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The proliferation of Internet of Things (IoT) applications poses formidable challenges in managing data processing, privacy, and security. In response, technologies such as Fog Computing (FC), Blockchain (BC), and Federated Learning (FL) have emerged as promising solutions. Combining these technologies can broaden their scope, and impose novel challenges. This paper conducts a Systematic Literature Review (SLR) to investigate their integration within the IoT domain, systematically evaluating the current state-of-the-art by analyzing 40 papers against 38 extraction criteria, encompassing technical characteristics specific to FC, BC, FL, or their integration. The findings offer insights into the advantages, challenges, opportunities, and limitations of this integration, addressing data processing, privacy, and security concerns in IoT. By filling a research gap and directly examining FC, BC, and FL interoperability across architectural layers, this study contributes to knowledge expansion in the field. This paper proposes a novel framework for implementing FL and BC within FC environments for IoT applications, alongside a comprehensive synthesis of existing literature, distinguishing it from previous research efforts. Furthermore, it offers valuable insights into the current landscape, identifies research needs, and proposes future research directions. The framework and literature synthesis provided allow readers to access customized information on FC-BC-FL integration, aiding in designing and implementing robust IoT solutions.

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.

In modern cities, consumers with distributed energy resources (DERs) can trade energy by managing their consumption and supply. Blockchain is considered to provide technical support for establishing a distributed energy market, while the current mainstream blockchain technology cannot meet the requirement of efficiency and scalability under such a transaction scenario. In addition, the potential defaults of market players also hinder market implementation. Therefore, a reputation-based distributed energy trading mechanism and the corresponding blockchain consensus method considering reputation management are proposed in this paper. Firstly, a distributed reputation management mechanism is designed to systematically evaluate the user’s behavior in the market. Secondly, to address the limitations of traditional consensus methods in the distributed energy market distributed reputation control is introduced into the node model of blockchain, and a new energy blockchain consensus method named DPoR is proposed to solve the technical bottleneck under the distributed energy trading scenario. We also present a corresponding transaction mechanism to encourage market participants to maintain their reputations. Finally, the simulation results verify the effectiveness of the proposed transaction mechanism in this paper, and the presented blockchain consensus mechanism can meet the performance requirements under distributed energy trading scenarios in terms of high efficiency, low consumption, and openness.

The Metaverse platform offers 3D immersive experiences through virtual reality, artificial intelligence, and blockchain technologies. Blockchain-based Metaverse has garnered recent interest due to its decentralization, anonymity, and other security features. Integrating blockchain into Metaverse promotes the formation of a shared ecosystem and provides digital asset tracking, privacy protection, and security in both virtual and physical environments. This paper explores the role of blockchain in creating and managing the Metaverse platform. It is intended to provide a helpful reference for researchers and practitioners in the field of the blockchain-based Metaverse. The main topics covered include the concept and characteristics of the Metaverse; its different use cases, architectures, and technologies; Metaverse as a service provider; Metaverse management; Metaverse users and data; and blockchain-based Metaverse in terms of roles, technologies, applications, and challenges. In addition, recent advances in the blockchain-based Metaverse and challenges such as scalability, interoperability, and edge resource sharing will be discussed. The paper will conclude by highlighting open research issues and future directions, including improving immersion, scalability, security, and integration with existing systems.

Sixth-generation (6G) communication is emerging as a seamless and massive connection of almost all digital devices. Vehicles, which are extensively linked with human mobility, must keep up with a certain technological pace to maintain compatibility with the 6G era. 6G is also expected to potentially revolutionize Vehicle-to-Everything (V2X) communication. However, this modernization will surface several security challenges in the complex heterogeneous architecture of V2X communication in 6G. Similarly, the expansion of V2X is expected to introduce its own unconventional security risks and vulnerabilities. Therefore, the current paper aims to provide an overview of the security challenges associated with and solutions for V2X communication in the upcoming 6G era to visualize the future of this research domain. This paper discusses the architecture and standards utilized in 6G-enabled V2X communications and provisions a comprehensive analysis of V2X security in the Confidentiality, Integrity, Availability, Authentication, and Access Control (CIA3) domains. Through this process, we analyze the impact of the emerging technological concepts of Blockchain and Federated Learning (FL) in 6G-enabled V2X communication. Therefore, we propose a Blockchain-enabled FL-based generic security architecture for V2X communication in 6G networks. Ultimately, this review highlights the key lessons that have been learned and the future research directions in the domain of security of V2X communications in the 6G including Privacy in 3D Fog Computing, Privacy in Augmented Reality, Secure Software Defined Networking (SDN), Physical Layer Security in the THz Spectrum, SUMO (Simulation of Urban MObility), and Intrusion Detection using AI.

As the metaverse gains attraction, the importance of metaverse security research becomes increasingly evident. While there has been research on authenticating users in the metaverse, there is a notable gap in research concerning the authentication of specific spaces within the metaverse. This paper addresses this gap by proposing a novel user-centric blockchain-based authentication approach that incorporates space authentication. The proposed approach leverages blockchain smart contracts to authenticate users using cosine similarity metrics. A significant advantage of this approach its ability to establish user-centric authentication by seamlessly integrating metaverse and blockchain technologies, all without the need for a centralized authority. In this paper, we not only evaluate the security of our proposed approach but also conduct experiments to determine the cosine similarity threshold and assess its feasibility within a metaverse environment.

Understanding the prospective of blockchain technology and its uses in the healthcare sector is essential so that its considerable implementation can support the industry’s much-needed digitization. Furthermore, blockchain can provide answers to the issues in the healthcare industry today. Blockchain’s features like security, traceability, transparency, cost efficiency etc. can help bring supply chain transparency, health record management and prevent drug counterfeiting. Blockchain has emerged as a promising technology with great ability to bring changes to the healthcare sector. Therefore, this study aims to comprehend the current state of blockchain technology research in the healthcare supply chains. Further, it presents potential repercussions and the potential routes it may open for future research initiatives in this area. A systematic literature (SLR) process has been used and conducted in two stages. In the first stage, articles were identified through literature search and were subjected to keyword selection, database search and screening process. Finally, 124 papers were categorized through bibliographic coupling. A detailed investigation of these included papers was performed in the second stage with descriptive and content analysis. The results reveal that research related to blockchain applications or implementation is at a nascent stage. The publications in this area have been rising steadily over the past few years. When it comes to publishing in this field, India is the most productive nation while IEEE Access is the most productive journal. Applications for blockchain technology in healthcare include medical insurance, remote patient monitoring, medication supply chain management, electronic health records (EHRs), and more. The most popular use case is EHR management. The analysis further conveys that findings are less generalizable due to more theoretical or less empirically designed studies published in this domain. This study will help stakeholders, policymakers, researchers, and managers in taking strategic decisions regarding the adoption of the technology in the healthcare industry. This study is done concerning the blockchain’s use in the healthcare sector context, so other emerging technologies and sectors not taken must be considered while generalizing the results. This study is among the few up-to-date consolidated attempts to present a systematic literature review and bibliometric analysis for assessing blockchain technology’s potential in the healthcare sector. It provides an overview of the published work with implications and proposed cluster-wise future research directions.

In recent times, Learning Management Systems (LMS) have gained significant popularity, particularly due to the COVID-19 pandemic, offering improved effectiveness and efficiency. Within LMS, online exams have emerged as a critical tool for assessing students’ performance and understanding of course material, playing a vital role in determining their progression. Ensuring the reliability and transparency of online exam results is imperative. Any vulnerability, such as hacking, can adversely impact students’ grades. Conventional online exam systems often store data centrally in databases like MySQL, making them susceptible to unauthorized access and manipulation. This paper presents a blockchain-based framework to enable secure and peer-to-peer conduction and evaluation of academic exams. The framework uses hashing techniques to ensure data integrity and employs proof of stake mechanisms for enhanced security. Blockchain’s decentralized data storage and cryptographic hashing for each block make it effective in safeguarding data integrity. The paper demonstrates the use of blockchain for developing online exams, storing each question and answer directly on the blockchain. To achieve this, we have created a module that integrates with the Moodle learning management system. Through a comparative analysis with Moodle’s default centralized storage, our module modifies the exam result storage, ensuring secure and tamper-proof data storage on the blockchain. By leveraging the blockchain, exam data is reliably secured, maintaining integrity, and resisting manipulation. Our results show that data stored on the blockchain is entirely accurate, with no discrepancies compared to Moodle’s standard approach. The blockchain network provides a reliable and immutable platform, preventing unauthorized changes to student data. In conclusion, our blockchain-based framework offers a robust solution for enhancing the security and reliability of online exam results. By harnessing blockchain’s decentralized and tamper-proof nature, we ensure data integrity and transparency, providing a more trustworthy assessment of academic performance.

Malicious assaults and information leakage have grown in importance in practically every area of information and communication technology (ICT) in recent years. Enterprise ledger organization, preservation, security, and protection are all greatly aided by information security (IS). To maintain their positions in the market, industries must safeguard their data and other vital assets. The main goals of this paper’s systematic review, which covers the entire process of privacy protection and security, are to introduce cryptographic IS for Industry 5.0 (the Fifth Industrial Revolution) as a comprehensive solution that provides regulatory compliance and IS policies in addition to the industrial goals. The review covers the four main areas: 1) recognizing the need for frameworks to be developed for a secure Industry 5.0 lifecycle; 2) emphasizing security guidelines, procedures, and countermeasures for Industry 5.0; 3) applying control, access, and availability in real-time; and 4) proposing a futuristic architecture for industrial information security. Furthermore, the analysis of previously published state-of-the-art techniques is presented in this paper. These techniques survive with various limitations and challenges, including intercommunication exchange, fine-grained control access, and interconnectivity-related issues, which affect the adoption of an IS in industrial programs. At the end of this systematic review, we investigated a few open research problems and mentioned those that are involved in the design of cryptographic re-encryption enabled IS for future Industry 5.0 developments.

Supply chain as an industry has gone through four-fold changes in the last century. Born as a bare-bones structure in 1.0 it grew to incorporate some form of record preservation in 2.0 and then integrated communication between two entities in 3.0. Supply chain 4.0, the current one, has total global integration of multiple entities with the records digitised. But increasing entities and pipelines, means increasing complexities, overhead and soft spots. In this paper, a systematic literature review is done with the objective of analysing existing Supply Chain 4.0. The focus of the paper is the usage of blockchain technology in the electronic industry to provide a decentralised architecture. Several papers were compared on the basis of different schemas like the type of blockchain network used, platform deployed on, security of frameworks, representation of unique identity, testing authenticity, working implementation, cost of implementation, etc. The pros and cons of various privacy and security methodologies are also explored and discussed. The paper also discusses the open issues and challenges in the same area of interest. Finally, the paper outlines the future scope to be delved into as a part of the future research.

Despite the increasing reliance on the Internet of Things (IoT) as a basic infrastructure for future applications. Integrating blockchain technology with IoT extensively helps provide basic security requirements owing to the built-in security structure of the blockchain. Healthcare IoT applications are one of the industries that will be revolutionized by using IoT-blockchain technology. This review aims to provide an integrated understanding of blockchain IoT healthcare applications. The methodology of our paper is to review the literature from 2018 to 2023, paying more attention to research that intersects and integrates IoT, Blockchain, and healthcare applications. This review addresses IoT-based blockchain types and technologies, healthcare applications, sensors, hardware tools, application databases, programming languages, software tools, challenges and open issues, and solutions with their advantages and limitations. We then compared our work with existing works on common metrics. The study in this paper includes 14 blockchain IOT healthcare applications: remote patient monitoring, patient tracking, disease prediction, tracking COVID-19, image retrieval, security of medical records, smart telemedicine, securing the Internet of Medical Things, big data, blockchain and sensors, accurate medical decisions, health monitoring, tracking soldiers, and solar energy.

This paper introduces a novel dynamic spectrum sharing (DSS) scheme designed for cell-free massive MIMO (CF-mMIMO) networks. The motivation behind this work arises from the urgent need to enhance spectrum utilization in modern wireless communication systems. Traditional spectrum allocation methods often struggle to meet the diverse spectrum demands of different wireless operators. The proposed approach addresses these challenges by enabling the spectrum provider (SP) to flexibly allocate and sell its spectrum resources, empowering wireless virtual operators to acquire bandwidth efficiently based on their specific needs. In our framework, each wireless operator is represented by a CF-mMIMO network, characterized by an average spectral efficiency metric that quantifies the potential value of additional spectrum acquisition. Leveraging a Stackelberg game formulation, our DSS policy achieves an equilibrium point that optimally allocates bandwidths to operators and determines corresponding prices. This approach not only enhances spectrum utilization but also fosters fair competition among operators. A key innovation of our work lies in the utilization of blockchain technology, where all spectrum transactions are managed through a smart contract. This ensures transparency, integrity, and auditability throughout the spectrum trading process. The novel protocol facilitates seamless information exchange, orchestrates the Stackelberg game dynamics, and delivers conclusive outcomes to both the SP and the CF-mMIMO operators.

Supply chain management depends on a complex, interconnected network of suppliers, manufacturers, transportation companies, distributors and customers with the goal of predicting, monitoring and controlling operations and processes. Globalization has introduced fierce competition, forcing supply chains to innovate and enhance their performance and capabilities. Centralized management systems are prone to attacks, disruptions and malfunctions. A potential solution to these known issues is the adoption of blockchain technology. The blockchain offers an immutable ledger that allows for a trustless, decentralized system without reliance on third parties. It can provide new features, improve performance, advance network visibility and strengthen the four flows of a supply chain. To survive and compete on the global stage, supply chains must adopt emergent technologies to develop new business strategies. In this paper, a comprehensive survey of academic literature and research works relating to blockchain platforms for global supply chain management is presented. This survey will provide an overview of blockchain technology for supply chain management, summarize industry applications, highlight persistent challenges, and identify research opportunities to enhance the current state of research in the past six years. The contribution of this survey is to also provide a list of available blockchain solutions for global supply chain management and to elaborate on future advancements in the field. New solutions will be proposed and explained.

Particularly in the context of smart cities, remote sensing data (RSD) has emerged as one of the hottest study topics in information and communication technology (ICT) today. The development of machine learning (ML) and artificial intelligence (AI) has made it possible to solve a number of issues, including automation, control access, optimization, monitoring, and management. Simultaneously, there are significant issues with the design and development of the process hierarchy, including inadequate training records, centralized architecture, data privacy protection, and overall resource consumption restrictions. The development of Distributed Ledger Technology (DLT), on the other hand, provides a decentralized infrastructure that allows systems to eliminate centralized data-sharing procedures of smart cities while transferring from network node to network node, and third-party access control solves machine learning issues. To process an ideal data delivery mechanism for the smart cities analytical model, the paper employs Partial Swam Optimization (POS) in conjunction with a secure blockchain distributed consortium network. This work makes three contributions. Firstly, it offers a safe transmission method that combines blockchain and machine learning to optimize the path for reliable data delivery across secure channels. Second, neighborhood encryption sequences are carried out using NuCypher proxy re-encryption-enabled value encryption, a public key cryptographic approach that avoids cypher conversion. Third, Artificial Neural Networks (ANNs) can solve the data deliverance classification problem in smart cities by optimizing record management and preservation.

Ensuring robustness against adversarial attacks is imperative for Machine Learning (ML) systems within the critical infrastructures of the Industrial Internet of Things (IIoT). This paper addresses vulnerabilities in IIoT systems, particularly in distributed environments like Federated Learning (FL) by presenting a resilient framework - Secure Federated Learning (SFL) specifically designed to mitigate data and model poisoning, as well as Sybil attacks within these networks. Sybil attacks, involving the creation of multiple fake identities, and poisoning attacks significantly compromise the integrity and reliability of ML models in FL environments. Our SFL framework leverages a Digital Twin (DT) as a critical aggregation checkpoint to counteract data and model poisoning attacks in IIoT’s distributed settings. The DT serves as a protective mechanism during the model update aggregation phase, substantially enhancing the system’s resilience. To further secure IIoT infrastructures, SFL employs blockchain-based Non-Fungible Tokens (NFTs) to authenticate participant identities, effectively preventing Sybil attacks by ensuring traceability and accountability among distributed nodes. Experimental evaluation within IIoT scenarios demonstrates that SFL substantially enhances defensive capabilities, maintaining the integrity and robustness of model learning. Comparative results reveal that the SFL framework, when applied to IIoT federated environments, achieves a commendable 97% accuracy, outperforming conventional FL approaches. SFL also demonstrates a remarkable reduction in loss rate, recording just 0.07 compared to the 0.14 loss rate experienced by standard FL systems. These findings highlight the efficiency and applicability of the SFL framework in enhancing data security and traceability within the IIoT ecosystem.

This paper presents a unified multi-timescale control approach for a power system with distributed energy resources to achieve cyber-resilient operation. The proposed concept combines two cyber-resilient control methods: proactive and reactive methods. The proactive method uses a blockchain that ensures measurement and control data can be securely exchanged among grid assets and also derives control set points as a load-sharing supervisory control, with an embedded logic called chaincode. The proactive method ensures data integrity, but it inherits stochastic latency with significant standard deviation due to the nature of the distributed ledgers and security measures, leading to challenges in control. To overcome this trade-off, the reactive approach uses event-driven communication. For this approach, rather than communicating the complete data, a lightweight data packet is communicated in a peer-to-peer fashion. Therefore, it guarantees driving the system into a stable operation in case the proactive operation degrades with insufficient latency. To validate the concept, Hyperleger Fabric blockchain 2.2 is used to characterize the latency and is customized for an inverter control system in this study. Based on the use case, a stability analysis is presented to evaluate the impact of the variable delay and to identify the need for a reactive approach to mitigate the effects of a prolonged delay in the proactive method. A test bed with two hardware inverter prototypes and a custom blockchain programmed with the unified method is developed for validation. A set of hardware experimental results validates the methodology and demonstrates the inverter system operations achieving frequency recovery and load-sharing restoration based on the unified control method.

Searchable encryption is widely used in electronic health record systems because it enables users to search ciphertext data without decryption. However, the existing traditional searchable encryption schemes lack fine-grained access policies with wildcards in electronic health record systems. And they also do not consider the problem of hiding policies, as well as the problem of incomplete search results caused by cloud servers. In order to solve all the above problems, this paper proposes a blockchain-aided attribute-based searchable scheme with the properties of inner product predicate. In the proposed scheme, the attribute encryption mechanism implements fine-grained access policies with wildcards, which improves the data owner’s ability to control access authorization precisely. Introducing the inner product predicate not only achieves fully hidden access policies but also prevents the leakage of sensitive medical data. The immutability of the blockchain ensures the integrity of multi-keyword search results, guaranteeing reliable data sharing. Finally, the security proof and the performance evaluation are conducted to confirm the security and effectiveness of the proposed scheme.

Open-cry electronic auctions have revolutionized the landscape of high-value transactions for buying and selling goods. Online platforms such as eBay and Tradera have popularized these auctions due to their global accessibility and convenience. However, these centralized auctioning platforms rely on trust in a central entity to manage and control the processing of bids, e.g., the submission time and validity. The use of blockchain technologies for constructing decentralized systems has gained popularity for their versatility and useful properties toward decentralization. However, blockchain-based open-cry auctions, are sensitive to the order of transactions and deadlines which, in the absence of a governing party, need to be provided in the system design. In this paper, we identify the key properties for the development of decentralized open-cry auctioning systems, including verifiability, transaction immutability, ordering, and time synchronization. Three prominent blockchain platforms, namely, Ethereum, Hyperledger Fabric, and R3 Corda were analyzed in terms of their capabilities to ensure these properties for gap identification. We propose a solution design that addresses these key properties and presents a proof-of-concept (PoC) implementation of such design. Our PoC uses Hyperledger Fabric and mitigates the identified gaps related to the time synchronization of this system by utilizing an external component. During the chaincode execution, the creation and submission of bids initiate requests to the time service API. This API service retrieves trusted timestamps from NTP services to obtain accurate bid times. We then analyzed the system design and implementation in the context of the identified key properties. Lastly, we conducted a performance evaluation of the time service and the PoC system implementation in time-sensitive scenarios and assessed its overall performance.

The increased digitalization of society raises concerns regarding data protection and user privacy, and criticism on how the companies handle user data without being transparent and without providing adequate mechanisms for users to control how their own data is being processed or shared. To address this problem and open the way for a secure and efficient society, where the privacy of citizens is paramount, the identity concept and proof of identity mechanisms need to be redesigned from the ground up. In this paper we discuss how the emerging Web3 technologies like distributed ledger technology (DLT), blockchain, smart contracts, decentralized storage systems, and crypto wallets can be leveraged to design and implement a decentralized digital identity system based on decentralized identifiers (DID) and self-sovereign identities (SSI). Such a system puts the users in full control over their own data while also providing a solid backbone for building interoperable systems that are secure, scalable, and efficient. We propose different architectures for the decentralized identity infrastructure and storage layer, and also discuss the mapping of these architectures on cloud platforms. The main goal is to provide an architectural blueprint for a scalable, secure, privacy-preserving and trusted system.

Voice over Internet Protocol (VoIP) networks are vulnerable to caller-ID (caller-identification) spoofing attacks due to the open nature of Session Initiation Protocol (SIP) signaling. Caller-ID spoofing is a critical security threat in modern telecommunication systems, allowing attackers to impersonate legitimate callers and gain access to sensitive information. While these attacks pose a significant threat to the telecom and financial industries, the existing solutions are limited to only closed-circuit options for subscribers of the same service provider. In this paper, we present a novel blockchain-based solution to effectively prevent caller-ID spoofing attacks in real time. Our approach employs a low-latency consensus algorithm to manage and verify end-to-end the caller-ID information of Internet Service Providers (ISPs) and institutions. We propose a two-step verification process, in which the accuracy and integrity of Automatic Number Identification (ANI) information is verified at different stages of the call. The proposed solution initiates a renewal of the ISP registration on every caller-ID change, making it unaffected by unusual situations such as roaming, the use of an IP-PBX (Internet Protocol Private Branch Exchange), or the use of a VPN (Virtual Private Network). We also discuss the proposed solution’s feasibility and potential deployment issues, including its integration into existing RFC (Request for Comments) efforts and the necessary regulations for service providers to demonstrate compliance. Furthermore, we address future research directions, such as handling complex call scenarios such as call forwarding and teleconference calls. Our approach not only improves the security of telecommunication systems but also provides an efficient and scalable solution to prevent caller-ID spoofing attacks.

Education has become the most essential endeavor in our lives. There are many ways to learn, but only a few capture my interest. However, education has grown more interesting and attractive with the aid of technology. A fascinating step forward in education is merging the real and digital worlds through Virtual Reality (VR) and Augmented Reality (AR). The term used to denote the digital world is the “Metaverse.” Metaverse enables us to engage in virtual conversations with others by utilizing avatars that mirror ourselves. Using Metaverse technology, readers of certain books have discovered ways to study rather than focusing on their screens. Several advanced technologies, such as Blockchain, Big Data, Artificial Intelligence (AI), game design, Internet computing, and the Internet of Things (IoT), are integrated into the Metaverse, an innovative idea in social work. The integration of the Metaverse is expected to contribute significantly to the advancement of education. On the other hand, it is important to acknowledge that the development of educational Metaverse concepts is still in its early stages. Addressing issues related to the Metaverse’s objective in the classroom is critical. This research aims to conduct a comprehensive literature review on integrating the Metaverse in educational environments. We will start by giving a general overview of the Metaverse, its educational uses, and some background on the motivations behind its use. Moving on to the educational aspect, we examine the Metaverse, identifying its defining characteristics, including educational environments, Integrated technologies, and customized instructions. Following this, we suggested an essential structure for how teachers and students could connect in the Metaverse classroom. In addition, we investigate the most recent case studies of Metaverse in education, including investigations conducted by academic institutions and technology enterprises. Finally, this paper thoroughly analyzes the Metaverse in education, covering its current technological state, challenges, opportunities, prospects, and feature directions. The findings of our research indicate that the Metaverse is a valuable resource for educational purposes.

The concern and opposition to centralized management of user identities by third-party authorities have led to the emergence of Self-Sovereign Identity (SSI). With the help of blockchain, SSI effectively restore users’ control over their own identities, but privacy concerns due to blockchain transparency, coupled with the absence of accountability like Know Your Customer (KYC) and Anti-Money Laundering (AML), have cast uncertainties upon the viability of SSI. In this paper, we bridge this gap by introducing AASSI, a pioneering SSI protocol meticulously designed to balance the twin imperatives of privacy and accountability. Specifically, AASSI extends support for anonymity, self-derivation, fine-grained tracing and selective revocation. In the realm of anonymity and self-derivation, AASSI introduces redactable signatures, which empowers users to autonomously derive distinctive credentials for each user-service-provider interaction, effectively improving privacy protection and self-management capabilities. Pertaining to fine-grained tracing, the protocol employs a dual-tag system that facilitates tracing users’ real identities as well as a granular historical records of derived credentials. For selective revocation, AASSI leverages dynamic accumulators as a building block to enable the revocation of offending users. Ultimately, we provide functional comparison, which shows that AASSI has robust features, in particular, it supports novel self-derived features that further increase user control over their identity, and fine-grained tracking, which provides more flexibility for tracers. We demonstrate protocol efficiency through off-chain time-consuming comparison, which show that AASSI dramatically reduces the time overhead of credential verification. Moreover, We test the on-chain communication overhead and experimentally prove the feasibility of AASSI.

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.

Industrial Internet of Things (IIoT) applications consist of resource constrained interconnected devices that make them vulnerable to data leak and integrity violation challenges. The mobility, dynamism, and complex structure of the network further make this issue more challenging. To control the information flow in such environments, access control is critical to make collaboration and communication safe. To deal with these challenges, recent studies employ attribute-based access control on top of blockchain technology. However, the attribute-based access control frameworks suffer due to high computational overhead. In this paper, we propose an improved role-based access control framework using hyperledger blockchain to deal with IIoT requirements with less computational overhead making the information control process more efficient and real-time. The proposed framework leverages a layered architecture of chaincodes to implement the improved access control framework that handles the permission delegation and conflict management to deal with the dynamism of the IIoT network. The system uses a Policy Contract, Device Contract, and Access Contract to manage the workflow of the whole access control process. Each chaincode in the proposed framework is isolated in terms of its responsibilities to make the design low coupled. The integration of improved access control with blockchain enables the proposed framework to provide a highly scalable solution, tamper-proof, and flexible to manage conflicting scenarios. The proposed system outperforms the recent studies significantly in computational overhead in extensive simulation results. To verify the scalability and efficiency, the proposed is evaluated against a large number of concurrent virtual clients in simulation and statistical analysis proves that the proposed system is promising for further research in this domain.

This paper minimizes fake news, which has been a hot topic recently, using blockchain and artificial intelligence technology, and verifies it with blockchain. Also, using Artificial Intelligence technology, we want to create an algorithm that predicts how fake news will spread in the future. You can see various attempts at a news media platform based on Blockchain technology. However, the Blockchain news media platform is still not getting the market response we expected. It is questionable whether the reason is simply because it is a new technology, so it takes a long time to gain trust from consumers, whether consumers are not yet expecting an innovative news media platform, or whether the explosive growth of the Blockchain news media platform is difficult for other reasons. Research to answer this or direct research between Blockchain and media platforms is still lacking. In addition, the method of verifying fake news using artificial intelligence was verified, ANN, CBR, and MDA were changed, and the experiment was verified for progress. In addition, the use of 5-fold cross-validation as a comparative method was added as described above to more closely examine the possibility of its usefulness even in general situations. Also, through various fields of artificial intelligence and blockchain, verification work was done with blockchain, and fake news prediction was made using artificial intelligence. Various experiments were conducted and performance tests were performed, while the performance of about 5,000 TTPS was recorded through the third experiment. In the future, we think it is necessary to combine Artificial Intelligence and blockchain technology.

The process of controlling the flow of products and services from a company by encompassing each stage involved in transforming raw materials and parts into finished items, also delivering them to the final consumer is known as Supply Chain Management (SCM). The development of numerous smart city applications including smart grids, smart homes, smart supply chains, and smart healthcare has drawn attention to the Internet of Things (IoT). Nowadays, researchers are considering the smart healthcare system’s role as a Public Emergency Service (PES) to treat patients promptly. A distributed smart fire brigade system receives little attention like PES to save lives and property from catastrophic fire damage. The conventional PES methods are created using a centralized method that needs a lot of processing power and doesn’t offer timely services. The traditional systems developed for managing the supply chain have drawbacks like single-point failure issues, data integrity, transparency, and lack of trust. To alleviate the existing issues, in this paper, a Blockchain and IoT Enable Secure and Transparent Supply Chain Management framework is utilized for PES in the smart city environment. Further, two edge computing servers, like a service controller and an IoT controller are adapted. The local storage is handled by the service and IoT controller. Thus, it enhances the data processing speed of PES requests and PES fulfillment. The service controller utilizes the Optimal Queue Model to manage the PES requests based on the minimum service queue length. The efficiency of the network is improved by fine-tuning the parameters from the Queue model with the aid of a Revised Fitness-based Political Optimizer (RF-PO). The multi-objective constraints like queue length, utilization, actual arrival time, expected arrival time, and end-to-end delay are utilized for the efficient supply chain system. These stimulated results show the feasibility and effectiveness of the supply chain framework.

As the modern computing market experiences a surge in demand for efficient data-management solutions, challenges posed by centralized storage systems become more pronounced, especially with the proliferation of Internet of Things devices. Centralized storage, although cost-effective, faces issues of scalability, performance bottlenecks, and security vulnerabilities. With decentralized storage, data are distributed across nodes, offering redundancy, data availability, and enhanced security. Unfortunately, decentralized storage introduces its own challenges, such as complex data retrieval processes, potential inconsistencies in data versions, and difficulties in ensuring data privacy and integrity in a distributed setup. Effectively managing these challenges calls for innovative techniques. In response, this paper introduces a decentralized storage system that melds cloud-native concepts with blockchain technology. The proposed design delivers enhanced scalability, data security, and privacy. When operating on a containerized edge infrastructure, this storage system provides higher data-transfer speeds than the interplanetary file system. This research thus blends the advantages of cloud-native frameworks with the security mechanisms of blockchain, crafting a storage system that addresses the present-day challenges of data management in decentralized settings.

Cloud data warehouse (CDW) platforms have been offered by many cloud service providers to provide abundant storage and unlimited accessibility service to business users. Sensitive data warehouse (DW) data consisting of dimension and fact data is typically encrypted before it is outsourced to the cloud. However, the query over encrypted DW is not practically supported by any analytical query tools. The Searchable Encryption (SE) technique is palpable for supporting the keyword searches over the encrypted data. Although many SE schemes have introduced their own unique searching methods based on indexing structure on top of searchable encryption techniques, there are no schemes that support Boolean expression queries essential for the search conditions over the DW schema. In this paper, we propose a secure and verifiable searchable encryption scheme with the support of Boolean expressions for CDW. The technical construct of the proposed scheme is based on the combination of Partial Homomorphic Encryption (PHE), B+Tree and Inverted Index, and bitmapping functions to enable privacy-preserving SE with efficient search performance suitable for encrypted DW. To enhance the scalability without requiring a third party to support the verification of search results, we employed blockchain and smart contracts to automate authentication, search index retention, and trapdoor generation. For the evaluation, we conducted comparative experiments to show that our scheme is more proficient and effective than related works.

The current explosion in user traffic necessitates the placement of edge servers in proximity to the Internet of Things (IoT) devices, allowing computation tasks to be offloaded to edge servers. This strategy aims to minimize the average delay of traffic requests by enabling user/IoT devices to locally execute time-sensitive tasks or offload them to edge servers within the edge computing paradigm. This new paradigm will also allow to cache contents at edge servers, but considering such an increasing number of user requests and limited storage capability of edge servers, selection in edge caching decisions is challenging. In addition, while there is general consensus that this technology may provide a variety of benefits, there are serious questions about its security implications. This is because malicious users can manipulate the caching decisions of the edge servers by sending fake traffic requests, which reduces the caching efficiency of the resource-constrained edge servers. Driven by these issues, in this paper, we propose a blockchain-based content caching and computation strategy to validate the authenticity of cached content and thus prevent unauthorized requests from malicious users. Specifically, the Proof of Stake (PoS) consensus mechanism is presented to handle low computational work, validate the process of blocks, and manage the transactions between edge servers and legitimate users. Then, a Deep Q Network (DQN)-based solution is proposed to intelligently develop an effective content caching and computation strategy. According to performance evaluation, the proposed model significantly outperforms the conventional caching strategies. It improves the cache hit rate by up to 8.2% on average and reduces the response delay by up to 7.45% on average.

Applying blockchain to copyright protection is currently a popular research trend. However, the characteristics of blockchain open data also lead to the threat of copyright privacy leakage. Targeting at this issue, we design a secure digital copyright protection scheme based on blockchain and ring signature algorithm, which can achieve privacy protection of copyright information and improve the efficiency of data authentication. In this paper, we design a new ring signature scheme based on lattice. In this scheme, by using the lattice basis delegation algorithm, user’s public-private key pair is generated without expanding the dimension of lattice. Subsequently, according to the rejection sampling, message is signed by signer’s secret keys and other ring participants’ public keys. It can reduce scheme’s computational complexity. Finally, by combining ring signatures with blockchain technology, a new copyright protection scheme is proposed. More importantly, this scheme is proven to be secure with its correctness and anonymity. Meanwhile, it has less communication costs and shorter key sizes than those in other similar schemes. The results show that the proposed new scheme has good performance and efficiency.

The rapid development of the metaverse and generative Artificial Intelligence (GAI) has led to the emergence of AI-Generated Content (AIGC). Unlike real-world products, AIGCs are represented as digital files, thus vulnerable to plagiarism and leakage on the Internet. In addition, the trading of AIGCs in the virtual world is prone to various trust issues between the involved participants. For example, some customers may try to avoid the payment after receiving the desired AIGC products, or the content sellers refuse to grant the products after obtaining the license fee. Existing digital asset management (DAM) systems often rely on a trusted third-party authority to mitigate these issues. However, this might lead to centralization problems such as the single-point-of-failure (SPoF) when the third parties are under attacks or being malicious. In this paper, we propose MetaTrade, a blockchain-empowered DAM framework that is designed to tackle these urgent trust issues, offering secured AIGC trading and management in the trustless metaverse environment. MetaTrade eliminates the role of the trusted third party, without requiring trust assumptions among participants. Numerical results show that MetaTrade offers higher performance and lower trading cost compared to existing platforms, while security analysis reveals that the framework is resilient against plagiarism, SPoF, and trust-related attacks. To showcase the feasibility of the design, a decentralized application (DApp) has been built on top of MetaTrade as a marketplace for metaverse AIGCs.

Decentralized exchanges are becoming a competitive necessity for Web3 users. However, they cannot beat centralized exchanges in terms of user experience. Due to expensive gas fees, the blockchain cannot implement the classic order book model which is the pillar for traditional finance exchanges. Instead, most decentralized exchanges operate on the Automated Market Maker (AMM) model using a pre-defined mathematical pricing rule. AMM is more efficient to run on the blockchain but the biggest tradeoff is impermanent loss for liquidity providers and price slippage for traders. This remains the most noticeable drawback of today’s AMM. In this paper, we make the following contributions. First, we observe that if AMM is virtualized as an order book, its “order-book” shape is awkwardly different from that of a real-world order book. We argue that this is conceptually connected to the above weakness. We are thus motivated to design an AMM, the first of its kind, that mimics the price impact behaviors of real-world order books. Second, the proposed AMM, thanks to this property, significantly outperforms the state-of-the-art AMM in impermanent loss. Interestingly, our AMM can even result in impermanent gain. We are also better for large orders where price slippage is a concern. Third, another feature is that, while today’s AMM typically requires a fixed inventory ratio for the liquidity pool, the new AMM allows this ratio to vary, giving liquidity providers flexible options for joining or exiting the pool. All these advantages are offered without losing desirable properties of an AMM regarding split-order exploitation, arbitrage risks, and liquidity continuity. Our findings are validated by theoretical analysis with mathematical proofs and, also, experimental evaluation which was comprehensively conducted using two real-world datasets and a synthetic dataset representing different market scenarios. Our research is the first in the literature on AMM design that factors in statistical properties from the order book model.

Wireless body area networks ( $WBAN$ ) are essential components of intelligent healthcare monitoring techniques. Especially, when the number and datatype in $WBAN$ increases. In $WBAN$ , secure multidimensional data aggregation received a lot of attention. However, the related schemes consume more computational and communication overhead to encrypt/decrypt the multidimensional health reports. In this paper, a blockchain-assisted scalable and secure multidimensional data aggregation scheme is introduced for fog-based $WBAN$ . The multidimensional health data are efficiently generated, encrypted, and decrypted by using the Paillier cryptosystem. Further, the batch verification method is used to achieve efficient authentication. The proposed system offers significant security attributes with less computation and communication overhead in comparison with competing systems. Further, it supports statistical analyses such as summation and variance to analyze the received health report.

The driving experience in fifth-generation (5G)-assisted vehicular fog computing systems has improved thanks to recent advancements in intelligent transportation. However, in the present vehicular system setup, the phenomenon of providing low computation overhead with massive serving capability is crucial. In the existing scenario, the computational complexity rises when an authenticated driver travels from one roadside unit (RSU) area to another RSU region and must undergo re-authentication by the existing RSU. In this paper, an efficient blockchain-based pseudonym authentication scheme to address these issues and avoiding using RSU for 5G-assisted vehicular fog computing. The pseudonym identity generated for each vehicles and fog servers in order to exchange information about the road environment. The proposed scheme avoids re-authentication by the future fog server by utilising bilinear pairing of points on the elliptic curve and utilising blockchain technology without the need for a trusted authority. For fog computing, fog server obtains the verification key to authenticate the messages sent from vehicles for supporting revocation. The security analysis part of this work shows that the proposed scheme is not only satisfy requirements of security and privacy, but also resistance security attacks. Finally, the evaluation of the proposed scheme’s performance shows that it is more efficient than existing schemes with regards to computation cost, verification speed, and energy consumption.

In the rapidly evolving realm of the Industrial Internet of Things (IIoT), securing shop floor operations, especially in audit processes, is of critical importance. This paper confronts the challenge of ensuring data integrity and trust in IIoT systems by leveraging the capabilities of blockchain technology. The unique characteristics of blockchain, such as its immutable and decentralized ledger, establish a solid and transparent foundation for verifying shop floor transactions and activities. We introduce a privacy-centric approach, meticulously designed to comply with stringent data privacy regulations. This method allows auditors to authenticate both IIoT data and devices, ensuring confidentiality and adhering to regulatory standards. Our practical implementation strategy, tailored for shop floor environments, not only enhances the security of device and data integrity but also showcases robustness against specific adversarial threats, including network intrusion, data tampering, and unauthorized access. The findings indicate that our approach not only strengthens security protocols but also integrates effortlessly with existing IIoT infrastructures. It presents an efficient, scalable solution that elevates the safety and reliability of IIoT ecosystems, making it a significant step forward in the quest for secure and compliant industrial operations.

In the rapidly evolving realm of cloud computing security, this paper introduces an innovative solution to address persistent challenges. The proliferation of cloud technology has brought forth heightened concerns regarding data security, necessitating novel approaches to safeguarding sensitive information. The issue centers on the vulnerability of cloud-stored data, usually necessitating enhanced encryption and key management strategies. Traditional methods usually fall short in mitigating risks associated with compromised encryption keys and centralized key storage. To combat these challenges, our proposed solution encompasses a two-phase approach. In the first phase, dynamic Advanced Encryption Standard (AES) keys are generated, ensuring each file’s encryption with a unique and ever-changing key. This approach significantly enhances file-level security, curtailing an attacker’s ability to decrypt multiple files even if a key is compromised. The second phase introduces blockchain technology, where keys are securely stored with accompanying metadata, bolstering security and data integrity. Elliptic Curve Cryptography (ECC) public key encryption enhances security during transmission and storage, while also facilitating secure file sharing. In conclusion, this comprehensive approach enhances cloud security, providing robust encryption, decentralized key management, and protection against unauthorized access. Its scalability and adaptability make it a valuable asset in contemporary cloud security paradigms, assuring users of data security in the cloud.

Decentralized finance (DeFi) offers a range of financial instruments and services that leverage the capabilities of web3 technology. Maker protocol, which enables users to obtain loans backed by cryptocurrencies, is one of them. Unlike traditional banks, Maker’s data is transparently recorded on the Ethereum blockchain. In this research paper, we focus on analyzing the lending aspect of Maker from a traditional finance perspective. To achieve this, we create a unique dataset with loan portfolios from the MakerDAO project, making it the first dataset of its kind in the DeFi field. This publicly available dataset contains essential financial characteristics related to borrowing, including balance, loss given default, annual equivalent rate, and probability of default. Additionally, we develop a specialized mathematical model tailored specifically to this project. This model allows us to estimate the probability of default by considering the presence of crypto-collateral and utilizing Brownian motion passage levels. The results of this study provide valuable insights into lending practices in DeFi projects. They also help bridge the gap between traditional finance and blockchain-based financial services.

perceptron (MLP). We use feature vectors from the Opcodes and CFG for the machine learning (ML) model training. The existing ML-based approaches for analyzing the smart contract code are constrained by the vulnerability detection space, significantly varying Solidity versions, and no unified approach to verify against the ground truth. The primary contributions in this paper are 1) a standardized pre-processing method for smart contract training data, 2) introducing bugs to create a balanced dataset of flawed files across Solidity versions using AST, and 3) standardizing vulnerability identification using the Smart Contract Weakness Classification (SWC) registry. The ML models employed for benchmarking the proposed MLP, and a multi-input model combining MLP and Long short-term memory (LSTM) in our study are Random forest (RF), XGBoost (XGB), Support vector machine (SVM). The performance evaluation on real-time smart contracts deployed on the Ethereum Blockchain show an accuracy of up to 91% using MLP with the lowest average False Positive Rate (FPR) among all tools and models, measuring at 0.0125.

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 makes heavy use of cryptographic hashing to achieve integrity and consensus in a peer-to-peer network, but hashing causes some inefficiencies. For example, blockchain stores data with their hash digest as a key in the database, so the blockchain always reads and writes data in a random order. This can affect blockchain performance, especially for account-based blockchains such as Ethereum, which must maintain a huge, hash-based data structure for accounts, called the state trie. Also, Proof-of-Work (PoW) consensus algorithm requires the miners to find a nonce that makes the block hash lower than a difficulty threshold, but ASICs with parallel hashing have made PoW use a large dataset such as the Ethash DAG for memory-hardness and ASIC-resistance. Unfortunately, verification of the nonce is not easy for many light clients, which cannot deal with the overhead caused by the dataset. This paper proposes a novel PoW mining algorithm named Trie-Hashimoto to address these issues. Trie-Hashimoto adds a nonce field in a state trie node. It then makes the miners find a nonce of every newly-created trie node for a new block such that each node has a hash digest whose prefix is equal to the block number. This can accelerate the database performance by storing the trie nodes in a sequential order. The way for Trie-Hashimoto to achieve memory-hardness is also different. It uses the block headers that any client must maintain, obviating a separate dataset. Furthermore, it allows partial verification using a few Merkle proofs of accounts, so that a client with minimal resources or even a smart contract in another interoperable blockchain can verify a block with a high probability. Finally, Trie-Hashimoto discourages big mining pools by increasing the network overhead among the miners. Our experiment on the Geth client with 500K blocks and 100M accounts shows that Trie-Hashimoto improves the transaction execution time tangibly, reducing the full synchronization time by half. It also shows that Trie-Hashimoto has enough memory-hardness as Ethash. Lastly, a Trie-Hashimoto mining pool should exchange messages highly frequently, proportional to the total number of miners.

The development of smart vehicles has been a major focus of the automotive industry in recent years. Smart vehicles, equipped with advanced sensors and communication technologies, represent a transformative paradigm in modern transportation systems. Some of the challenges associated with the introduction of smart vehicles include developing reliable sensors, creating robust communication networks, and ensuring the security of vehicle systems. This paper proposes a Blockchain-based framework for accident prevention on the Internet of Vehicles, where vehicles monitor the state of the route and transmit information about hazardous situations to the Blockchain network. Once the event is confirmed, warnings are sent to all vehicles, and their speed is automatically reduced to avoid accidents. The tests in a 3D graphical simulator, combined with Hyperledger Besu technology for the creation of the Blockchain network, demonstrated both horizontal and vertical scalability, validating the potential of this framework for real-world integration. Moreover, it presents a fast reaction to anomalous situations on a route compared to human reactions under similar circumstances.

Practical Byzantine Fault Tolerance (PBFT), a classic consensus algorithm in blockchain technology, is extensively used in consortium blockchain networks. However, it is challenged by issues such as low consensus efficiency, poor scalability, inability to guarantee throughput with large-scale node access, and complex communication processes. To solve these problems, this paper proposes an improved PBFT consensus mechanism based on credit scoring and aggregated signatures, i.e., the CA-PBFT algorithm. First, the algorithm designs the node credit scoring mechanism, adds the coordination node in the original algorithm model, stipulates the node state and functional limitations, and realizes the dynamic joining and exiting of the nodes, to solve the low efficiency of the PBFT algorithm during the consensus process and the problem of not supporting the dynamic joining and exiting of the nodes; at the same time, the signature scheme based on the BLS aggregated signature is designed, which reduces the length of the signature and simplifies the signing process, to solve the problem of the node’s signature taking up too much space during the consensus process, which affects the efficiency of the signature validation as well as the efficiency of the signature construction. Experimental results show that this consensus mechanism enables an efficient, secure, and scalable consensus process with low resource and computational costs.

As reliance on disruptive applications based on Artificial Intelligence (AI) and Blockchain grows, the need for secure and trustworthy solutions becomes ever more critical. Whereas much research has been conducted on AI and Blockchain, there is a shortage of comprehensive studies examining their integration from a security perspective. Hence, this survey addresses such a gap and provides insights for policymakers, researchers, and practitioners exploiting AI and Blockchain’s evolving integration. Specifically, this paper analyzes the potential benefits of the integration of AI and Blockchain as well as the related security concerns, identifying possible mitigation strategies, suggesting regulatory measures, and describing the impact it has on public trust.