additionally, a blockchain network is used in the fog layer to ensure that the data is not altered, enhancing the integrity and privacy of the medical data. The experimental results show that the TNN and blockchain models produce the expected result. Furthermore, the accuracy of the TNN model reached 99.99% based on the F1-score accuracy metric.