Blockchain-based IoT Research Articles

Blockchain-based IoT system for personalized indoor temperature control

This study aimed to develop a blockchain-based IoT (BIoT) system for adopting automated personalized indoor temperature control to the building management system (BMS) while ensuring data privacy and security. A novel blockchain framework was proposed to register occupants and the personalized thermal sensation vote (TSV) prediction model for training, and control indoor temperatures while ensuring the security of occupant and building data. By implementing the proposed BIoT temperature control system, it could securely transfer about 30,000 personal data for TSV prediction at the same time using a single PC. Moreover, the personalized TSV prediction model could improve accuracy compared to the existing generalized TSV prediction model. As a result, the developed BIoT temperature control system could improve thermal comfort and energy efficiency compared to manual indoor temperature control. Occupants can ultimately be satisfied with the personalized temperature control in every room where required IoT devices are installed without privacy issues.

Blockchain-based IoT enabled health monitoring system

Blockchain-based IoT enabled health monitoring system

A Lightweight and Attack-Proof Bidirectional Blockchain Paradigm for Internet of Things

Diverse technologies, such as machine learning and big data, have been driving the prosperity of the Internet of Things (IoT) and the ubiquitous proliferation of IoT devices. Consequently, it is natural that IoT becomes the driving force to meet the increasing demand for frictionless transactions. To secure transactions in IoT, blockchain is widely deployed since it can remove the necessity of a trusted central authority. However, the mainstream blockchain-based IoT payment platforms, dominated by Proof-of-Work (PoW) and Proof-of-Stake (PoS) consensus algorithms, face several major security and scalability challenges that result in system failures and financial loss. Among the three leading attacks in this scenario, double-spend attacks and long-range attacks threaten the tokens of blockchain users, while eclipse attacks target Denial of Service. To defeat these attacks, a novel bidirectional-linked blockchain (BLB) using chameleon hash functions is proposed, where bidirectional pointers are constructed between blocks. Furthermore, a new committee members auction (CMA) consensus algorithm is designed to improve the security and attack resistance of BLB while guaranteeing high scalability. In CMA, distributed blockchain nodes elect committee members through a verifiable random function. The smart contract uses Shamir’s secret-sharing scheme to distribute the trapdoor keys to committee members. To better investigate BLB’s resistance against double-spend attacks, an improved Nakamoto’s attack analysis is presented. In addition, a modified entropy metric is devised to measure eclipse attack resistance across different consensus algorithms. Extensive evaluation results show the superior resistance against attacks and demonstrate high scalability of BLB compared with current leading paradigms based on PoS and PoW.

Blockchain localization spoofing detection based on fuzzy AHP in IoT systems

Location spoof detection is a major component of location proofing mechanisms in internet of things (IoT), and it is significant for the system to assess the trustworthiness of the location data associated with the user. Unlike the work that employs physical layer features, we interest in building the infrastructure for a solution to establish location spoofing detection capabilities in blockchain-based IoT systems. In detail, at the node and the mobile trajectory level, we create an IoT system for evaluating the trustworthiness of location proofs with blockchain location system features. A blockchain-based multilayer fuzzy hierarchical analysis process (AHP) evaluation method is contemplated to detect location spoofing in the IoT system. Simulation results indicate the proposed method has a superior performance and provides a basis for the trustworthiness assessment of location proofs.

Building trust of Blockchain-based Internet-of-Thing services using public key infrastructure

ABSTRACT The advancement of hardware, software, and Internet infrastructure leads to the increasing quantities of smart Internet of Things (IoT) devices. Meanwhile, security issues have increasingly brought to us the concerns due to the evolving IoT scope and mass communications. Trusting service vendors depends on their devices that generate information and provide executions. Blockchain becomes an attractive choice, as evidenced by its wide adoptions. However, trusting IoT-based services becomes an important issue since the implementation of Blockchain-based IoT (BIoT) services is proprietary and independent. This paper introduces a generic architecture design that incorporates Public Key Infrastructure (PKI) to establish trust of BIoT services. This can potentially solve the trust problem and based on our experiment it can be scaled well. We also demonstrate how specification languages can be useful to express requirements. It decouples users from Blockchain and thus they can specify qualities of BIoT services without deep knowledge to work with Blockchain.

Blockchain-Based Internet of Things: Machine Learning Tea Sensing Trusted Traceability System

A framework combining the Internet of Things (IoT) and blockchain can help achieve system automation and credibility, and the corresponding technologies have been applied in many industries, especially in the area of agricultural product traceability. In particular, IoT devices (radio frequency identification (RFID), geographic information system (GIS), global positioning system (GPS), etc.) can automate the collection of information pertaining to the key aspects of traceability. The data are collected and input to the blockchain system for processing, storage, and query. A distributed, decentralized, and nontamperable blockchain can ensure the security of the data entering the system. However, IoT devices may generate abnormal data in the process of data collection. In this context, it is necessary to ensure the accuracy of the source data of the traceability system. Considering the whole-process traceability chain of agricultural products, this paper analyzes the whole-process information of a tea supply chain from planting to sales, constructs the system architecture and each function, and designs and implements a machine learning- (ML-) blockchain-IoT-based tea credible traceability system (MBITTS). Based on IoT technologies such as radio frequency identification (RFID) sensors, this article proposes a new method that combines blockchain and ML to enhance the accuracy of blockchain source data. In addition, system data storage and indexing methods and scanning and recovery mechanisms are proposed. Compared with the existing agricultural product (tea) traceability system based on blockchain, the introduction of the ML data verification mechanism can ensure the accuracy (up to 99%) of information on the chain. The proposed solution provides a basis to ensure the safety, reliability, and efficiency of agricultural traceability systems.

Blockchain-Based Deep Learning to Process IoT Data Acquisition in Cognitive Data.

Remote health monitoring can help prevent disease at the earlier stages. The Internet of Things (IoT) concepts have recently advanced, enabling omnipresent monitoring. Easily accessible biomarkers for neurodegenerative disorders, namely, Alzheimer's disease (AD) are needed urgently to assist the diagnoses at its early stages. Due to the severe situations, these systems demand high-quality qualities including availability and accuracy. Deep learning algorithms are promising in such health applications when a large amount of data is available. These solutions are ideal for a distributed blockchain-based IoT system. A good Internet connection is critical to the speed of these system responses. Due to their limited processing capabilities, smart gateway devices cannot implement deep learning algorithms. In this paper, we investigate the use of blockchain-based deep neural networks for higher speed and delivery of healthcare data in a healthcare management system. The study exhibits a real-time health monitoring for classification and assesses the response time and accuracy. The deep learning model classifies the brain diseases as benign or malignant. The study takes into account three different classes to predict the brain disease as benign or malignant that includes AD, mild cognitive impairment, and normal cognitive level. The study involves a series of processing where most of the data are utilized for training these classifiers and ensemble model with a metaclassifier classifying the resultant class. The simulation is conducted to test the efficacy of the model over that of the OASIS-3 dataset, which is a longitudinal neuroimaging, cognitive, clinical, and biomarker dataset for normal aging and AD, and it is further trained and tested on the UDS dataset from ADNI. The results show that the proposed method accurately (98%) responds to the query with high speed retrieval of classified results with an increased training accuracy of 0.539 and testing accuracy of 0.559.

Deep Learning Based Homomorphic Secure Search-Able Encryption for Keyword Search in Blockchain Healthcare System: A Novel Approach to Cryptography.

Due to the value and importance of patient health records (PHR), security is the most critical feature of encryption over the Internet. Users that perform keyword searches to gain access to the PHR stored in the database are more susceptible to security risks. Although a blockchain-based healthcare system can guarantee security, present schemes have several flaws. Existing techniques have concentrated exclusively on data storage and have utilized blockchain as a storage database. In this research, we developed a unique deep-learning-based secure search-able blockchain as a distributed database using homomorphic encryption to enable users to securely access data via search. Our suggested study will increasingly include secure key revocation and update policies. An IoT dataset was used in this research to evaluate our suggested access control strategies and compare them to benchmark models. The proposed algorithms are implemented using smart contracts in the hyperledger tool. The suggested strategy is evaluated in comparison to existing ones. Our suggested approach significantly improves security, anonymity, and monitoring of user behavior, resulting in a more efficient blockchain-based IoT system as compared to benchmark models.

Fast and Efficient Security Scheme for Blockchain-Based IoT Networks

Internet of Things (IoT) has become widely used nowadays and tremendous increase in the number of users raises its security requirements as well. The constraints on resources such as low computational capabilities and power requirements demand lightweight cryptosystems. Conventional algorithms are not applicable in IoT network communications because of the constraints mentioned above. In this work, a novel and efficient scheme for providing security in IoT applications is introduced. The scheme proposes how security can be enhanced in a distributed IoT application by providing multilevel protection and dynamic key generation in the data uploading and transfer phases. Existing works rely on a single key for communication between sensing device and the attached gateway node. In proposed scheme, this session key is updated after each session and this is done by applying principles of cellular automata. The proposed system provides multilevel security by using incomparable benefits of blockchain, dynamic key and random number generation based on cellular automata. The same was implemented and tested with the widely known security protocol verification tool called Automated Validation of Internet Security Protocols and Applications (AVISPA). Results show that the scheme is secure against various attacks. The proposed scheme has been compared with related schemes and the result analysis shows that the new scheme is fast and efficient also.

Securing the Internet of Things (IoT) with Blockchain: A Proof-of-Concept Implementation and Analysis

The Internet of Things (IoT) has revolutionized the way we interact with everyday objects, enabling devices to collect and share data seamlessly. However, this increased connectivity has also increased the security risks associated with these devices, as they often lack the necessary security mechanisms to prevent malicious attacks. To address this issue, we propose using blockchain technology to secure IoT devices. In this paper, we present a proof-of-concept implementation of a blockchain-based IoT security system and analyze its effectiveness. Our system leverages blockchain's distributed ledger technology to ensure data integrity, decentralization, and transparency, making it more resilient to attacks. We evaluate our system's performance and compare it with other existing IoT security solutions. Our results show that our blockchain-based approach outperforms traditional security measures and is a viable solution for securing IoT devices. Finally, we discuss the limitations of our study and suggest future research directions for improving the security of IoT devices.

Survey on Blockchain-Based IoT Payment and Marketplaces

The ever-growing smart applications will expand the Internet of Things (IoT) ecosystem to connect over 75 billion devices by 2025. IoT ecosystems comprise sensors that act as data suppliers and applications where monetary transactions are required to compensate the data producers. This signifies the importance of IoT payments and marketplaces to facilitate micro-transactions of billions of connected devices in the IoT ecosystem, which is heterogeneous, decentralized, and diverse. However, realizing such an ecosystem raises multiple challenges such as overcoming poor inter-operability, resource constraints, and security and privacy vulnerabilities of IoT devices and platforms. Blockchain is a Distributed Ledger Technology (DLT) that can be identified as a potential solution to overcome the challenges in realizing IoT payments and marketplaces. This is due to the characteristics of blockchain such as decentralization, traceability, immutability, and non-repudiation. This paper presents a comprehensive survey on blockchain-based IoT payments and marketplaces. This paper provides a brief introduction to the concepts of IoT payments and IoT marketplaces. Then the technical challenges involved in realizing IoT payment and marketplaces are discussed by highlighting the blockchain-based solutions. Furthermore, blockchain-based smart applications which use IoT marketplace and IoT payment concepts are presented marking the role of blockchain in each of the application. Subsequently, the paper discussed the integration challenges while also highlighting possible solutions. It is envisaged that this paper would shed light on the development of blockchain-based solutions to realize IoT payments and marketplaces.

A Blockchain-Based IoT Framework for Oil Field Remote Monitoring and Control

The oil and gas industry involves a high level of operational expenditure and often faces high risks of asset safety and operational failures. It has never been so important to monitor and control the oil field operations remotely in real-time to ensure safety and efficiency. The traditional monitoring and control systems for oil field operations are typically centralized, prone to failure, and lack efficiency. Blockchain technology mitigates the centralization problem by creating a decentralized, immutable and transparent control environment for automatic monitoring and control of industrial operations. In this study, we propose a blockchain-based IoT framework for real-time monitoring and control to increase oil field operation and asset efficiency and safety. We present the key components of the framework, including the system architecture, operation flows, algorithms, and smart contracts. As a proof-of-concept modeling, a smart contract is developed and validated on a blockchain test platform. A comparative analysis shows the advantages of using blockchain technology and smart contract to provide trustworthy and automatic monitoring and control for oil field operations.

High-performance Edwards curve aggregate signature (HECAS) for nonrepudiation in IoT-based applications built on the blockchain ecosystem

“Blockchain” is a buzzword that has captured attention from researchers in almost every possible domain. In a blockchain ecosystem, multiple parties across the network have to establish trust in an untrusted environment to ensure seamless nonrepudiation. Nonrepudiation is a crucial factor for secure information auditing in the blockchain. To achieve this, we require an optimal digital signature. In this work, we design a digital signature to address the nonrepudiation challenge in blockchain ecosystems. Our approach developed in the current work completed signing and verification tasks with 10% and 13% shorter processing times, respectively than the conventional digital signature scheme. The adoption of the high-performance Edwards curve aggregate signature (HECAS) in a blockchain ecosystem can yield a 10% improvement in the transaction flow, a 10% improvement in block validation and a 40% decrease in storage costs relative to the same system implemented without HECAS. Finally, we simulated various blockchain-based Internet of Things (IoT) ecosystems and experimented with our scheme. The results show that our work can produce convincing, consistent results across various sensor data types from smart IoT-based blockchain solutions.

A framework for privacy-preservation of IoT healthcare data using Federated Learning and blockchain technology

With the dramatically increasing deployment of IoT (Internet-of-Things) and communication, data has always been a major priority to achieve intelligent healthcare in a smart city. For the modern environment, valuable assets are user IoT data. The privacy policy is even the biggest necessity to secure user’s data in a deep-rooted fundamental infrastructure of network and advanced applications, including smart healthcare. Federated learning acts as a special machine learning technique for privacy-preserving and offers to contextualize data in a smart city. This article proposes Blockchain and Federated Learning-enabled Secure Architecture for Privacy-Preserving in Smart Healthcare, where Blockchain-based IoT cloud platforms are used for security and privacy. Federated Learning technology is adopted for scalable machine learning applications like healthcare. Furthermore, users can obtain a well-trained machine learning model without sending personal data to the cloud. Moreover, it also discussed the applications of federated learning for a distributed secure environment in a smart city.

Blockchain-Based IoT Devices in Supply Chain Management: A Systematic Literature Review

Through recent progress, the forms of modern supply chains have evolved into complex networks. The supply chain management systems face a variety of challenges. These include lack of visibility of the upstream party (Provider) to the downstream party (Client); lack of flexibility in the face of sudden variations in demand and control of operating costs; lack of reliance on safety stakeholders; ineffective management of supply chain risks. Blockchain (BC) is used in the supply chain to overcome the growing demands for items. The Internet of Things (IoT) is a profoundly encouraging innovation that can help companies observe, track, and monitor products, activities, and processes within their respective value chain networks. Research establishments and logical gatherings are ceaselessly attempting to answer IoT gadgets in supply chain management. This paper presents orderly writing on and reviewing of Blockchain-based IoT advances and their current usage. We discuss the smart devices used in this system and which device is the most appropriate in the supply chain. This paper also looks at future examination themes in blockchain-based IoT, referred to as the executive’s framework production network. The essential deliberate writing audit has been consolidated by surveying research articles circulated in highly reputable publications between 2016 and 2021. Lastly, current issues and challenges are present to provide researchers with promising future directions in IoT supply chain management systems.

Sustainable Smart Cities: Convergence of Artificial Intelligence and Blockchain

Recently, 6G-enabled Internet of Things (IoT) is gaining attention and addressing various challenges of real time application. The artificial intelligence plays a significant role for big data analytics and presents accurate data analysis in real time. However, designing big data analysis through artificial intelligence faces some issues in terms of security, privacy, training data, and centralized architecture. In this article, blockchain-based IoT framework with artificial intelligence is proposed which presents the integration of artificial intelligence and blockchain for IoT applications. The performance of the proposed architecture is evaluated in terms of qualitative and quantitative measurement. For qualitative measurement, how the integration of blockchain and artificial intelligence addresses various issues are described with the description of AI oriented BC and BC oriented AI. The performance evaluation of proposed AI-BC architecture is evaluated and compared with existing techniques in qualitative measurement. The experimental analysis shows that the proposed framework performs better in comparison with the existing state of art techniques.

CBCIoT: A Consensus Algorithm for Blockchain-Based IoT Applications

Internet of things is widely used in the current era to collect data from sensors and perform specific tasks through processing according to the requirements. The data collected can be sent to a blockchain network to create secure and tamper-resistant records of transactions. The combination of blockchain with IoT has huge potential as it can provide decentralized computation, storage, and exchange for IoT data. However, IoT applications require a low-latency consensus mechanism due to its constraints. In this paper, CBCIoT, a consensus algorithm for blockchain-based IoT applications, is proposed. The primary purpose of this algorithm is to improve scalability in terms of validation and verification rate. The algorithm is developed to be compatible with IoT devices where a slight delay is acceptable. The simulation results show the proposed algorithm’s efficiency in terms of block generation time and transactions per second.

Comparative study on hash functions for lightweight blockchain in Internet of Things (IoT)

Over the last few years, there has been a great interest in the Internet of Things (IoT). This is mainly because the IoT interacts directly with people's everyday lives in critical applications, such as in smart homes and healthcare applications. IoT devices typically have a resource-constrained architecture, rendering them vulnerable to cyberattacks. Accordingly, smart devices and stored data need to be secured through lightweight and energy-efficient security solutions, which have been identified as the main challenge facing adoption of IoT systems. To address this problem, a disruptive technology (blockchain) has been foreseen by the industry and research community as being able to deliver secure, fast, reliable, and transparent solutions for IoT systems. Hence, this work investigates the adoption of lightweight blockchain technology, mainly as a method of securing IoT systems. Because hashing plays a major role in creating a robust blockchain structure, we select a number of different hash techniques to be executed on a Raspberry Pi device. In summation, this work provides a numerical study to evaluate the performance of well-known hash functions that can be used for lightweight blockchain-based IoT.

A Blockchain-Based IoT Cross-Domain Delegation Access Control Method

The collaborative demand in the Internet of Things (IoT) is becoming stronger. One of the collaborative challenges is the security of interoperability between different management domains. Although cross-domain access control mechanisms exist in IoT, the majority of them are based on a trusted third party. In addition, the heterogeneity of multidomain policies makes it difficult for authority delegation to satisfy the principle of least authority. In this paper, we propose a blockchain-based IoT cross-domain delegation access control method (CDDAC). The delegation-trajectory-on-blockchain strategy proposed enhances the scalability of the cross-domain delegation system. The presented multidomain delegation trajectory aggregation scheme supports the forensic analysis of the cross-domain delegation system. The performance of CDDAC is evaluated in the Ropsten, which is the Ethereum’s official public blockchain test network. The experimental results show that CDDAC has faster delegation verification speed and higher decision-making efficiency than existing work, demonstrating the lightweight and scalability of the method.

A review study on blockchain-based IoT security and forensics

A review study on blockchain-based IoT security and forensics