The healthcare industry is exponentially growing its dependence on smart wearables and remote devices for efficient treatment and diagnosis. These smart devices benefit the healthcare industry, but they raise serious security and integrity concerns while exchanging healthcare data. These devices are primarily meant for data dissemination; hence, they are equipped with weak security protocols that are susceptible to attacks like distributed denial-of-service (DDoS), data injection, and man-in-the-middle (MiTM) attacks. To circumvent the aforementioned security challenges, this article proposed a secure and intelligent data exchange framework for smart healthcare systems. For that, we amalgamate artificial intelligence (AI) and blockchain technology to strengthen the security of data dissemination between smart medical devices. Further, we adopted fuzzy logic that extracts the essential features from the healthcare security dataset to enhance the detection rate of AI models. We used different AI algorithms such as logistic regression (LR), random forest (RF), decision trees (DT), stochastic gradient descent (SGD), and Gaussian naive Bayes (GNB) to classify healthcare data into malicious and non-malicious. The predicted data can still be maneuvered by adversaries that introduce subtle changes that skew the results to their advantage. Therefore, we employed blockchain technology that stores non-malicious healthcare data (predicted data) from data tampering attacks. The developed smart contract validates the non-malicious healthcare data and only allows them to be securely stored inside the interplanetary file system (IPFS)-based public blockchain. The proposed framework is evaluated by considering various evaluation metrics like recall, precision, accuracy, F1 score, area under the curve (AUC) score, and blockchain scalability.
Zainab Khalid Mohammad, Salman Bin Yousif, Yunus Bin Yousif
Abstract The metaverse, a virtual multiuser environment, has garnered global attention for its potential to offer deeply immersive and participatory experiences. As this technology matures, it is evolving in tandem with emerging innovations such as Web 3.0, Blockchain, nonfungible tokens, and cryptocurrencies like Bitcoin, which play pivotal roles in the metaverse economy. Robust Bitcoin networks must be modelled for the metaverse environment in Industry 5.0 platforms to ensure the metaverse’s sustained growth and relevance. Industry 5.0 is poised to experience significant economic expansion, driven in large part by the transformative influence of metaverse technology. Researchers have actively explored diverse strategies and approaches to address the unique challenges and opportunities presented by current Bitcoin networks, highlighting the limitless potential for enhancing anonymity and privacy while navigating this exciting digital frontier. By addressing the diverse anonymity and privacy evaluation attributes, the lack of clarity regarding the prioritisation of these attributes and the variability in data, this modelling approach can be categorised as a form of multiple attribute decision-making (MADM). This review seeks to achieve three main objectives: firstly, to identify research gaps, obstacles, and problems within scholarly literature, which is crucial for assessing and modelling Bitcoin networks to succour the metaverse environment of Industry 5.0; secondly, to pinpoint theoretical gaps, proposed solutions, and benchmarking of Bitcoin networks; and thirdly, to offer an overview of the existing validation and evaluation methods employed in the literature. This review introduced a unique taxonomy by intersecting “Bitcoin networks based on blockchain aspects” with “anonymity and privacy development attributes aspect.” It emphasised the study’s significance and innovation. The results illustrate that employing MADM techniques is highly suitable for modelling Bitcoin networks to support the metaverse within the context of Industry 5.0. This thorough review is an invaluable resource for academics and decision-makers, offering perspectives regarding the improvements, applications, and potential directions for evaluating Bitcoin networks to bolster the metaverse environment of Industry 5.0.
The study introduces an efficient data aggregation technique for smart agriculture by leveraging Blockchain technology and a novel method referred to as the "cluster head sleep schedule." The primary objective is to enhance the data collection process within a large-scale agricultural setting where multiple sensors continually generate vast amounts of data while monitoring and safeguarding crops from pest attacks. The proposed method involves the segmentation of sensors into clusters, each led by a designated cluster head responsible for collecting data from its constituent members deployed in the field to monitor pest attacks and promptly report any issues to the management. To curtail data redundancy, the study employs a fuzzy matrix to group nodes based on high-similarity data. This approach enables the selective suspension of certain nodes while others remain active. The data received from these nodes undergoes analysis using a fuzzy similarity matrix for clustering, ensuring that only unique data is transmitted to the base station. Redundant nodes from all clusters are identified and placed in a sleep mode, thus conserving energy and prolonging the network’s lifespan. This sleep scheduling mechanism is implemented subsequent to data redundancy reduction, facilitating immediate pest attack control in agriculture. By implementing these techniques, smart agriculture stands to benefit from optimized energy utilization and reduced costs associated with monitoring and pest control, thereby fostering sustainable and efficient operations. The cluster head is responsible for storing the data on a base station positioned at the network’s edge, allowing for local processing and prompt communication of pest attack information to the farmer for immediate action. Moreover, this edge system stores the data on a Blockchain network for future analysis and serves as a guideline for pest attack control in the pesticide industry, thereby enhancing data security and immutability. In addition to these advantages, the research also emphasizes the importance of controlling pest attacks to enhance crop production in the field, ultimately contributing to the country’s economic growth. Simulation results affirm that the proposed approach leads to notable cost reductions, decreased energy consumption, improved crop production, precise crop monitoring to prevent pest attacks, and a prolonged network lifespan. These outcomes underscore the effectiveness of this approach within the context of smart agriculture and its role in enhancing the monitoring system for smart agriculture and bolstering security through Blockchain technology.
This study investigates the impact of Zlib compression on gas consumption within blockchain systems, focusing particularly on Ethereum transactions. By employing the Ethereum simulator Ganache, we simulate 100 realistic home delivery system datasets to evaluate the performance of compressed versus uncompressed data. The methodology encompasses rigorous statistical analysis to ensure robust results. Our findings reveal that using the Zlib algorithm to compress textual data exceeding 141 bytes before submitting transactions on the Ethereum network reduces the gasUsed while maintaining the system time unchanged. This demonstrates the effectiveness of data compression in optimizing transaction costs without affecting operational efficiency. Additionally, our research extends to analyzing real gasPrice trends on the Ethereum network. We propose a non-linear regression model that accurately predicts hourly gasPrice variations based on the day of the week and the specific time. This provides a valuable tool for users to plan transactions strategically. These insights enhance the understanding of blockchain dynamics and offer practical solutions for improving economic and system efficiency in blockchain operations.
Mohammed L. Khalaf, Israa M. Hayder, Taief Alaa Al-Amiedy, Hussain A. Younis · 8 authors
The Internet of Thing (IoT) is an innovative technology designed to integrate tangible artefacts with the digital era, resulting in the development of new digital services to improve and ease our lives. Despite the advantages of IoT technology in a variety of industries. The existing centralised IoT architecture has a number of issues, including single point of failure, stability, safety, accountability, and data integrity. Such issues are impeding the growth of IoT in the future. To address the a forementioned issues, distributed ledger technologies are regarded as promising and feasible solutions. The blockchain is one of the most prevalent and widely used forms of distributed ledger technology. The combination of IoT and blockchain technology has numerous advantages. The combination of IoT and blockchain technologies will provide numerous benefits. This article demonstrates the fundamentals of IoT and blockchain technology in order to provide a thorough analysis of the architecture of the combination of IoT and blockchain technology. In addition, this study provided a comprehensive description of the combination of the blockchain with the IoT platform from a variety of perspectives in order to address IoT's shortcoming. The service function of blockchain in IoT applications is demonstrated. Finally, the prospective applications of blockchain technology to IoT fields are discussed.
Latifa Albshaier, Alanoud Budokhi, Ahmed Aljughaiman
The integration of the Internet of Things (IoT) and cloud computing, which play essential roles in our everyday routines, is expected to emerge as a fundamental element of the forthcoming internet, realizing increased usage and acceptance. This fusion is anticipated to revolutionize various applications, offering The integration of IoT and cloud may pose challenges. Cloud computing’s capacity to distribute resources and data across diverse locations, facilitating access from different industrial settings, has significantly enhanced IoT functionality. However, rapid migration to the cloud has raised security concerns, as conventional security measures for computers are not always applied effectively to cloud-based systems. Overcoming these obstacles can be achieved by integrating cloud and IoT technologies, as the vast resources available on the cloud can greatly benefit IoT, helping the cloud transcend current limitations related to physical objects in a more dynamic, distributed manner. Several discoveries from the research were made by exploring the facilitation of a smooth shift of IoT initiatives to the cloud by studying IoT and cloud computing, investigating various cloud-related challenges and resolutions derived from recent scholarly works, and analyzing the most recent advancements in attacks targeting cloud-based IoT systems. Identifying gaps in the research on IoT-based cloud infrastructure and addressing cybersecurity in cloud computing is important for future research directions, necessitating a review of the technological challenges mentioned in the literature. As such, this research explores how blockchain technology effectively addresses security concerns within this combination, emphasizing its capacity to improve data integrity and privacy and to ensure secure transactions. The exploration delves into the multifaceted implications and potential applications of blockchain, elucidating its role in reinforcing the overall security of these interconnected systems.
Paula Fraga‐Lamas, Tiago M. Fernández‐Caramés, António Miguel Rosado da Cruz, Sérgio Ivan Lopes
Industry 5.0 is an evolving concept that aims to enhance the way modern factories operate by seeking long-term growth, production efficiency and the well-being of industrial workers. Human-centricity, sustainability and resilience are the three pillars of Industry 5.0, which are developed on Industry 4.0 enabling technologies. One of the most compelling technologies to help implement the communications architecture proposed by Industry 5.0 is blockchain, which can provide trustworthy, secured and decentralized information to different industrial domains. This article provides an analysis of the transition between Industry 4.0 and Industry 5.0 paradigms. Moreover, it examines the benefits and challenges that arise when using blockchain to develop Industry 5.0 applications and analyzes the design factors that should be considered when developing this type of applications. Furthermore, it presents a thorough review on the most relevant blockchain-based applications for Industry 5.0 pillars. Therefore, the main goal of this article is to provide a comprehensive and detailed guide for future Industry 5.0 developers that allows for determining how blockchain might benefit the next generation of human-centric, sustainable, and resilient applications.
The Internet of Vehicles (IoV) represents a paradigm shift in vehicular communication, aiming to enhance traffic efficiency, safety, and the driving experience by leveraging interconnected vehicles. Despite its promise, the IoV faces challenges such as efficient task offloading, energy management, and data security. Mobile Edge Computing (MEC) emerges as a solution to some of these challenges by bringing computational resources closer to the vehicular network’s edge, yet it raises critical concerns regarding resource management, service continuity, and scalability in dynamic vehicular environments. Addressing both IoV and MEC challenges necessitates robust and dynamic optimization mechanisms. In response to these challenges, our study introduces a multi-objective approach using Double Deep Q-Networks (DDQN), a cutting-edge application of Deep Reinforcement Learning (DRL). This algorithm combines the strengths of Deep Neural Networks (DNNs) and Deep Learning (DL) techniques, enabling dynamic decision-making that can adapt to changing conditions. By considering multiple objectives, the DDQN algorithm allows for a sophisticated trade-off analysis, efficiently balancing between the different objectives to optimize overall system performance. Through the use of Blockchain technology, known for its secure, decentralized structure, our model enhances the integrity of data, providing a reliable and efficient solution for IoV-MEC systems. We conducted a comparative analysis of our model against the standard Deep Q-Network (DQN) and Deep Deterministic Policy Gradient (DDPG) algorithms, which are prevalent in this field. Our model demonstrated significant improvements over these traditional methods: energy consumption was reduced by 26.4%, latency decreased by 6.87%, and the cost was minimized by 7.41%.
The dynamic landscape of the Internet of Things (IoT) is set to revolutionize the pace of interaction among entities, ushering in a proliferation of applications characterized by heightened quality and diversity. Among the pivotal applications within the realm of IoT, as a significant example, the Smart Grid (SG) evolves into intricate networks of energy deployment marked by data integration. This evolution concurrently entails data interchange with other IoT entities. However, there are also several challenges including data-sharing overheads and the intricate establishment of trusted centers in the IoT ecosystem. In this paper, we introduce a hierarchical secure data-sharing platform empowered by cloud-fog integration. Furthermore, we propose a novel non-interactive zero-knowledge proof-based group authentication and key agreement protocol that supports one-to-many sharing sets of IoT data, especially SG data. The security formal verification tool shows that the proposed scheme can achieve mutual authentication and secure data sharing while protecting the privacy of data providers. Compared with previous IoT data sharing schemes, the proposed scheme has advantages in both computational and transmission efficiency, and has more superiority with the increasing volume of shared data or increasing number of participants.
<abstract> <p>Ensuring the reliability and trustworthiness of massive IoT-generated data processed in cloud-based systems is paramount for data integrity in IoT-Cloud platforms. The integration of Blockchain (BC) technology, particularly through BC-assisted data Edge Verification combined with a consensus system, utilizes BC's decentralized and immutable nature to secure data at the IoT network's edge. BC has garnered attention across diverse domains like smart agriculture, intellectual property, and finance, where its security features complement technologies such as SDN, AI, and IoT. The choice of a consensus algorithm in BC plays a crucial role and significantly impacts the overall effectiveness of BC solutions, with considerations including PBFT, PoW, PoS, and Ripple in recent years. In this study, I developed a Football Game Algorithm with Deep learning-based Data Edge Verification with a Consensus Approach (FGADL-DEVCA) for BC assisted IoT-cloud platforms. The major drive of the FGADL-DEVCA algorithm was to incorporate BC technology to enable security in the IoT cloud environment, and the DL model could be applied for fault detection efficiently. In the FGADL-DEVCA technique, the IoT devices encompassed considerable decentralized decision-making abilities for reaching an agreement based on the performance of the intrablock transactions. Besides, the FGADL-DEVCA technique exploited deep autoencoder (DAE) for the recognition and classification of faults in the IoT-cloud platform. To boost the fault detection performance of the DAE approach, the FGADL-DEVCA technique applied FGA-based hyperparameter tuning. The experimental result analysis of the FGADL-DEVCA technique was performed concerning distinct metrics. The experimental values demonstrated the betterment of the FGADL-DEVCA approach with other existing methods concerning various aspects.</p> </abstract>
C. Wang, Wei Wu, Fulong Chen, Hong Shu · 9 authors
Blockchain is commonly employed in access control to provide safe medical data exchange because of the characteristics of decentralization, nontamperability, and traceability. Patients share personal health data by granting access rights to users or medical institutions. The major purpose of the existing access control techniques is to identify users who are permitted to access medical data. They hardly ever recognize internal assailants from legitimate entities. Medical data will involve multilayer access within the authorized organizations. Considering the cost of permissions management and the problem of insider malicious node attacks, users hope to implement authorization constraints within the authorized institutions. It can prevent their data from being maliciously disclosed by end‐users from different authorized healthcare domains. For the purpose to achieve the fine‐grained permissions propagation control of medical data in sharing institutions, a trust‐based authorization access control mechanism is suggested in this study. Trust thresholds are assigned to different privileges based on their sensitivity and used to generate zero‐knowledge proof to be broadcasted among blockchain nodes. This method evaluates the trust of each user through the dynamic trust calculation model. And meanwhile, smart contract is employed to verify whether the user’s trust can activate some permissions and ensure the privacy of the user’s trust in the process of authorization verification. In addition, the authorization transaction between users and institutions is recorded on the blockchain for patient traceability and accountability. The feasibility and effectiveness of the scheme are demonstrated through comprehensive comparisons and extensive experiments.
Blockchain, a distributed and digital ledger technology, has the potential to transform several industries from cryptocurrencies to supply chains. However, the complexity of understanding the technology can be a challenge for most people, especially for newcomers. This study paper aims to provide an in-depth analysis and review of the different layers including the data, network, consensus, smart contract, and application layers. In this paper, we performed an in-depth analysis and review of the components of each layer. We also tried to simulate different consensus algorithms so a reader can understand which blockchain consensus algorithm can be chosen for a specific application. By reading this paper, a reader can understand the blockchain architecture and choose the right algorithms, languages and protocols for building their own blockchain network. The paper also addresses the challenges and difficulties of building a sustainable and secure blockchain.We believe that the choice of consensus algorithm is the most important thing for sustainability in a blockchain network. We show that some consensus algorithms use much more energy than others, and we suggest that developers choose consensus algorithms that use less energy. This paper is a great resource for anyone who wants to learn more about blockchain architecture and consensus algorithms. It gives a complete review of the subject and talks about the difficulties of making a blockchain that will be secure and sustainable. Researchers, developers, and anyone else interested in the future of blockchain technology will be interested in this study.
A blockchain is a distributed ledger with interrelated blocks secured by a consensus mechanism based on cryptography. The breadth of the blockchain network and the complexity of the consensus mechanism used to verify transactions are also the causes of slowness on the blockchain. This is referred to as a well-known scalability problem in public blockchain applications such as bitcoin. To overcome this, a simpler consensus mechanism can be used, or to manage the extent of the distribution on a ledger network. This study discusses various strategies to increase scalability, especially those related to limiting the ledger network using side chains technology. A side chain is a secondary chain that is connected to the main chain and has a consensus mechanism that is independent from the main chain. One way is to limit the number of nodes in the side chain so that the transaction verification process can be accelerated. In addition, grouping active node transactions into side chains can significantly reduce the burden on the main chain. Another strategy is to use a simpler consensus mechanism for transactions with small nominal values so transaction speed can be increased. Each strategy has its weaknesses, but implementing several of the proposed strategies together will cover the weaknesses of the other strategies to produce an effective method to increase scalability.
S. Deepak, Preeti Gulia, Nasib Singh Gill, Mohammad Yahya · 7 authors
Internet of Things (IoT) plays an essential contribution in connecting devices and enabling seamless data exchange, leading to increased efficiency and convenience. However, security concerns in IoT systems are significant, as compromised devices can lead to data breaches and privacy violations. Blockchain technology can enhance IoT security by providing decentralized consensus, immutability, and transparent transaction records, ensuring secure and trustworthy communication and data integrity. This review article gives a succinct but thorough understanding of blockchain technology, covering architecture of blockchain, working principles, types, applications, platforms, and its role in the IoT environment. The study highlights potential benefits of blockchain like enhanced security and privacy, and explores its integration with IoT. Additionally, the study discusses various real-world applications, examines blockchain platforms, and addresses the limitations and challenges associated with blockchain technology. This review serves as a valuable resource for researchers and practitioners seeking a deeper understanding of blockchain’s potential and its implications in the IoT landscape.
All of us know that cryptography is an innovative security strategy. Network security construction with authentication techniques of its layers through blockchain technologies is an important field to discuss. The problem that we are trying to solve is the Transaction Privacy Leakage in public Blockchain networks with IOT networks, which has resulted in the publicity of this data on the network as well as synchronizing the information that allowed it to be accessed and propagated between distributed nodes. At the same time, there are some privacy risk concerns associated with public data wherein transactions contain sensitive information about their issuers. Although some previous research introduced models to deal with the problem of Transaction Privacy Leakage like deterministic key generation, mixing services, ring signature, zero-knowledge proof, and quantum-resistant algorithms, the suggested models do not fully achieve prevention or integrity in all cases. This paper presents a developed Multi-Layer Blockchain Security Model (MLBSM) that can be used to protect IoT networks while also facilitating their implementation for protecting IoT networks and similar networks to prevent Transaction Privacy Leakage for all users in the public blockchain network. The clustering concept is utilized to facilitate the multi-layer architecture. By implementing this, we may achieve unprecedented levels of security and transparency in the blockchain network which will protect the privacy of all users in different technologies.
This paper presents a Blockchain-based framework for providing Blockchain services for purposes of stability in terms of consensus protocol infrastructure and governance mechanisms and accessible auxiliary services suitable for the vast majority of current business needs, including fundamental factors such as digital identity with autonomous identity, building solutions to ensure transaction privacy with zero-knowledge proofs, and other services related to digital assets. The proposed framework helps promote digital transformation for businesses, especially small and medium enterprises with limited resources and costs, to apply Blockchain technology to their business models, increasing competitive advantages and assisting the companies in focusing on business logic while still using Blockchain technology in their functions.
By 2025, the Internet of Things (IoT) infrastructure is projected to encompass over 75 billion devices, facilitated by the increasing proliferation of intelligent applications. The Internet of Things ecosystem consists of sensors that function as data generators and applications that necessitate financial transactions to compensate the data producers. Security is a highly important concern. Employing blockchain technology makes it feasible to enhance security by maintaining payments in a ledger that is not just secure but also translucent, distributed, and immutable. This article provides an introductory overview of the Internet of Things (IoT) and subsequently delves into the many security threats and vulnerabilities arising within the IoT framework. This study provided an overview of the blockchain, focusing on its categorization and important properties. Moreover, this article examines the necessity of combining blockchain technology with the Internet of Things (IoT), in addition to reviewing relevant literature and the studies conducted by other scholars. This article offers insight into the uses of blockchain on the Internet of Things (IoT).
Exponential growth of the space industry avails unprecedented opportunities to establish a marketplace of satellite infrastructure services. However, security and resource constraints pose critical challenges to implementing the exchange of services such as storage, compute or even arm-based manipulation. We propose a fully distributed architecture that will facilitate resilient, trustless interactions to enable space infrastructure as a service and applications such as in-space servicing. The distributed architecture engages Distributed Ledger Technology (DLT) such as blockchains and directed acyclic graphs to designate and enforce security policy via smart contracts between multiple parties across payloads owned or operated by different service providers on the same satellite bus or across a constellation. This work presents a zero-trust space infrastructure as a service architecture and examines how the architecture addresses critical challenges such as consensus and cyber resilience to facilitate a space services marketplace.
Building smart services for smart cities has become a significant focus of the Internet of Things (IoT). These IoT devices are able to sense their surroundings and react appropriately. Smart city applications emphasize the necessity of safe data sharing across heterogeneous devices. Certain behaviors taken while sharing could aim at compromising security, privacy, and integrity. The centralized repository that is currently in place made the majority of hacks possible. The sharing of sensitive data and authentication are essential stages in guaranteeing the security of applications associated with IoT. Blockchain and IoT are two widely used technologies, with IoT focusing on data collection via various devices and blockchain enabling data integrity. This paper introduces a novel blockchain-based framework to ensure the security and integrity aspects of IoT data. The proposed SecPrivPreserve framework ensures security through various phases including initialization, registration, data protection, authentication, data access control, validation, and data sharing and download. Diverse security mechanisms such as passwords (OTP), encryption, and hashing have been deployed in various phases to strengthen security merits confidentiality, privacy, and integrity. Since the SecPrivPreserve framework is simulated in a permissioned blockchain platform the merits and tamper-proof and non-repudiation are automatically considered. Moreover, data protection uses Chebyshev polynomials and interpolation. The presented framework has experimented with Fabric SDK. The experimental results of the proposed framework are compared with the BaseLine state-of-the-frameworks, The experimental analysis reveals that the proposed SecPrivPreserve approach achieved 34 Sec improvement in terms of responsiveness 94 Sec as computational time, encryption quality as 0.87 Sec and 0.82 Sec for detection rate.
Blockchain technology originated alongside Bitcoin as a novel method of conducting financial transactions. It has garnered significant attention from both industry and academia in recent years, emerging as a prominent area of research. It is a decentralized record-keeping system that holds transactional information. The scale of a blockchain network expands according to the growth in the number of nodes and transactions, resulting in issues related to storage capacity, data processing speed, and time delay. These issues have a direct impact on the scalability of a blockchain network. Currently, scalability is one of the prominent concerns in the field of blockchain technology and an active research area. This study conducts a comprehensive survey of the scalability challenges faced by blockchain technology in several sectors. It also examines potential solutions based on consensus mechanisms, smart contracts and directed acyclic graph (DAG). It is observed that the proposed scalability solutions target enhancing system throughput, reducing costs, and improving blockchain efficiency. Therefore, we examine, compare, and evaluate the literature using these specific criteria. Moreover, a survey of existing blockchain based survey papers is presented. A comparative analysis of these survey papers is presented along with their recency score, which is determined by the number of recent publications reviewed in a survey paper. By "recent," we mean the current year (or the publication year of a survey paper) and the three years prior to it. Additionally, this paper offers an elaborate discussion on the forthcoming open research challenges and applications of blockchain.
A Dutta, Nafiz Imtiaz Rafin, M. Ali Akber Dewan, Md. Golam Rabiul Alam
Blockchain is a ground-breaking technology that has changed how we manage and store protected data. It is a decentralized ledger that enables safe, open, and unchangeable record-keeping. It relies on a distributed network of nodes rather than a single central authority to check and verify transactions, guaranteeing that each entry is correct and unchangeable. Transactions in a blockchain network are grouped into blocks, which are then linked together in a chronological and immutable chain. Block size is a critical parameter in blockchain technology, which refers to the maximum size of each block in the chain that is not benchmarked yet. However, we cannot just change the block size of the blockchain. It is challenging and will create security issues. The Block size is crucial because it affects the number of transactions processed per second, the confirmation time, and overall network efficiency. The confirmation time should be faster to ensure stable earnings for the miners. Moreover, it needs help with broader applications due to high transaction fees and long verification times. We have proposed a reinforcement learning model named ROBB that can efficiently create a block considering the current network state and previous transactions. At first, the problem was converted into a reinforcement learning environment to solve using multiple reinforcement algorithms. We developed a blockchain simulator to replicate the network environment. To transform it into a reinforcement learning environment, we integrated it with OpenAI Gym. The simulator was trained by generating random transactions. Finally, we designed a reward function that enables the simulator to hold transactions and create blocks with the pending transactions when it determines that the environment is favourable. In the final results, ROBB successfully minimized the waiting time for transactions and utilized the blocks to their full potential. Additionally, it optimized the block space, building upon the findings of previous researchers. From the research we can see that our propsed models shows impressive results with 100% block utlization and 1.8s average waiting time while creating the least number of blocks.
Daniel Commey, Bin Mai, Sena Hounsinou, Garth V. Crosby
This paper reviews the role of blockchain technology in enhancing the security of Internet of Things (IoT) systems and maintaining data integrity. We address the increased vulnerabilities and broader attack surface resulting from the integration of blockchain and IoT. The review emphasizes the potential of technologies like zero-knowledge proofs (ZKP) and post-quantum cryptography (PQC) to mitigate these security challenges. Additionally, we explore how game theory, machine learning, and cyber deception strengthen the defense of blockchain-based IoT systems against various threats. The paper also identifies open research areas, emphasizing the need for continued exploration to advance these fields. An additional contribution of this study is introducing a conceptual framework incorporating these technologies, laying the groundwork for developing advanced security solutions within the blockchain-enhanced IoT ecosystem.