Jiejun Hu, Martin J. Reed, Nikolaos Thomos, Mays Al-Naday · 5 authors
With the increasing demand for digitalization and participation in Industry 4.0, new challenges have emerged concerning the market of digital services to compensate for the lack of processing, computation, and other resources within Industrial Internet of Things (IIoTs). At the same time, the complexity of interplay among stakeholders has grown in size, granularity, and variation of trust. In this paper, we consider an IIoT resource market with heterogeneous buyers such as manufacturer owners. The buyers interact with the resource supplier dynamically with specific resource demands. This work introduces a broker between the supplier and the buyers, equipped with Distributed Ledger Technologies (DLT) providing a service for market security and trustworthiness. We first model the DLT-assisted IIoT market analytically to determine an offline solution and understand the selfish interactions among different entities (buyers, supplier, broker). Considering the non-cooperative heterogeneous buyers in the dynamic market, we then follow an independent learners framework to determine an online solution. In particular, the decision-making procedures of buyers are modeled as a Partially Observable Markov Decision Process which is solved using independent Q-learning. We evaluate both the offline and online solutions with analytical simulations, and the results show that the proposed approaches successfully maximize players’ satisfaction. The results further demonstrate that independent Q-learners achieve equilibrium in a dynamic market even without the availability of complete information and communication, and reach a better solution compared to that of centralized Q-learning.
The Internet of Objects (IoT) could be a new paradigm for the linked, data-exchanging nature of things and their parts through a network supported by nodes. IoT has risen to the forefront of emerging technologies in a very type of applications, including peer-to-peer networks, smart energy grids, home and building automation, vehicle-to-vehicle communication, and wearable computing devices, because of the widespread use of small devices and embedded sensor frameworks. thanks to its tremendous expansion and widespread use, it's posed security issues that may prevent it from getting used during a style of new applications. The growing number of networked gadgets creates several access points for attackers, also as security issues. due to the fragile nature of IoT applications including health, automation, and energy grids, security concerns can't be tolerated. DLT (Distributed Ledger Technology) is one such technology which will help to mitigate IoT security threats. The vulnerability of a central node, which can compromise the whole system, are often reduced by adopting a distributed ledger to eliminate the necessity for one node. Blockchain, a distributed ledger technology, has sparked plenty of interest and generated real-world value. Here we construct a distributed multi ledger construction algorithm for peer-to-peer data transaction which involves key generation for each transaction.
Prabhat Kumar, Randhir Kumar, Abhinav Kumar, A. Antony Franklin · 6 authors
The rapid expansion of the Industrial Internet of Things (IIoT) necessitates the digitization of industrial processes in order to increase network efficiency. The integration of Digital Twin (DT) with IIoT digitizes physical objects into virtual representations to improve data analytics performance. Nevertheless, DT empowered IIoT generates a massive amount of data that is mostly sent to the cloud or edge servers for real-time analysis. However, unreliable public communication channels and lack of trust among participating entities causes various types of threats and attacks on the ongoing communication. Motivated from the aforementioned discussion, we present a blockchain and Deep Learning (DL) integrated framework for delivering decentralized data processing and learning in IIoT network. The framework first present a new DT model that facilitates construction of a virtual environment to simulate and replicate security-critical processes of IIoT. Second, we propose a blockchain-based data transmission scheme that uses smart contracts to ensure integrity and authenticity of data. Finally, the DL scheme is designed to apply the Intrusion Detection System (IDS) against valid data retrieved from blockchain. In DL scheme, a Long Short Term Memory-Sparse AutoEncoder (LSTMSAE) technique is proposed to learn the spatial-temporal representation. The extracted characteristics are further used by the proposed Multi-Head Self-Attention (MHSA)-based Bidirectional Gated Recurrent Unit (BiGRU) algorithm to learn long-distance features and accurately detect attacks. The practical implementation of our proposed framework proves considerable enhancement of communication security and data privacy in DT empowered IIoT network.
The Internet of Things is gaining more importance in the present era of Internet technology. It is considered as one of the most important technologies of everyday life. Moreover, IoT systems are ceaselessly growing with more and more devices. They are scalable, dynamic, and distributed, hence the origin of the crucial security requirements in IoT. One of the most challenging issues that the IoT community must handle recently is how to ensure an access control approach that manages the security requirements of such a system. Traditional access control technologies are not suitable for a large-scale and distributed network structure. Most of them are based on a centralized approach, where the use of a trusted third party (TTP) is obligatory. Furthermore, the emergence of blockchain technology has allowed researchers to come up with a solution for these security issues. This technology is highly used to record access control data. Additionally, it has great potential for managing access control requests. This paper proposed a blockchain-based access control taxonomy according to the access control nature: partially decentralized and fully decentralized. Furthermore, it presents an overview of blockchain-based access control solutions proposed in different IoT applications. Finally, the article analyzes the proposed works according to certain criteria that the authors deem important.
Mohammed Shuaib, Sumit Badotra, Muhammad Irfan Khalid, Abeer D. Algarni · 9 authors
Cryptography and associated technologies have existed for a long time. This field is advancing at a remarkable speed. Since the inception of its initial application, blockchain has come a long way. Bitcoin is a cryptocurrency based on blockchain, also known as distributed ledger technology (DLT). The most well-known cryptocurrency for everyday use is Bitcoin, which debuted in 2008. Its success ushered in a digital revolution, and it currently provides security, decentralization, and a reliable data transport and storage mechanism to various industries and companies. Governments and developing enterprises seeking a competitive edge have expressed interest in Bitcoin and other cryptocurrencies due to the rapid growth of this recent technology. For computer experts and individuals looking for a method to supplement their income, cryptocurrency mining has become a big source of anxiety. Mining is a way of resolving mathematical problems based on the processing capacity and speed of the computers employed to solve them in return for the digital currency incentives. Herein, we have illustrated benefits of utilizing GPUs (graphical processing units) for cryptocurrency mining and compare two methods, namely overclocking and undervolting, which are the superior techniques when it comes to GPU optimization. The techniques we have used in this paper will not only help the miners to gain profits while mining cryptocurrency but also solve a major flaw; in order to mitigate the energy and resources that are consumed by the mining hardware, we have designed the mining hardware to simultaneously run longer and consume much less electricity. We have also compared our techniques with other popular techniques that are already in existence with respect to GPU mining.
Open access
Blockchain Technology Applications and Security
IoT and Edge/Fog Computing
Advanced Steganography and Watermarking Techniques
In traditional Internet of Things (IoT) ecosystems, fog devices transmit data from sensors to a centralized cloud server. Issues with security and upkeep while updating firmware for millions of smart devices, single points of failure, as well as third-party Cloud server administration, the difficulty of frequently updating the firmware on millions of smart devices presents security and maintenance issues as well as a bottleneck in information flows, all raise privacy concerns. Blockchain technology eliminates the need for trusted third parties while also preventing single points of failure and other issues. As a result, academics are looking into the usage of blockchain in the IoT space. The most recent state-of-the-art developments in blockchain for IoT, blockchain for Cloud, blockchain for eHealth, smart cities, transportation, and other programmes are examined in this article.
Blockchain is a modern technology that has revolutionized the way society interacts and trades. It could be defined as a chain of blocks that stores information with digital signatures in a distributed and decentralized network. This technique was first adopted for the creation of digital cryptocurrencies, such as Bitcoin and Ethereum. However, research and industrial studies have recently focused on the opportunities that blockchain provides in various other application domains to take advantage of the main features of this technology, such as: decentralization, persistency, anonymity, and auditability. This paper reviews the use of blockchain in several interesting fields, namely: finance, healthcare, information systems, wireless networks, Internet of Things, smart grids, governmental services, and military/defense. In addition, our paper identifies the challenges to overcome, to guarantee better use of this technology.
Open access
Blockchain Technology Applications and Security
IoT and Edge/Fog Computing
Advanced Steganography and Watermarking Techniques
Kawther A. Al‐Dhlan, Hamad A. Alreshidi, Shahbaz Pervez, Zahida Paraveen · 8 authors
The adoption of blockchain technology can provide data asset management’s high security, privacy, and traceability. After a comprehensive investigation of the present blockchain-based data asset management mechanism, it was determined that it is only relevant to a portion of the blockchain system design. To address this issue, a new model of data asset management based on blockchain technology is being developed, which incorporates applications at all levels of the blockchain system. This model implements a network layer node authority control mechanism, a consensus layer consensus mechanism with customizable attributes, improved data query efficiency at the data layer by optimizing the structure and building indexes, intelligent data management, and smart contract layer management. Furthermore, at the transaction layer, sharing information encryption using customizable encryption algorithms is introduced. The experimental results reveal that, when compared to the traditional paradigm, the new blockchain-based data asset management strategy enhances the efficiency of on-chain data queries by 2.33 times.
Over the last couple of years, Blockchain technology has emerged as a game-changer for various industry domains, ranging from FinTech and the supply chain to healthcare and education, thereby enabling them to meet the competitive market demands and end-user requirements. Blockchain technology gained its popularity after the massive success of Bitcoin, of which it constitutes the backbone technology. While blockchain is still emerging and finding its foothold across domains, Cloud computing is comparatively well defined and established. Organizations such as Amazon, IBM, Google, and Microsoft have extensively invested in Cloud and continue to provide a plethora of related services to a wide range of customers. The pay-per-use policy and easy access to resources are some of the biggest advantages of Cloud, but it continues to face challenges like data security, compliance, interoperability, and data management. In this article, we present the advantages of integrating Cloud and blockchain technology along with applications of Blockchain-as-a-Service. The article presents itself with a detailed survey illustrating recent works combining the amalgamation of both technologies. The survey also talks about blockchain-cloud services being offered by existing Cloud Service providers.
Directed Acyclic Graph (DAG) is a popular approach to achieve scalability of blockchain networks. Due to its high efficiency in data communication and great scalability, DAG has been widely adopted in many applications such as Internet of Things (IoT) and Decentralized Finance (DeFi). DAG-based blockchain, nevertheless, faces the key challenge of transaction inclusion collision due to the high concurrency and the network delay. Particularly, the transaction inclusion collision in DAG-based blockchain leads to the revenue and throughput dilemmas, which would greatly degrade the system performance. In this paper, we propose "TIPS", the Transaction Inclusion Protocol with Signaling, which broadcasts a signal indicating the transactions in the block. We show that with the prompt broadcast of a signal, TIPS substantially reduces the transaction collision and thus resolves these dilemmas. Moreover, we show that TIPS can defend against both the denial-of-service and the delay-of-service attacks. We also conduct intensive experiments to demonstrate the superior performance of the proposed protocol.
Usman Khalil, Owais Ahmed Malik, Mueen Uddin, Chin‐Ling Chen
Smart devices have become an essential part of the architectures such as the Internet of Things (IoT), Cyber-Physical Systems (CPSs), and Internet of Everything (IoE). In contrast, these architectures constitute a system to realize the concept of smart cities and, ultimately, a smart planet. The adoption of these smart devices expands to different cyber-physical systems in smart city architecture, i.e., smart houses, smart healthcare, smart transportation, smart grid, smart agriculture, etc. The edge of the network connects these smart devices (sensors, aggregators, and actuators) that can operate in the physical environment and collects the data, which is further used to make an informed decision through actuation. Here, the security of these devices is immensely important, specifically from an authentication standpoint, as in the case of unauthenticated/malicious assets, the whole infrastructure would be at stake. We provide an updated review of authentication mechanisms by categorizing centralized and distributed architectures. We discuss the security issues regarding the authentication of these IoT-enabled smart devices. We evaluate and analyze the study of the proposed literature schemes that pose authentication challenges in terms of computational costs, communication overheads, and models applied to attain robustness. Hence, lightweight solutions in managing, maintaining, processing, and storing authentication data of IoT-enabled assets are an urgent need. From an integration perspective, cloud computing has provided strong support. In contrast, decentralized ledger technology, i.e., blockchain, light-weight cryptosystems, and Artificial Intelligence (AI)-based solutions, are the areas with much more to explore. Finally, we discuss the future research challenges, which will eventually help address the ambiguities for improvement.
By the development and advancement of blockchain technique, Internet of Things (IoT) proliferation driven devices and the application of blockchain-enabled IoT alter the view and operating infrastructure of the smart networks. The blockchain is responsible for supporting decentralized systems and offers secured means of authentication, management, and access to IoT system thereby deploying smart contracts offered by Ethereum. The increasing demand and the blockchain expansion generate huge volume of sensitive data. The growing demand and expansion of blockchain-IoT systems is generating large volume of sensitive data. Furthermore, distributed denial-of-service (DDoS) attacks are regarded as the most promising threats for smart contracts in the blockchain-based systems. Therefore, there is a need to detect and classify the attack type and the data should be stored in server more securely with the use of blockchain and data aggregation method. For this purpose, this presented technique aims at introducing decentralized consensus blockchain and Interplanetary file system (IPFS) based data aggregation for effective classification and data storage. The attack is detected using meta-hyperparameter random forest (MHP-RF) classifier. Once the attack is detected, the transaction information is stored in server securely by means of smart contract-based blockchain system. The transaction handling stage classifies the transaction type as normal or abnormal one which then followed by execution of business logic by smart contract thereby appending the transaction of blockchain in the network cloud. The consensus blockchain technique is employed with the use of PoW-enabled scheme integrated with Elgamal-based data aggregation. Therefore, the system security is improved and the intrusion is prevented greatly. The performance analysis of the system is analyzed in terms of accuracy, precision, recall, F-score, Encryption time, decryption time, execution time, and space complexity. The attained outcomes are compared with traditional approaches to prove the effectiveness of proposed strategy. The proposed system is said to be effective in time consumption, classifier performance, and in overcoming space complexity issues.
Security is one of the primary issues in any wireless network deployment, because, wireless nodes are susceptible to a wide-variety of internal & external attacks. These include improper authentication & access control, distributed denial of service (DDoS), sybil, spoofing, spying, masquerading, etc. Securing networks against these attacks requires an immutable, transparent, traceable, and distributed computing security model, that has minimum overheads. Most of these characteristics are fulfilled via use of blockchains, which assist in low-complexity deployment of security & hashing models. But the delay needed to scale these blockchains increases exponentially w.r.t. chain length, due to which researchers split the main blockchain into multiple sidechains. A wide variety of models are proposed by researchers for sidechain formation, and most of them are consensus dependent, which limits the scalability. Moreover, energy needed to mine blocks for these sidechains depends directly on the consensus model, encryption model, hash rules, and length of the blockchain. Thus, models proposed for sidechain formation are context-specific, and have limited scalability performance when used for multiple blockchain types. To overcome these limitations, and maintain high security performance, this text proposes design of a Low-power hybrid Consensus Method for QoS-aware Sidechain-based IoT Networks via Augmented Bioinspired computing Models. This method uses a combination of Proof-of-Work (PoW), Proof-of-Stake (PoS) & Proof-of-Authority (PoA) based consensus models, which assists in reducing its mining delay. The PoW model allows selection of nodes with higher performance, PoS allows selection of nodes with higher stake, and PoA ensures better control of IoT devices. Selection of these consensus models is done via use of an Improved Genetic Algorithm (IGA) model, that evaluates the power needed for mining, and minimizes it using a rule-based method. This is combined with a sidechain creation model, that assists in improving QoS performance via dynamically splitting the main blockchain into performance-specific sidechains. These sidechains are categorized into low-power, low-delay, and high-throughput sidechains, which are formed via Elephant Herding Optimization (EHO) model. Due to combination of IGA for consensus selection, and EHO for sidechain creation, the proposed model is able to reduce energy needed for mining by 15.4% when compared with various state-of-the-art models. It is also able to improve mining speed by 5.3%, while maintaining high security performance under different IoT Network attacks. Due to this performance enhancement, the proposed model is capable of being deployed for a wide variety of low-delay healthcare IoT, high-throughput industrial IoT, and low energy home IoT application deployments.
A distributed ledger system blockchain proves to be worthy in the domain of healthcare due to its enormous applications and benefits. Peer-to-peer devolved transactions in an allocated way make the blockchain an efficient and modern tool to be utilized in healthcare as a solution to problems and challenges. The traditional healthcare system utilizes classical approaches to manage and maintain the EHR and cross-domain implementation. Therefore, a systematic investigation is necessary to find the current research trends, challenges, and solutions to implement blockchain to address the challenges. The motivation of this study is to pave the way for future research to find more problem-specific solutions by implementing blockchain to make the healthcare system more robust. The presented systematic survey provides the visualization and graphical representation of current methodologies, challenges, and future directions. The bibliometric analysis has been performed on the published studies in Scopus from 2017 to 2021. The publication published in the first three months of 2021 in the domain of healthcare using blockchain has also been reviewed to find the latest trends in the blockchain. The study covers multiple challenges in the presented systematic literature review, especially the interoperability of blockchain-based systems in the healthcare domain. The presented study results show the top trending research topics, top-ranked authors, and top institutes focusing on blockchain around the world. The proposed study provides a baseline for future challenges and solutions related to blockchain implementation in healthcare.
Abstract In the Industry 4.0 era, an inherited featured technology, blockchain, plays a vital role in knowledge engineering applications. Blockchain provides privacy to sensitive data as an intelligent agent, so its adoption rate increases in all the advanced domains. Especially in the health care department, blockchain technology usage helps avoid attacks like the Wannacry ransomware attack during 2017. Therefore, this paper described a decentralised application (DApp) expert system using public blockchain to create and maintain official health documents, especially medical certificates. Current existing systems, either paper‐based or database or clouds to save the medical certificates, have more scope to do attacks. Hence, proposed a blockchain‐based DApp that acts as an interface between intelligent agents, blockchains, and system related to the medical certificates. The main strength of this paper is implementation results, which are not among the maximum literary works currently available. The associate cost for conducting distributed application operations on the blockchain in terms of Gas comprehensively presented here. Furthermore, it consists of comparing the system's non‐functional functions by considering blockchain and non‐blockchain environments. Also, presented the simulation results with the performance results compared with the existed systems.
Emerging growth in technology has rapidly changed our homes and cities. Present homes and cities will be upgraded to smart homes and smart cities in the near future. Various solutions used to build the smart-city network demand a scalable and decentralized solution. This study proposes a blockchain-empowered decentralized and scalable solution for a sustainable smart-city network. The Internet of Things (IoT), fog nodes, permissioned trust chain, smart contract, blockchain, and InterPlanetary file system (IPFS) are deployed to construct a scalable and decentralized solution for a sustainable smart city. Three main public sector departments, i.e., electricity, water supply, and health care, are studied over the proposed solution. The proposed solution is implemented over constrained application protocol (CoAP) and Ethereum blockchain. The performance of the proposed model is evaluated for 1500 devices and over 10,000 records. A total 77.44% improvement is registered during performance evaluation over a scalable environment. The performance evaluation of each case study and collaborative performance evaluation concludes the improvised performance of the proposed solution for scalable and distributed applications. Better performance, scalability, and the distributed nature of the presented model make it suitable for the sustainable smart-city network.
Electric Vehicles (EVs), as well as the number of applications for their management, are rapidly increasing due to the fact that Internet of Vehicles (IoV) becomes more informative and industrialized. According to the literature, IoV requires decentralization towards the energy Demand Response (DR) management, with secure energy trading, efficient charging scheduling, and incentives for making the drivers to participate. Blockchain and Distributed Ledger Technologies (DLTs) can be used to enable a foundational environment to support DR management. However, and to the best of our knowledge, none of the existing research works discussed in the literature adopts a holistic approach to address them. As such there is a demand for exploring a unified blockchain-based framework for distributed DR management. Therefore, the aim of this work is focused on the blockchain adoption in IoV-assisted smart cities. More specifically, we propose a blockchain based approach, to be used for building a secure and user-centric DR management framework. Our proposition aims to address the DRP in IoV through charging scheduling based on the generation of EV driving profiles, and optimal Vehicle-to-Vehicle/Grid (V2V | V2G) energy trading.
Mohammad Hossein Tabatabaei, Roman Vitenberg, Narasimha Raghavan Veeraragavan
The explosive advent of the blockchain technology has led to hundreds of blockchain systems in the industry, thousands of academic papers published over the last few years, and an even larger number of new initiatives and projects. Despite the emerging consolidation efforts, the area remains highly turbulent without systematization, educational materials, or cross-system comparative analysis. In this paper, we provide a systematic and comprehensive study of four popular yet widely different blockchain systems: Bitcoin, Ethereum, Hyperledger Fabric, and IOTA. The study is presented as a cross-system comparison, which is organized by clearly identified aspects: definitions, roles of the participants, entities, and the characteristics and design of each of the commonly used layers in the cross-system blockchain architecture. Our exploration goes deeper compared to what is currently available in academic surveys and tutorials. For example, we provide the first extensive coverage of the storage layer in Ethereum and the most comprehensive explanation of the consensus protocol in IOTA. The exposition is due to the consolidation of fragmented information gathered from white and yellow papers, academic publications, blogs, developer documentation, communication with the developers, as well as additional analysis gleaned from the source code. We hope that this survey will help the readers gain in-depth understanding of the design principles behind blockchain systems and contribute towards systematization of the area.
Actual challenges with data in physical infrastructure include: 1) the adversity of its velocity based on access and retrieval, thus integration; 2) its value as its intrinsic quality; 3) its extensive volume with a limited variety in terms of systems; and finally, 4) its veracity, as data can be modified to obtain an economical advantage. Physical infrastructure design based on Agile project management and minimum viable products provides benefits against the traditional waterfall method. Agile supports an early return on investment that promotes circular reinvesting while making the product more adaptable to variable social-economical environments. However, Agile also presents inherent issues due to its iterative approach. Furthermore, project information requires an efficient record of the aims, requirements, and governance not only for the investors, owners, or users but also to keep evidence in future health & safety and other statutory compliance. In order to address these issues, this article presents a Validation and Verification (V&V) model for data marketplaces with a hierarchical process; each data V&V stage provides a layer of data abstraction, value-added services, and authenticity based on Artificial Intelligence (AI). In addition, this proposed solution applies Distributed Ledger Technology (DLT) for a decentralised approach where each user keeps and maintains the data within a ledger. The presented model is validated in real data marketplace applications: 1) live data for the Newcastle Urban Observatory Smart City Project, where data are collected from sensors embedded within the smart city via APIs; 2) static data for University College London (UCL)—Real Estate—PEARL Project, where different project users and stakeholders introduce data into a Project Information Model (PIM).
As the backbone of every blockchain application, the consensus protocol is impacted by numerous risks, namely resource requirements and energy consumption, which limit the usage of blockchain. Applications such as IoT/IIoT cannot use these high-cost consensus methods due to limited resources. Therefore, we introduce Delegated Proof of Accessibility (DPoAC), a new consensus technique that employs secret sharing, PoS with random selection, and an interplanetary file system (IPFS).DPoAC is decomposed into two stages. During the initial stage, a secret is generated by a randomly chosen super node and divided into n shares. These shares are encrypted and stored in different n nodes on the IPFS network. The nodes will compete to access these shareholders to reconstruct the secret. The winning node will be awarded block generation rights. PoS with random selection is used in the second stage to compute the appropriate hash value and construct a block with valid transactions. In this novel approach, a node with few computational resources and small stakes can still obtain block generation rights by providing access to secret shares and reconstructing the secret, making the system reasonably fair. We qualitatively analyze and compare our scheme based on performance parameters against existing mainstream consensus protocols in the context of IoT/IIoT networks.
The cloud storage is far away from us and it is not capable of handling huge bandwidth data due to network latency. The goal of the Fog computing is to decrease the data that needs to be transferred to the cloud for data processing and to increase the efficiency. Fog computing improves the QoS and also reduces network bandwidth. All machine learning algorithm performances are dependent on the quality of the training data. If the training data is inadequate or it is modified by attackers, then the machine learning algorithm will miss predict and may give invalid results. In order to avoid modification of training data, it is preferable to store it in Blockchain. Blockchain is a decentralized model and its data structure is practically difficult to forge, hence it has attracted both industry and research now-a-days. Proposed system uses Ethereum platform to implement Blockchain. Ethereum allows users to create and run decentralized applications (DApps) to make agreements and to conduct transactions directly with each other without any third party by making use of smart contracts. Blockchain is convenient to store only a small amount of data, hence alternative solution to store large amount of data, for example in healthcare, in Blockchain is possible with the help of IPFS (Interplanetary File System). In e-healthcare applications, Activity Recognition System (ARS) is the most significant undertaking in remote checking of patients experiencing physical medical issues for taking quick action. Hence this paper, especially concentrate on the overall framework of the e-healthcare ARS and implementation of Blockchain to store e-healthcare training data to avoid forging, ultimately which improves ARS results. Our implementation results also show that constant and less transaction fee required to store into Blockchain irrespective of size of training data with help of IPFS and also proved transaction throughput increases and network delay decreases with help of IPFS. HIGHLIGHTS All machine learning algorithm performances are dependent on the quality of the training data. If the training data is inadequate or it is modified by attackers, then the machine learning algorithm will miss predict and may give invalid results To avoid modification of training data, it is preferable to store it in Blockchain. Blockchain is a decentralized model, and its data structure is practically difficult to forge Proposed system uses Ethereum platform and IPFS to implement Blockchain using smart contracts for health care applications Our implementation results also show that constant and less transaction fee required to store into Blockchain irrespective of size of training data with help of IPFS, and proved transaction throughput increases and network delay decreases with help of IPFS GRAPHICAL ABSTRACT
The fifth generation (5G) wireless networks technologies support diverse vertical applications by connecting heterogeneous devices and machines, promising drastic improvements in terms of low latency, increased network capacity and enhanced system throughput. Despite all these advantages that 5G will bring about, there are still major challenges to be addressed, including decentralization, transparency, risks of data interoperability, and above all, network privacy and security vulnerabilities. On paper, Distributed Ledger Technologies provide a framework to effectively handle most challenges in 5G networks. The panel provides a forum to discuss recent developments in 5G services, focusing on the potential of key 5G technologies, including edge computing, Network Function Virtualization, Network Slicing, and M2M communications,