In this paper, a layered architecture incorporating Blockchain technology (BCT) and Machine Learning (ML) is proposed in the context of the Industrial Internet-of-Things (IIoT) for smart manufacturing applications. The proposed architecture is composed of five layers covering sensing, network/protocol, transport enforced with BCT components, application and advanced services (i.e., BCT data, ML and cloud) layers. BCT enables gathering sensor access control information, while ML brings its effectivity in attack detection such as DoS (Denial of Service), DDoS (Distributed Denial of Service), injection, man in the middle (MitM), brute force, cross-site scripting (XSS) and scanning attacks by employing classifiers differentiating between normal and malicious activity. The design of our architecture is compared to similar ones in the literature to point out potential benefits. Experiments, based on the IIoT dataset, have been conducted to evaluate our contribution, using four metrics: Accuracy, Precision, Sensitivity and Matthews Correlation Coefficient (MCC). Artificial Neural Network (ANN), Decision Tree (DT), Random Forest, Naive Bayes, AdaBoost and Support Vector Machine (SVM) classifiers are evaluated regarding these four metrics. Even if more experiments are required, it is illustrated that the proposed architecture can reduce significantly the number of DDoS, injection, brute force and XSS attacks and threats within an advanced framework for sensor access control in IIoT networks based on a smart contract along with ML classifiers.
Whereas the use of distributed ledger technologies has previously been limited to cryptocurrencies, other sectors—such as healthcare, supply chain, and finance—can now benefit from them because of bitcoin scripts and smart contracts. However, these applications rely on oracles to fetch data from the real world, which cannot reproduce the trustless environment provided by blockchain networks. Despite their crucial role, academic research on blockchain oracles is still in its infancy, with few contributions and a heterogeneous approach. This study undertakes a bibliometric analysis by highlighting institutions and authors that are actively contributing to the oracle literature. Investigating blockchain oracle research state of the art, research themes, research directions, and converging studies will also be highlighted to discuss, on the one hand, current advancements in the field and, on the other hand, areas that require more investigation. The results also show that although worldwide collaboration is still lacking, various authors and institutions have been working in similar directions.
Ihab L. Hussein Alsammak, Mohammed F. Alomari, Intedhar Shakir Nasir, Wasan H. Itwee
Recently, with the emergence and growth of the IoT as a promising vehicle for sustainable development, the concept of ‘smart cities’ has advanced significantly. However, many challenges inhibit the development of using IoT applications in smart cities, such as issues of privacy, scalability, trust, security, and centralisation. On a daily basis in smart cities, the IoT generates a large amount of data (big data) which could potentially be used for questionable or suspect purposes by attackers. The weight of the security issues surrounding big data must be acknowledged as the associated technology is continuously developing. To solve this issue, a strategy that secures important and potentially sensitive user information on a distributed blockchain and transmits non-sensitive information to the primary system by controlling the size of the blockchain is proposed. This solution cannot be achieved in traditional blockchain because it requires too many resources. The model is composed of three proposed algorithms: the first aims to allocate data to each user; the second performs the process of searching for data, and the third confirms the communication process. Experiments have proved that this proposed protocol for blockchain has excellent byzantine fault tolerance. The final experimental results of the proposed model established that the algorithms effectively meet the performance requirements.
Artificial intelligence (AI)-based studies have been carried out recently for the early detection of COVID-19. The goal is to prevent the spread of the disease and the number of fatal cases. In AI-based COVID-19 diagnostic studies, the integrity of the data is critical to obtain reliable results. In this paper, we propose a Blockchain-based framework called AIBLOCK, to offer the data integrity required for applications such as Industry 4.0, healthcare, and online banking. In addition, the proposed framework is integrated with Google Cloud Platform (GCP)-Cloud Functions, a serverless computing platform that automatically manages resources by offering dynamic scalability. The performance of five different machine learning models is evaluated and compared in terms of Accuracy, Precision, Recall, F-Score and Area under the curve (AUC). The experimental results show that decision trees gives the best results in terms of accuracy (98.4 %). Further, it has been identified that utilization of Blockchain technology can increase the load on memory.
In the Internet of Things (loT) era, edge computing is a promising paradigm to improve the quality of service for latency sensitive applications by filling gaps between the loT devices and the cloud infrastructure. Highly geo-distributed edge computing resources that are managed by independent and competing service providers pose new challenges in terms of resource allocation and effective resource sharing to achieve a globally efficient resource allocation. In this paper, we propose a novel blockchain-based model for allocating computing resources in an edge computing platform that allows service providers to establish resource sharing contracts with edge infrastructure providers apriori using smart contracts in Ethereum. The smart contract in the proposed model acts as the auctioneer and replaces the trusted third-party to handle the auction. The blockchain-based auctioning protocol increases the transparency of the auction-based resource allocation for the participating edge service and infrastructure providers. The design of sealed bids and bid revealing methods in the proposed protocol make it possible for the participating bidders to place their bids without revealing their true valuation of the goods. The truthful auction design and the utility-aware bidding strategies incorporated in the proposed model enables the edge service providers and edge infrastructure providers to maximize their utilities. We implement a prototype of the model on a real blockchain test bed and our extensive experiments demonstrate the effectiveness, scalability and performance efficiency of the proposed approach.
Centralization has dominated classic scientific, social, and economic developments. Decentralization has also received increasing attention in management, decision, governance, and economics, despite its incomparability in AI. Going beyond centralized and distributed AI, this article reviews and delineates the conceptual map, research issues, and technical opportunities of decentralized AI and edge intelligence. The complementarity and metasynthesis between centralized and decentralized AI are also elaborated. We further assess where decentralized AI and edge intelligence can enable and promote smart blockchain, Web3, metaverse and decentralized science disciplinarily, technically, practically, and more broadly.
In today's era, internet-connected things provide immense opportunities to the world for enhancing the quality of lives through better data processing and intelligent decision making. Since the last decade, IoT brought numerous changes in people's personal as well as professional lives. With the enhancement in quality of lives, IoT also comes up with challenges such as security and privacy of data and devices. Every day, the attacker generates new zero-day attacks for IoT devices and data, and it's important to detect and protect the IoT eco-system from this type of attacks. Numerous researchers have proposed security schemes and methods to protect the IoT eco-system through either cryptography way or learning technique based way. AI and ML learning techniques have got immense popularity in handling the IoT security challenges as they are automatic in nature and can outperform provided the sufficient quality and quantity of data. Moreover, the AI techniques, including ML, DL and FL helps in intelligent decision-making and can also generate knowledge through its learning techniques. AI needs data to process, and IoT supplies the necessary data to process. In this paper, we provide a state-of-the-art survey for IoT security solutions proposed based on learning techniques. We provide an in-depth review of available learning techniques to solve critical security challenges such as IoT authentication, access control, anomaly detection and malware analysis. At the end, we also highlighted various futuristic technologies that can invigorate IoT research and help in the design of full proof IoT eco-system.
As a result of the proliferation of digital and network technologies in all facets of modern society, including the healthcare systems, the widespread adoption of Electronic Healthcare Records (EHRs) has become the norm. At the same time, Blockchain has been widely accepted as a potent solution for addressing security issues in any untrusted, distributed, decentralized application and has thus seen a slew of works on Blockchain-enabled EHRs. However, most such prototypes ignore the performance aspects of proposed designs. In this paper, a prototype for a Blockchain-based EHR has been presented that employs smart contracts with Hyperledger Fabric 2.0, which also provides a unified performance analysis with Hyperledger Caliper 0.4.2. The additional contribution of this paper lies in the use of a multi-hosted testbed for the performance analysis in addition to far more realistic Gossip-based traffic scenario analysis with Tcpdump tools. Moreover, the prototype is tested for performance with superior transaction ordering schemes such as Kafka and RAFT, unlike other literature that mostly uses SOLO for the purpose, which accounts for superior fault tolerance. All of these additional unique features make the performance evaluation presented herein much more realistic and hence adds hugely to the credibility of the results obtained. The proposed framework within the multi-host instances continues to behave more successfully with high throughput, low latency, and low utilization of resources for opening, querying, and transferring transactions into a healthcare Blockchain network. The results obtained in various rounds of evaluation demonstrate the superiority of the proposed framework.
This work presents a Self Sovereign Identity based system proposal to show how Blockchain, Building Information Modeling, Internet of Thing devices, and Self Sovereign Identity concepts can support the process of building digitalization, guaranteeing the compliance standards and technical regulations. The proposal ensures eligibility, transparency and traceability of all information produced by stakeholders, or generated by IoT devices appropriately placed, during the entire life cycle of a building artifact. By exploiting the concepts of the Self Sovereign Identity, our proposal allows the identification of all involved stakeholders, the storage off-chain of all information, and that on-chain of the sole data necessary for the information notarization and certification, adopting multi-signature approval mechanisms where appropriate. In addition it allows the eligibility verification of the certificated information, providing also useful information for facility management. It is proposed as an innovative system and companies that adopt the Open Innovation paradigm might want to pursue it. The model proposal is designed exploiting the Veramo platform, hence the Ethereum Blockchain, and all the recommendations about Self Sovereign Identity systems given by the European Blockchain Partnership, and by the World Wide Web Consortium.
Yue Wang, Tingyu Che, Xiaohu Zhao, Tao Zhou · 6 authors
Due to the competitive relationship among different smart factories, equipment manufacturers cannot integrate the private information of all smart factories to train the intelligent manufacturing equipment fault prediction model and improve the accuracy of intelligent manufacturing equipment fault detection. The use of a low fault recognition rate model for smart factories will cause additional losses for them. In this work, we propose a blockchain-based privacy information security sharing scheme in Industrial Internet of Things (IIoT) to solve the sharing problem of private information in smart factories. Firstly, we abstract smart factories as edge nodes and build decentralized, distributed trusted blockchain networks based on Ethereum clients on simulated edge devices and propose an Intelligent Elliptic Curve Digital Signature Algorithm (IECDSA) to guarantee the ownership of shared information by edge nodes. Secondly, we propose the Reputation-based Delegated Proof of Stake (RDPoS) consensus algorithm to improve the security and reliability of the Delegated Proof of Stake (DPoS) consensus algorithm. Furthermore, we design and implement an incentive mechanism based on information attributes to increase the motivation of edge nodes to share information. Finally, the proposed solution is simulated. Through theoretical and simulation experiments, it is proved that the blockchain-based privacy information security sharing scheme in IIoT can improve the enthusiasm of edge nodes to share information on the premise of ensuring the security of information sharing.
Blockchain has recently been able to draw wider attention throughout the research community. Since its emergence, the world has seen the mind-blowing expansion of this new technology, which was initially developed as a pawn of digital currency more than a decade back. A self-administering ledger that ensures extensive data immutability over the peer-to-peer network has made it attractive for cybersecurity applications such as a sensor-enabled system called the Internet of things (IoT). Brand new challenges and questions now demand solutions as huge IoT devices are now online in a distributed fashion to ease our everyday lives. After being motivated by those challenges, the work here has figured out the issues and perspectives an IoT infrastructure can suffer because of the wrong choice of blockchain technology. Though it may look like a typical review, however, unlike that, this paper targets sorting out the specific security challenges of the blockchain-IoT eco-system through critical findings and applicable use-cases. Therefore, the contribution includes directing Blockchain architects, designers, and researchers in the broad domain to select the unblemished combinations of Blockchain-powered IoT applications. In addition, the paper promises to bring a deep insight into the state-of-the-art Blockchain platforms, namely Ethereum, Hyperledger, and IOTA, to exhibit the respective challenges, constraints, and prospects in terms of performance and scalability.
Most traditional agricultural traceability systems are centralized, which could result in the low reliability of traceability results, enterprise privacy data leakage vulnerabilities, and the generation of information islands. To solve the above problems, we propose a trusted agricultural product traceability system based on the Ethereum blockchain in this paper. We designed a dual storage model of "Blockchain+IPFS (InterPlanetary File System)" to reduce the storage pressure of the blockchain and realize efficient information queries. Additionally, we propose a data privacy protection solution based on some cryptographic primitives and the Merkle Tree that can avoid enterprise privacy and sensitive data leakage. Furthermore, we implemented the proposed system using the Ethereum blockchain platform and provided the cost, performance, and security analysis, as well as compared it with the existing solutions. The results showed that the proposed system is both efficient and feasible and can meet the practical application requirements.
Blockchain systems are challenged by the so-called Trilemma tradeoff: decentralization, scalability and security. Infrastructure and node configuration, choice of the Consensus Protocol and complexity of the application transactions are cited amongst the factors that affect the tradeoffs balance. Given that Blockchains are complex, dynamic dynamic systems, a dynamic approach to their management and reconfiguration at runtime is deemed necessary to reflect the changes in the state of the infrastructure and application. This paper introduces the utilisation of Digital Twins for this purpose. The novel contribution of the paper is design of a framework and conceptual architecture of a Digital Twin that can assist in maintaining the Trilemma tradeoffs of time critical systems. The proposed Digital Twin is illustrated via an innovative approach to dynamic selection of Consensus Protocols. Simulations results show that the proposed framework can effectively support the dynamic adaptation and management of the Blockchain
Single point of failure and node attack tend to cause instability in the centralized Internet of Things (IoT). Combined with blockchain technology, the deficiency of traditional IoT architecture can be effectively alleviated. However, the existing blockchain consensus mechanism still has the problems of forks and wasting of computing power. Therefore, this paper proposes a new framework based on a two-stage credit calculation to handle these problems. Notably, the nodes are selected through the model, and these nodes will compete on the chain according to the behavior of participating in the creation of the block. Then, a comparative simulation with the existing consensus mechanism proof of work (PoW) is presented. The results show that the proposed framework can quickly eliminate malicious nodes, maintain the overall security of the blockchain and reduce consensus delay.
In this era, the ultimate vision is to transform current technologies into intelligent global environments to facilitate everyday transactions. The emerging Industry 4.0 has introduced promising potential technologies that have expedited the transition of Internet of Things (IoT) into the Internet of Everything (IoE), utilizing the advances in artificial intelligence. Such a transition implies that sensitive data can be effortlessly accessed via the open network used by various domains such as military, business, transportation, medical, and education, leading to potential security concerns. Although a blockchain, along with the above fields, already employs a fast network such as 5G, the explosive growth in the development and implementation of various Industry 4.0-related domains requires significantly faster networking speeds and a secure mechanism for data transfer. This exhibits the need for 6G to meet the requirements of real-time applications, as shown in the graphical representation of the abstract. The bulk of this work was performed on a blockchain, but some methodology was needed that fulfilled security at different levels, such as the process level, data level, and infrastructure level. Our contribution in this work was twofold: first, at the process level, a novel smart contract mechanism was described; and second, at the data level, a digital signature methodology was employed that allowed anonymization to authenticate and secure the blockchain without encryption.
Miguel Pincheira, Massimo Vecchio, Raffaele Giaffreda
An increasing amount of research focuses on integrating the Internet of Things and blockchain technology to address the requirements of traceability applications for Industry 4.0. However, there has been little quantitative analysis of several aspects of these new blockchain-based traceability systems. For instance, very few works have studied blockchain’s impact on the resources of constrained IoT sensors. Similarly, the infrastructure costs of these blockchain-based systems are not widely understood. This paper characterizes the resources of low-cost IoT sensors and provides a monetary cost model for blockchain infrastructure to support blockchain-based traceability systems. First, we describe and implement a farm-to-fork case study using public and private blockchain networks. Then, we analyze the impact of blockchain in six different resource-limited IoT devices in terms of disk and memory footprint, processing time, and energy consumption. Next, we present an infrastructure cost model and use it to identify the costs for the public and private networks. Finally, we evaluate the traceability of a product in different scenarios. Our results showed that low-cost sensors could directly interact with both types of blockchains with minimal energy overhead. Furthermore, our cost model showed that setting a private blockchain infrastructure costs approximately the same as that managing 50 products on a public blockchain network.
Analysis of existing work and studies lead to the observation that BIoT (Blockchain (BC) and Internet of Things (IoT) integration) faces various efficiency issues in IoT-to-BC adaption associated with (a) scalability, (b) energy efficiency, and (c) security. To solve these concerns, at the first step and via experimental analysis of multiple Distributed Applications (dApp), this paper and PhD thesis does identify key BIoT efficiency affecting metrics. In the second step, these metrics are used to design and evaluate an efficient BIoT architecture —termed as BIIT—. Extensive simulations conducted on IoT network proves that BIIT enhances the efficiency of IoT-to-BC communications even for a limiting IoT protocol such as LoRaWAN. As of the third, the design and evaluation of DLIT (Distributed Ledger (DL) for IoT daTa) is presented. DLIT offers a highly scalable and secure DL via a hybrid consensus mechanism, equipped with sharding, and IoT data modification possibilities.
The publicly accessible feature of edge servers leads to the threat of malicious access to the data stored on the server and a series of security problems such as the leakage of user data privacy and the destruction of integrity. Data custody causes the separation of user ownership and management rights and brings potential security risks of data theft and destruction. Among them, for the integrity of the data uploaded by the terminal, the current protection mechanism mostly verifies the identity of the visitor or encrypts the data, but the role of verification is mostly assumed by the server, and it is impossible to avoid the collusion of edge servers with malicious intruders. In this paper, a distributed virtual machine agent (VMA) is designed and implemented, an edge cloud data integrity monitoring framework is built, and the verification protocol based on blockchain is proposed, which achieves trusted verification without relying on a trusted third party. Also, a prototype system of edge cloud data integrity protection based on blockchain is constructed to prevent data corruption. The results of security proof and experimental verification show that the mechanism based on blockchain technology can defend against three attacks of cloud service providers, has superior computation, and reduces the storage costs to protect the integrity of user data.
Internet of Things is a recent potential advancement in an IT arena, consists of multiple smart things (devices) which are connected through a physical network. Cisco incorporation predicts that IoT network will connect 50 billion devices by 2020. Most of the industries are adopting IoT technology and because of its fast spreading, immense adoption and deployment current authentication mechanisms have serious disadvantages. For numerous reasons the security issues are the major hurdle in adoption and deployment of IoT on a large scale since it is highly vulnerable to attacks. In this paper we propose a Blockchain based authentication mechanism i.e. Ethereum which is a public blockchain as it has emerged as a technology that possess great capabilities of providing secure authentication, management and access control for IoT devices in a decentralized, trusty and flexible manner by creating a secure environment where the devices can identify and trust each other and only authenticated users are given permission to access them.
Mahmood K. Mohammed, Alharith A. Abdullah, Zaid A. Abod
In general, health records include important information like the patient’s history, findings of examinations and assessments, diagnosis reports, documentation of consent, and treatment plans. Sharing this information has grown to be a challenge concerning data security, as it could result in compromising patient privacy. Therefore, the patient's information should not be misused or tampered with. In this paper, a full process of storing and retrieving medical records is proposed using a decentralized system through the integration of two emerging technologies: Blockchain and Inter-Planetary File System (IPFS). The system provides solutions for the major security concerns associated with medical files, including authentication and authorization, database breaches, data integrity of local and cloud storage, and data availability. The obtained results indicate a high level of safety by adding security layers such as confidentiality, authentication, authorization and access control, based on different factors. All these aspects contribute to reaching the aim of the proposed system, which is storing and retrieving medical records in a decentralized and safe manner.
Randeep Singh, Bilal Ahmed Mir, Lohith J. J, Dhruva Sreenivasa Chakravarthi · 7 authors
A radio communication sensor system is a collection of sensor modules that are connected to one another through wireless communication. It is common for them to be battery-powered and responsive to a nearby controller, referred to as the base station. They are capable of doing basic computations and transferring information to the base station in most scenarios. They are also in charge of transporting data from distant nodes, putting a burden on nodes with limited resources, and contributing to the quick depletion of energy in these nodes in the process. Nodes in close proximity to the base station are responsible for more than only detecting and sending data to the base station; they are also responsible for transmitting data from faraway nodes. To reward nodes that perform well, a protocol known as the Improved Fuzzy Inspired Energy Effective Protocol (IFIEEP) employs three separate sorts of nodes in order to provide more energy to those who do not. It takes into account the remaining node energy, the node's proximity to the base station, the node's neighbor concentration, and the node's centrality in a cluster when determining node viability. All of these assumptions are founded on a shaky understanding of the situation. Adaptive clustering must be applied to the most viable nodes in order to identify cluster leaders and transmit data to the base station, in addition to disseminating data across the rest of the network, in order to achieve success. In addition, the research provides proper heterogeneity parameters, which describe, among other things, the number of nodes as well as the starting energy of each node. The percentage gain in-network lifetime when compared to current approaches is minor for smaller numbers of supernodes; however, the percentage gain in the area covered 12.89 percent and 100% when more significant numbers of super nodes are used. These improvements in stability, residual energy, and throughput are accomplished by combining these improvements while also taking into consideration the previously neglected energy-intensive sensing energy aspect. The protocol that has been presented is meant to be used in conjunction with applications that make use of blockchain technology.
The blockchain-enabled smart logistics market is expected to grow worth USD 1620 billion and at a compound annual growth rate of 62.4%. Smart logistics ensures intelligence infrastructure, logistics automation, real-time analysis of supply chain data synchronization of the logistics process, cost transparency, unbroken shipment tracking all the way down to the transportation route, etc. In the smart logistics domain, significant advancement and growth of the Internet of Things (IoT) sensors are evident. However, the connectivity of IoT systems, including Tactile Internet, without proper safeguards creates vulnerabilities that can still be deliberately or inadvertently cause disruption. In view of this, we primarily notice two key issues. Firstly, the logistics domain can be compromised by a variety of natural or man-made activities, which eventually affect the overall network security. Secondly, there are thousands of entities in the supply chain network that use extensive machine-learning algorithms in many scenarios, and they require high-power computational resources. From these two challenges, we note that the first concern can be addressed by adding blockchain to IoT logistic networks. The second issue can be addressed using 6G. This will support 1-μs latency communications, support seamless computing at the edges of networks, and autonomously predict the best optimal location for edge computing. Motivated by this, we have highlighted motivational examples to show the necessity to integrate 6G and blockchain in smart logistic networks. Then, we have proposed a 6G and blockchain-enabled smart logistic high-level framework. We have presented the key intrinsic issues of this framework mainly from the security and resource management context. In this paper, recent state-of-the-art advances in blockchain enabled next-generation smart logistic networks are analyzed. We have also examined why 6G and not 5G would be compatible with the smart network. We have introduced five different use cases of blockchain technology in smart logistics. Later, this paper discusses some important concerns that blockchain in smart logistics might face. We have also provided potential solutions to tackle these concerns.