Abstract

The Internet of Things (IoT) leads to the next phase of human interaction with technology. With the help of the IoT, physical objects can be given the ability to generate, receive, and seamlessly trade data with one another. The IoT includes a wide variety of applications, each of which focuses on automating a specific task and works to give inanimate objects the ability to act independently of human intervention. The currently available and upcoming IoT applications hold a great deal of promise for enhancing the level of convenience, productivity, and automation enjoyed by users. High levels of security, privacy, authentication, and the ability to recover from attacks are required for the implementation of such a world in a manner that is constantly expanding. In this light, it is necessary to make the necessary adjustments to the architecture of IoT applications to accomplish end-to-end security in IoT environments. In this article, a comprehensive review of the security-related challenges and potential sources of danger posed by IoT applications is provided. Following a discussion of security concerns, a variety of new and established technologies that are focused on achieving a high degree of trust in the applications of the IoT are covered. Machine learning, fog computing, edge computing, and blockchain are just a few of the technologies that help the IoT provide greater security.

Introduction

The Internet of Things (IoT) is one of the disruptive technologies of the 21st century that has revolutionized every business dimension across the globe. The Internet has become an essential component in daily activities such as e-commerce, e-learning, e-conferences, etc. According to [1], the number of IoT devices deployed may exceed 21.3 billion by 2022. Intelligent interfaces connect IoT devices in order to collaborate, gather, communicate, and store data. Deploying IoT devices enhances business productivity by optimizing operational procedures and maximizing the utilization of available resources. IoT brings innovation in the way things are monitored and managed remotely with the help of real-time data acquired from the sensors. With the unrestrained volumes of data generated by billions of connected devices, storage, management, and security are arduous. Security aspects such as authentication, authorization, privacy, confidentiality, availability, and integrity form the basis for information exchange in a trusted environment. Authentication is the process of identifying the genuineness of an entity. The authorization process allows only authenticated users to access the resources. The protection of privacy prevents hackers from accessing the user’s private information. Data confidentiality is an outcome of authentication and authorization. It prevents sensitive data from being reclaimed and exploited. A device’s availability confirms that IoT devices and services are resilient to attacks and are accessible all the time. Data integrity is the process of providing a tamper-proof platform for information communication, exchange, and storage.

Conclusion and future directions

In this paper, the methods that are currently available in the literature are discussed, and this paper also presents the methods that are currently available. The subsequent step is an in-depth discussion of the numerous security risks and the importance of threat modeling. The subsequent topic is a discussion of the various IoT applications’ necessary security precautions. It reviews the prior research on the numerous security issues and the solutions put forth by various researchers. The holes that were found while conducting this literature review served as inspiration for the current research work.

7.1. Research challenges
The billions of IoT devices deployed across the globe collect personal and sensitive data and exchange it with other networks using intelligent interfaces. Providing device authentication, authorization, data privacy, and security in such an un trusted environment is a challenge. Centralized trusted infrastructure cannot scale to the dynamic and ever intensifying traffic and, thus, leading to bottlenecks in the network. Distributed authentication can scale to the increasing demands of the IoT networks, but requires distributed trusted systems. The majority of the work in the IoT security domain focuses on embracing the security mechanisms of WSNs and conventional Internet-based applications. However, these mechanisms are far from being implemented in real-time scenarios due to the specific challenges of IoT, such as

Abstract

This study aims to investigate the influence of blockchain and artificial intelligence on the audit quality of firms from Turkey. Primary data from 300 respondents are collected through random sampling to attain the study’s objectives. PLS-SEM is used to investigate the relationship between exogenous and endogenous variables. Our findings show that blockchain technologies and artificial intelligence (AI) utilization in their financial system positively impact audit quality by assisting in the audit process and the detection of fraud, which also improves financial reporting. Blockchain and Artificial Intelligence in the financial system create confidence for investors, stakeholders, and legislators. Moreover, this study advocated significant implications for investors, government, firms, and policymakers. Investors can make investment decisions based on the accuracy of the financial accounts; the government and policymakers can improve the governance mechanism by using the study’s findings.

Introduction

Audits play a vital role in ensuring compliance with laws, regulations, and accounting standards. Companies are subject to various regulatory requirements and must adhere to accounting principles and reporting frameworks [1]. High-quality audits provide independent assurance that these compliance requirements are met, reducing the risk of penalties, legal consequences, or reputational damage [2]. Quality audits contribute to effective corporate governance by holding management accountable and independently assessing the company’s financial reporting [3]. By examining internal controls and risk management processes, audits help identify weaknesses and areas for improvement, enhancing organizational transparency and accountability. Audits protect the interests of various stakeholders, including employees, customers, suppliers, and lenders [4]. By assuring the accuracy and reliability of financial statements, audits help safeguard the investments, jobs, and contractual relationships associated with a company. This promotes trust and stability in the business environment.

Auditing quality is an interesting research problem and is influenced by many factors such as the blockchain, Artificial Intelligence, professional skepticism, auditor independence, audit firm size, regulatory environment, technological advancements, and the adoption of innovative audit tools. Professional skepticism plays a pivotal role in audit quality [5]. Auditor independence, ensuring auditors maintain an unbiased stance, is fundamental for objective and reliable audit outcomes [6]. The audit firm size has been identified as a factor, with larger firms often having more resources and expertise to deliver higher-quality audits [7]. The regulatory environment and oversight mechanisms significantly impact audit quality, as stringent regulations and effective oversight contribute to a more robust auditing process [8]. Technological advancements and the adoption of innovative audit tools have emerged as crucial factors shaping audit quality in the contemporary business landscape [9]. Understanding the intricate interplay of these factors is essential for advancing research and enhancing the overall quality and effectiveness of auditing practices. Therefore, these factors are widely discussed in the previous literature in different demographic contexts but lack the investigation on Artificial Intelligence (AI) and blockchain technology in relation to audit quality in the modern world.

Conclusion and recommendations

Our findings show that AI improves audit quality by providing assistance and timely fraud detection. AI’s data analysis capabilities, ability to identify complex fraud patterns, and real-time monitoring contribute to more effective and efficient audits. As AI advances, it holds tremendous potential to enhance auditing practices’ overall quality and effectiveness. This study provides specific insights into the implications of these technologies within Turkey and also other varieties of implications for investors, management, stakeholders, and policymakers. The study assessed the level of adoption and readiness of Turkish auditing firms to embrace blockchain and AI technologies. It identified the factors influencing the adoption process, including organizational culture, infrastructure, resources, and regulatory environment. Understanding the current state of technology adoption in Turkey sheds light on the potential implications for audit quality.

The implications of blockchain and AI on fraud detection and risk assessment practices in Turkish audits can be explored. The study assessed how these technologies improve the ability to detect and prevent fraud, including identifying unusual patterns, real-time monitoring of transactions, and using predictive analytics. It can also examine the impact of risk assessment methodologies and the ability to assess risks accurately. The investor can invest by seeing the audit quality of the firms within Turkey to protect their investment, and the government can make the legislation in the weakness and delayed audit without enjoying the blockchain technologies and the other factors. Future research should be conducted on the efficiency of blockchain technology that is effective in the accounting system and preparation of the financial system that makes it easier for the technologies to improve the audit quality. Some more Blockchain units should be included in further research. Due to the limitation, we included one economy in our investigation; future research should include more than one and compare each economy, the use, and the efficiency of the artificial intelligence system.

Abstract

In recent times, the energy calibration methods are universally expanding with the goal of effectuating, reliably operating, and managing the utility system. The growing demand for power in the current environment has necessitated the mandatory installation of energy meters, as well as the development of new methods for calibrating meter readings and governing the effective use of energy resources. AMR (Automatic Meter Reading system) is one such modernization. This employs analogue or digital energy meters with the assistance of smart meters. Currently, energy scaling is done by hand, which is a timeconsuming process in the world of day-to-day networking demand and also requires skilled labour. The concept of AMR Systems is to overcome complexities in the rapidly growing field of energy management. This article proposes a smart energy meter based on IoT to detect the power theft. The proposed model consists of Arduino UNO, ESP8266, AC713 current sensors, and so on. The AC713 senses current usage with the help of the ESP32, which is then passed to the IoT platform. Though AMR is a very effective method, it costs the proxy of existing energy meters by SEM (Smart energy meters), which is highly inefficient. As a result, the proposed method focuses on detecting the power theft caused by public tampering. The proposed model is programmed by using a BLYNK software and simulated in PROTEUS software. The proposed system is then validated by using the simulated results.

INTRODUCTION

People are currently exposed to a medium that provides extreme ultimatums. The major crisis in today’s society is the energy crisis. The proposed solution provides an appropriate solution to control this issue. To deal with this, various methods are now available. One of these methods is to reduce domestic or household power consumption. The traditional method of meter reading requires a large number of hired hands to visit the habitat in person and take readings offline from the meter by checking each one individually. This procedure necessitates two-way cooperation as it is necessary for an authority to take readings in a house only when an individual is present in the house in order to avoid insecurities. This causes a lag in the private working lives of ordinary people because they must be present in person during this procedure. Furthermore, it is a laborious procedure that leads to chaos when a hired-hand is mistaken for any criminal activities. “Monitoring of Energy Tampering using IoT” is a novel application that has been developed to control power tampering from anywhere in the world. This system has been modernized so that the data is updated every 10 to 12 seconds. This system is fundamentally designed to reduce power theft, which contributes to the reduction of commercial losses; direct tampering can be reduced by using this system. The proposed solution is cost-effective and provides significant assistance to the electricity authority. It is also a time-saving procedure for both authorities and general public.

CONCLUSION

In the digital age, the proposed solution focuses on the IoT’s connection and associating factor. In this proposed design, an IoT and Microcontroller-based meter reading system is framed to continuously govern the scale of power and detect electricity tampering and notify the appropriate authority. The design’s goals were met when the customer could access the energy meter from anywhere. The display of energy consumption units is shown in LCD displays. The benefits of SEM are that it saves time and eliminates the need to wait for customers to pay their bills. This enables energy providers to engage in activities against lawbreakers.

Abstract

This article aims to discuss the consensus mechanism of software-defined blockchain in the Internet of Things, analyze the characteristics of the traditional consensus mechanism algorithms, on the basis of comparing the advantages of each model, the traditional consensus mechanism algorithm is improved. Later, a supervisable consensus scheme based on improved DPOS-PBFT (Delegated proof of stake-Practical Byzantine Fault Tolerance) was proposed. In the context of the development of the Internet of Things technology, the decentralized distributed computing paradigm is used to improve the blockchain smart contract technology, and the DPOS blockchain consensus mechanism is optimized based on the DPOS protocol of the credit model. In addition, through the dynamic grouping algorithm of credibility, the research ranks the credit level of the consensus nodes of the blockchain network, thus further realizing the supervision of the Internet of Things system. The results of the case analysis show that the success rate of the mechanism algorithm can still be maintained at about 97% after 3000 user requests, the maximum delay remains below 8s after 3000 user requests, the minimum delay is always around 3s, the average delay is 2.38s, the overall performance of the algorithm is superior. It can ensure the final consistency of data transmission of each node in the Internet of Things, the research on the blockchain consensus mechanism in the Internet of Things has practical reference value.

Introduction

With the development of physical network technology, Bitcoin [1] As a new encrypted digital currency, it began to be used in the field of financial security and widely used in the supply chain, as the underlying technology to realize Bitcoin virtualization, Blockchain technology has begun to attract people’s attention. The essence of blockchain is a decentralized distributed database, as an emerging technology, Blockchain provides users with a reliable exchange trading platform with its own advantages such as autonomy, synchronicity, and anonymity, provide data integrity to ensure the authenticity of content and user transparency. In the budding period of the development of blockchain [[2], [3], [4]], as the bottom layer of Bitcoin, the application of blockchain is only limited to the use of mathematical methods to calculate and maintain the recorded data of the distributed ledger that will not be tampered with. With the continuous development of blockchain technology, it began to be gradually applied to stocks and bonds in the financial field. In transactions, people introduce “smart contracts” through programs and algorithms, apply blockchain technology to ensure the integrity and reliability of financial transactions. In the current stage of development, Blockchain technology has entered a period of rapid development, the development of technologies such as big data [5] and artificial intelligence [6] has brought about changes in Internet technology, the IoT solution of the autonomous self-organizing network has gradually penetrated into all aspects of social life. The connection between the Internet of Things and advanced technologies such as big data and artificial intelligence is constantly deepening.

Conclusion

With the development of the Internet of Things, the emergence of many decentralized P2P self-organizing network trading platforms makes blockchain technology a hot topic of research quickly, traditional distributed consensus algorithms have problems such as network delay and transmission errors, in order to solve these problems, this research proposes an improved DPOS-PBFT supervisable consensus mechanism based on the traditional consensus mechanism algorithm, and compare the performance with traditional consensus algorithms such as Raft, POW, POS, DPOS, PBFT, etc., the results of the case analysis show that the success rate of the mechanism algorithm can still be maintained at about 97% after 3000 user requests, the maximum delay remains below 8s after 3000 user requests, the minimum delay is always around 3s, the average delay is 2.38s, the overall performance of the algorithm is superior. However, the research still has some shortcomings. First, this research did not consider the issue of secure multi-party computing, in the distributed network to solve the collaborative computing of users who do not trust each other, this problem should be taken into consideration, therefore, secure multi-party computing can be integrated with the consensus mechanism in the future. Second, the number of specific blockchain nodes in the Ethereum environment varies according to the type of application, in the future, different numbers of attack nodes can be added to the Ethereum network for testing.

Abstract

Nowadays, creating a blockchain-based system for supply chain tracing is a complex task. This paper defines a model, a graphical domain specific language, and a set of tools aimed at helping supply chain domain experts to create blockchain based tracing systems for their supply chains. Starting from a graphical representation of the supply chain, the solidity smart contracts implementing the related tracing system are automatically generated by our framework. Small interventions of programmers are required to customize and finalize such smart contracts. A set of web based interfaces to interact with such smart contracts are also automatically generated. We are confident that our results will increase blockchain usage for supply chain traceability thanks to the automatic process of smart contract generation.

Introduction

A Supply Chain (SC1) has been defined in [1] as an organizations network involved in different processes and activities with the aim of producing value (products or services) at the benefit of the ultimate consumer. Focusing on the product/service, an SC represents a sequence of (even complex) operations which transform the initial assets into intermediate products/services and then into the final one.

In order to give a more precise definition of an SC, it is necessary to understand which aspects of the products/services and which operations are under analysis, the type of process represented, and the actors operating in the network. Regardless of the specific process represented by the SC, having the capability of automatically tracing and controlling the actions performed by the actors of the SC is of paramount importance to obtain an effective and efficient process. Auditability is a fundamental feature of such a tracing system, assuring that the records tracing the actions that have been performed on the SC assets must be always available and that they cannot be deleted or altered.

Supply Chain Management (SCM) systems are software systems that allow to follow and record the execution of the steps of the process represented by a given SC [2], [3]. A number of SCM system implementations, both from academy and industry, are currently available.234 A commonly used approach to have auditable SCM systems is to implement them over blockchain infrastructures.

A number of blockchain-based solutions tailored for SCs [4], [5], [6], [7] are already available but, according to the researchers proposing them, such solutions are still focused on a specific scenario and very difficult to be generalized. Consequently, to promote the usage of blockchain technology for SC tracing and with the aim to make the SCM systems development easier and usable by supply chain domain experts, who are not necessarily distributed ledger technology experts as well, we propose the *-chain framework.

Conclusion and future work

We presented *-chain, a framework defining a model, a DSL, and a set of tools for helping supply chain domain experts in designing and developing their supply chain Management Systems on top of blockchain technology. Our framework allows domain experts to easily represent the main types of supply chains through a simple and user-friendly graphical interface, and – once designed – to translate such supply chain scheme into: (i) a set of smart contracts skeletons implementing the related supply chain Management System, and (ii) two web interfaces for operating on such management system: one for the supply chain administrator, and the other for the supply chain participants. These interfaces allow supply chain administrators to register the participants to their Supply Chain Management systems assigning them roles and rights, and supply chain participants to the register the operations they executed on assets according to the designed supply chain and to the required roles.

We validated our framework, by using it to represent a well-known supply chain use case: the soybean traceability study case [7]. We built the corresponding model, adding more detail to the original schema, introducing role-based authorization controls and also other constraints on operations. We used our framework to translate the supply chain schema into solidity code, and to produce the supply chain Administrator and Participants interfaces.

Abstract

     This paper surveys the published work on how blockchain technology will impact accounting in general, but AI-enabled auditing specifically. The purpose is to investigate how blockchain technology can improve transparency and trust in accounting practice and how professionals can use blockchain data to improve decision-making, based on the qualities of immutability, append-only, shared, verified, and agreed-upon (i.e., consensus-driven) blockchain data. The multi-party validation of blockchain protocols adds real-time trusted data for the AI systems used by auditors to improve assurance and efficiency. This review summarizes four themes emerging from the literature focusing on how blockchain technology has changed record-keeping in accounting: event approach to accounting; real-time accounting; triple entry-accounting and continuous auditing. The research interprets the findings using agency theory and stakeholder theory to advance how using blockchain to mitigate information asymmetry and improve stakeholder collaborations is understood. The investigation also summarizes the challenges and clarifies organizations’ reasons to be cautious about adopting blockchain. Lastly, the study suggests that future researchers use this study in two ways that enrich blockchain literature: first, to apply the themes and answer the questions identified within this review to improve the business methods of practitioners and policymakers; and second, to encourage stakeholders such as practitioners, system designers/developers, and policymakers to collaborate in designing blockchain ecosystems that suit accounting and auditing as they transform digitally.

Introduction

     Making companies’ systems digital has enabled them to adopt new technological tools to simplify business processes and transform business models to innovate their operations (Gomber et al., 2018) because they can increasingly access advanced computing power and large databases (de Sousa et al., 2019). Today, the world’s most valuable businesses are Internet-driven and platform-based (Iansiti and Lakhani, 2017). Academics, social media, industries, and governments spend much time attending to the digital forms of technology: blockchain, artificial intelligence (AI), big data, the Internet of things (loT), and cloud computing. These innovations change organizations and individuals greatly (Benlian et al., 2018), with blockchain specifically providing the foundation for what Tapscott and Euchner (2019) call an Internet of value that will fundamentally reshape society and its business. Blockchain, now regarded to be the fifth pillar of the IT revolution (Thakkar, 2019) is expected to become the foundational technology as the next-generation Internet (Iansiti and Lakhani, 2017, Shermin, 2017). Since Nakamoto (2008) set the groundwork for what would become blockchain technology in 2008, the banking, financial, insurance, education, health care, and government sectors have been using blockchain technology to the extent that 10 % of the global GDP will be recorded and stored on blockchain by 2027 (World Economic Forum, 2015). PricewaterhouseCoopers (PwC) (2020) estimates blockchain could boost global GDP by 1.76 trillion US dollars by 2030. Deloitte’s, 2020 global blockchain survey indicates that organizations are more committed than ever to implementing blockchain in their business (Deloitte, 2020). With blockchain’s growing maturity, innovators are discovering new opportunities to create value and enhance trust and resilience to digital transformation by combining blockchain with other technology forms, notably, AI, IoT or cloud computing (Cuomo, 2020).

Conclusion and future research

     This study reviews and summarizes four themes marking the changes in recordkeeping in accounting with blockchain technology. This technology can provide shared, verified, and agreed-upon (i.e., consensus-driven) auditable data. Auditing can enhance audit effectiveness with AI tools by using traceable and auditable blockchain data. This review interprets the results using agency and stakeholder theories to explain how blockchain-enabled accounting can avoid information asymmetry and include all stakeholders because blockchain offers new ways of organizing collaboration. However, it is a new, evolving technology that will challenge organizations faced with possible risks from embracing blockchain in accounting. Therefore, more research is needed to explore more cases of using blockchain-enabled accounting. Lastly, this study suggests some questions that future research could seek to answer and thus broaden blockchain literature with empirical research. They could ask: What types of accounting transactions can be recorded on a blockchain, and at what cost? How can blockchain data be synchronized in AI-enabled auditing? What are the data standards that blockchain and AI can reach? How can businesses govern blockchain-based accounting information systems? How can regulations be adjusted to guide and support innovation in blockchain-based accounting information systems and AI-enabled auditing? What different responses and challenges face large accounting and auditing practices and SMPs from adopting blockchain? Blockchain needs to be developed, standardized, and improved to overcome technical, organizational, and regulatory challenges to become truly an integral part of the financial system.

Abstract

The purpose of this paper is twofold: (i) to investigate some of the main issues surrounding the classification of digital currencies, and (ii) to identify the accounting practices and standards tied to digital currencies. This paper discusses two different types of digital currencies, including: central bank digital currencies (CBDCs) and privately issued cryptocurrencies such as Bitcoin. The findings of this study suggest that current accounting standards do not precisely cover the accounting treatment of digital currencies, even though the estimated value of market capitalisation of cryptocurrency in 2022 was USD 200 billion. This conceptual paper identifies the imminent need for an accounting standard to provide guidance on the identification, classification, measurement, and presentation of digital currencies. In the interim, existing accounting standards can be amended to incorporate digital currencies to avoid inconsistent global accounting approaches.

Introduction

Digital currency is an unparalleled technological advancement that has received increasing attention from researchers, investors, financial institutions and regulators. It is a mode of exchange that does not have a physical or tangible basis and exists purely in an electronic form. It should not, however, be confused with electronic money such as an online bank account, which shows the amount of cash that is held in a specified account and is linked to a physical currency. Many businesses are now pursuing digital currency as part of their wider financial management system, and this should be appropriately recorded in their financial statements. Despite the rapid increase in the amount and frequency of digital currency transactions, there is no clear guidance from the International Accounting Standards Board (IASB). The classification of digital currencies is a significant issue, and lack of guidance from standard-setters affects the accounting treatment of digital currencies and disclosures in financial statements.

Current literature shows the lack of focus on accounting treatment of digital currencies. In this conceptual paper, we aim to address this literature gap by examining accounting classification and treatment of transactions involving digital currencies. In addition, the paper aims to discuss a number of potential risks associated with the use of digital currencies and lack of clear classifications. Key questions around the classification, reporting and disclosure of digital currencies are addressed in this paper, including: In what asset class should digital currencies be classified as? and, is there an existing accounting standard for digital currency within the current IFRS standards?

Summary and conclusion

Digital currencies represent a genuinely new development in the landscape of financial payments. The main issue is that there are currently no clear or universal accounting standards or classifications for digital currencies. It is critical that blockchain technology, regarded as the underlying technology of most digital currencies, is fully understood, in order to be able to create relevant accounting and taxation standards as well as regulatory frameworks. Blockchain could therefore positively impact business models due to its unique characteristics, which address a number of key business issues. In addition, it offers the possibility of ‘triple-entry accounting’, in which accounting entries are cryptographically sealed by a third entry and made accessible to all third parties. Furthermore, blockchain accounting can reduce errors in disclosure and earnings management, improve the reliability and timelines of accounting information, and accordingly mitigate information asymmetry.

Accounting standard setters seem to be struggling to cope with the exponential growth in digital assets, which has led to a lack of consensus among them about how to treat these assets. This demonstrates that there is an urgent need for clear guidance to be issued by the standard-setters, as this absence has hindered the development of a universal accounting practice for digital currencies and has thus posed a number of challenges for authorities in relation to the classification and measurement of digital currencies.

Abstract

The IoT market is continuously expanding, and security measures parallel to the growing industrialization has drawn the research community’s attention. While several works have focused on the different technologies used to protect IoT devices, this paper aims to narrow the focus to Blockchain and Artificial Intelligence (AI) solutions for security and privacy issues faced by these devices. These technologies address two major vulnerabilities with edge devices on IoT networks: centralization and weak edge nodes. Blockchain provides a distributed system that can help avoid a single-point failure and can be used to optimize battery life on low-level devices by load balancing. On the other hand, AI’s power to learn and adapt is critical to automate systems and make them intelligent enough to analyze collected data. The combination of these two technologies is capable of mitigating multiple challenges IoT architectures face currently. The paper discusses the latest major architectures that integrate Blockchain and AI to enhance security within the. This paper also presents the comprehensive take on the device security and drawbacks to these mechanisms. This work also addresses the future of security in IoT and suggests different areas that need further work to better comprehend how the combination of these technologies can assist in enhancing security.

INTRODUCTION

The Internet of Things (IoT) market, a network of devices that communicate and exchange data with each other, has expanded over the last decade. IoT devices provide different applications such as health care, smart homes, wearables, and smart cities. The advent of a wide range of devices requires security that matches its capabilities to ensure the safety of the system and network. The number and type of attacks carried out against IoT devices have increased exponentially. As the need for faster and more efficient devices increases, there is a lag in equal breakthroughs in IoT security. According to Business Insider’s 2020 IoT research, IoT devices are predicted to increase to 41 billion by 2027 [1].

In order to meet this challenge, we must focus on the security strategies that match IoT devices’ hardware and computational power to minimize internal or outsider attacks.

CONCLUSION

This paper defined the role that AI/ML and Blockchain have currently in IoT devices, explaining in detail how Blockchain technology works and how AI/ML is used to lessen the computational load on IoT devices. We then talked about Blockchain and AI/ML in IoT security and how having these technologies strengthens privacy, data integrity, and data processing. Four potential solutions were explored and analyzed to understand how they could help deficiencies in the current IoT network setup as well as challenges that were not addressed in the solutions. Finally, future lanes of research were brought up for researchers to study.

This paper presented the role that AI/ML and Blockchain have currently in IoT devices and how these two can work in tandem to lessen the computational load on IoT devices. The paper then discussed the scope of Blockchain and AI/ML in IoT security towards strengthening privacy, data integrity, and data processing. Then it addresses the vulnerabilities and feasibility of AI/ML and Blockchain towards IoT security. With several potential solutions, four major works were studied. The paper then progresses to analyze these works on several parameters, summarizing them based on their: 1) Feasibility, 2) Security Strength, 3) Applicability and 4) Robustness.

Abstract

     Security and privacy in the Internet of Things (IoT) other significant challenges, primarily because of the vast scale and deployment of IoT networks. Blockchain-based solutions support decentralized protection and privacy. In this study, a private blockchain-based smart home network architecture for estimating intrusion detection empowered with a Fused Real-Time Sequential Deep Extreme Learning Machine (RTS-DELM) system model is proposed. This study investigates the methodology of RTS-DELM implemented in blockchain-based smart homes to detect any malicious activity. The approach of data fusion and the decision level fusion technique are also implemented to achieve enhanced accuracy. This study examines the numerous key components and features of the smart home network framework more extensively. The Fused RTS-DELM technique achieves a very significant level of stability with a low error rate for any intrusion activity in smart home networks. The simulation findings indicate that this suggested technique successfully optimizes smart home networks for monitoring and detecting harmful or intrusive activities.

Introduction

     A smart home is connected to the Internet, allowing users to manage a variety of smart gadgets, each of which serves an important purpose in the home for the user and their family. The IoT is the foundation of an intelligent home network, connecting disparate intelligent devices such as smartphones, smart computers, and wearable devices. Citizens’ lives can be made easier and safer by making their homes more open and secure. The smart home provides useful resources such as monitoring habits and even safety tests, which have compelled consumers and system developers to conduct extensive research.

     Blockchain-type systems and unified “cloud-like” computing networks can be used to solve these problems. Blockchain was developed in 2008 by Satoshi Nakamoto and includes a time-stamped set of malicious evidence documentation managed by a network of autonomous networks [1]. Blockchain architecture consists of a series of blocks linked together by simple cryptography. The three main concepts underlying the operation of blockchain technologies are inflexibility, decentralization, and transparency. The three roles have been remarkably effective, exposing them to a wide range of digital currency technologies, such as the functionality of mobile vehicles, mobile phones, and embedded systems. While the blockchain platform is secure and anonymous, there are some issues with its current implementation. For example, Sybil attacks by generations of false identities to manipulate the community have become more complex.

Conclusions

     In this study, the idea of a smart contract in blockchain technology is employed to validate the user’s identity for accessibility to centralized smart home services. The most significant benefit of this research is the demonstration of how easy it is to receive facilities and how secure the resources are. There is no need to have redundant authentication because no other third-party users can access smart home systems, even if another user tries to access an already used resource. Intrusion detection in smart homes, especially in the context of assessment and prediction, remains a key concern. In the meantime, recent advances in the blockchain and machine learning sectors have demonstrated tremendous promise to accomplish these aims. Discussing the need for an efficient approach, this study provided a compact and efficient mechanism for intrusion prevention. An RTS-DELM approach was developed, and also data fusion techniques were presented to optimize multi-sensor networks. Numerous measures were used to assess the feasibility of the proposal. The consistency of RTS-DELM findings showed that the proposed method is more successful than others. The suggested RTS-DELM solution obtained an exceptionally high rate of success, showing 95.28% accuracy. The findings obtained are encouraging, and we will continue to investigate more applications for the device through the deployment of more datasets and varying frameworks.

Abstract

     Data storage for attendance at a company or agency is usually stored in a local or cloud database. This type of storage has several issues, such as privacy and data integrity, because several parties will fully regulate privacy and data integrity. Therefore, a data storage system is needed that can provide privacy, security, and data integrity to maintain the authenticity of sensitive data. This study wants to develop to implement blockchain technology to store employee attendance data from the HR department in a company. Employee attendance data is taken from the Angular web application integrated with a permissioned blockchain framework called Hyperledger Composer. This study chose Hyperledger Composer because this type of blockchain has a fast validation time. Hyperledger Composer has a Representational State Transfer Application Programming Interface (REST API) named composer-rest-server, which allows Hyperledger blockchain to interact with other components. The implementation results show that Hyperledger Composer can be functionally used as data storage for the attendance management and Payroll system. In addition, Hyperledger Composer performance is measured by evaluating block transaction times. The evaluation of the Hyperledger Composer is done in three ways: directly within the Hyperledger Composer, using the Angular web application through the REST API, and using JMeter through the REST API. As a result, testing for making transaction blocks varies from 1 – 17ms on an experiment directly in Hyperledger Composer, 5 – 296ms through the REST API using JMeter tools, and 1 – 4270ms through the Angular Web Application. The result shows that the performance of the REST API produced by the composer-rest-server is recorded faster than Ethereum. With these results, composer-rest-server can handle systems that require fast transaction times, such as voting systems, health monitoring, and the Internet of Things (IoT) application, because the average time to conduct transactions is still under one second. Thus, Hyperledger as attendance data storage can provide privacy and data integrity.

Introduction

     Blockchain is a distributed digital ledger technology that Nowadays, the development and use of technology are developing more rapidly in various fields, one of which is information technology. Information technology is a technology used to get, store, organize, process, and manipulate the amount of data to produce relevant and accurate information. The attendance management and payroll system are some of the information systems on financial activities required in a company or agency. The use of this information system can provide an accurate report of attendance records and payroll. The attendance management and payroll system is a system that processes the attendance information to determine the total salary of each employee. Attendance data is sensitive information that must be maintained for authenticity because it can affect the number of salaries to be paid.

Conclusion

     The blockchain attendance management and payroll system design can be well implemented. All functions of the Hyperledger Composer component and the Angular web application are running properly and according to the design. Hyperledger Composer can communicate with the other components through the REST API provided by the composer-rest-server. The REST API provided by composerrest-server performs well through JMeter with an average transaction time of 198ms and the total time required for 100 transactions of 1.98 seconds compared to Ethereum Blockchain. Blockchain technology can support the attendance and payroll system, so this system has advantages in data security and data integrity.

Highlights

Abstract

Keywords

1. Introduction

2. Background

3. Theoretical framework and enabling factors of blockchain technology adoption in the supply chain

4. Research method

5. Analysis and results

6. Discussion and implications

7. Limitations and conclusion

Appendix I. Description of the survey procedure and the questionnaire

Appendix II. Total Relation Matrix

References

Abstract

Blockchain technology has been growing in importance and acceptability over the past few years. Yet, there is limited empirical research on the organizational and technology specific factors that play a critical role in driving its adoption in the supply chain. The purpose of this paper is to develop a comprehensive framework for blockchain adoption in the supply chain by identifying the enablers and empirically evaluating their interdependencies and impact on adoption. 20 enablers of blockchain adoption in the supply chain are identified using an extensive literature review and theoretical lenses from the Diffusion of Innovation (DOI) theory and the business technology adoption model developed by Iacovou, Benbassat and Dexter (1995). In the confirmatory phase, we employ the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method to extract logic from data collected from 37 French experts about the impact of the enablers and their interdependencies. Our paper extends the multi-theoretic empirical studies to blockchain technology and identifies the enablers of blockchain adoption from technological, organizational, supply chain and external environment perspectives. Regarding the importance of the categories of enablers, we find that the relative advantage of the technology and the external pressure are the most prominent categories of enablers that impact blockchain adoption in the supply chain. Our analysis also shows the important causal role on adoption of the potential of blockchain to reduce transaction cost, the consumer interest in traceability data and the establishment of a regulatory framework for blockchain usage.

1. Introduction

Blockchain technology has recently gained importance as a promising technology in the area of supply chain management. For instance, Maersk used an IBM blockchain solution to efficiently track its containers around the world (Popper and Lohr, 2017). Catina Volpone vineyard (www.cantinavolpone.it) in Puglia, Italy and Ernst and Young’s EZ Lab (www.ezlab.it) developed a blockchain-based solution that enables full transparency through the wine supply chain and allows customers to access information about the harvesting, pressing, and bottling dates and conditions, among many other details for each bottle or case of wine (Montecchi et al., 2019). Similarly, Walmart and IBM have successfully implemented a blockchain-based solution for tracking pork products in China with a farm-to-table approach, providing transparency and full information about the supply chain stages every individual product went through (Yiannas, 2017). Blockchain solutions providers such as Everledger (everledger.io), Provenance (provenance.org), Bext360 (bext360.com) conducted pilot projects and offered typical use cases that demonstrate blockchain potential in verifying and certifying the origin, authenticity and integrity of products such as diamond, wine buttles, luxury fashion, coffee beans, and medicines (Kshetri, 2018; Montecchi et al., 2019; Lacity, 2018; Tönnissen and Teuteberg, 2020). Enabling traceability, enhancing transparency and establishing product provenance as shown in the above examples are not the only benefits of using blockchain technology. Indeed, blockchain is a distributed ledger (database) through which supply chain partners can interact and create, verify, validate, and securely store various kinds of records such as product information, certificates, localization data, transaction records, data acquired from sensors and other connected devices (Crosby et al., 2016; Iansiti and Lakhani, 2017). Thus, in addition to providing traceability and making the whole history of products digitally available, blockchain promises to improve supply chain coordination and process efficiency (Kshetri, 2018; Babich and Hilary, 2020; Queiroz et al., 2020; Wamba et al., 2020) and to achieve supply chain sustainability goals (Casey and Wong, 2017; Kouhizadeh and Sarkis, 2018; Kshetri, 2018; Babich and Hilary, 2020).

Abstrac

1. Introduction

2. Related Work

3. Design and Development of Blockchain-Based IoV

4. Experiment Setup and Results

5. Conclusions

References

Abstract

     The rapid advancement in the area of the Internet of Vehicles (IoV) has provided numerous comforts to users due to its capability to support vehicles with wireless data communication. The exchange of information among vehicle nodes is critical due to the rapid and changing topologies, high mobility of nodes, and unpredictable network conditions. Finding a single trusted entity to store and distribute messages among vehicle nodes is also a challenging task. IoV is exposed to various security and privacy threats such as hijacking and unauthorized location tracking of smart vehicles. Traceability is an increasingly important aspect of vehicular communication to detect and penalize malicious nodes. Moreover, achieving both privacy and traceability can also be a challenging task. To address these challenges, this paper presents a blockchain-based efficient, secure, and anonymous conditional privacy-preserving and authentication mechanism for IoV networks. This solution is based on blockchain to allow vehicle nodes with mechanisms to become anonymous and take control of their data during the data communication and voting process. The proposed secure scheme provides conditional privacy to the users and the vehicles. To ensure anonymity, traceability, and unlinkability of data sharing among vehicles, we utilize Hyperledger Fabric to establish the blockchain. The proposed scheme fulfills the requirement to analyze different algorithms and schemes which are adopted for blockchain technology for a decentralized, secure, efficient, private, and traceable system. The proposed scheme examines and evaluates different consensus algorithms used in the blockchain and anonymization techniques to preserve privacy. This study also proposes a reputation-based voting system for Hyperledger Fabric to ensure a secure and reliable leader selection process in its consensus algorithm. The proposed scheme is evaluated with the existing state-of-the-art schemes and achieves better results.

Introduction

     Internet of Vehicles (IoV) networks are able to improve driving safety, efficiency, and traffic management using On-Board Units (OBUs) for data communication, with or without prior infrastructure. As a result of the increase in the number of users and the open nature of these networks, security threats are a challenge. Security requirements such as authentication, the privacy of vehicle nodes, and audibility are necessary to avoid these networks from different types of attacks, such as impersonation attacks, and spreading of false information. Authentication of nodes in a network is the first line of defense to block any unwanted activity in a network [1,2]. If the network allows unauthenticated vehicle nodes, then malicious vehicle nodes can also join the network and undertake different types of activities, e.g., impersonate an ambulance to exceed the given speed limits. If integrity is not provided during message transmission, then vehicle nodes can misbehave and alter the content of a message. In such a case, the receiver only knows that the message was sent by a legitimate vehicle, and they would be responsible for any damage. Privacy is a core feature of IoV, but traceability is also necessary in the case of any unwanted activity in a network. In this case, the privacy of the vehicle should be revoked and punished

Conclusions

     In this paper, we introduced a hard security solution, i.e., the improved Hyperledger Fabric, to implement a blockchain-enabled IoV for safe vehicle information sharing. This paper comprehensively highlighted the issues related to IoV. The literature review concluded that most of the security services can be achieved by the implementation of blockchain. Hyperledger Fabric is one of the major implementations of blockchain for achieving security services. This paper provides a brief introduction to IoV, Hyperledger Fabric, consensus algorithms, privacy, and anonymization techniques, in conjunction with the additional terminology necessary to understand the problem statement and proposed scheme. Then a critical analysis is undertaken of existing consensus algorithms and conditional privacy schemes in the context of the IoV environment. The paper also discusses the non-applicability of existing schemes to the IoV environment. Thus, there is a requirement for an efficient decentralized scheme for IoV that can address security issues and fulfill the latest security requirements of vehicular communication. Hyperledger Fabric appears to be the most suitable emerging solution for a resource-constrained environment, and addresses some of the functionality issues of IoV. The security analysis indicates the proposed scheme will address some of the limitations of existing schemes and fulfill the security criteria of CPPA schemes for IoV. The two main contributions of this research relate to the manner in which it addresses the issue of the leader selection process. The first is to select leaders based on their reputation. A reputation-based scheme is utilized to calculate the accurate reputation of RSUs. Second, this paper presents an anonymous and traceable CPPA approach that can be utilized in a vehicular network.

Abstract

Keywords

1. Introduction

2. Overview and preliminary preparation of blockchain

3. Blockchain attack classification system

4. Mining attack and defense methods of mining pool

5. Attack and defense methods of network communication and smart contracts

6. Attack and defense methods of privacy thefts

7. Future research direction

8. Conclusion

Declaration of Competing Interest

Acknowledgment

References

Abstract

Owing to the incremental and diverse applications of cryptocurrencies and the continuous development of distributed system technology, blockchain has been broadly used in fintech, smart homes, public health, and intelligent transportation due to its properties of decentralization, collective maintenance, and immutability. Although the dynamism of blockchain abounds in various fields, concerns in terms of network communication interference and privacy leakage are gradually increasing. Because of the lack of reliable attack analysis systems, fully understanding some attacks on the blockchain, such as mining, network communication, smart contract, and privacy theft attacks, has remained challenging. Therefore, in this study, we examine the security and privacy of the blockchain and analyze possible solutions. We systematical classify the blockchain attack techniques into three categories, then discuss the corresponding attack and defense methods based on these categories. We focus on (1) the attack and defense methods of mining pool attacks for blockchain security issues, such as block withholding, 51%, pool hopping, selfish mining, and fork after withholding attacks, in the attack type of consensus excitation; (2) the attack and defense methods of network communication and smart contracts for blockchain security issues, such as distributed denial-of-service, Sybil, eclipse, and reentrancy attacks, in the attack type of middle protocol; and (3) the attack and defense methods of privacy thefts for blockchain privacy issues, such as identity privacy and transaction information attacks, in the attack type of application service. Finally, we discuss future research directions for blockchain security.

1. Introduction

Recently, some essential characteristics of blockchain1, such as decentralization, collective maintenance, and immutability, were identified and have led to its explosive growth. Blockchain has been defined as the fifth disruptive innovation of the computing paradigm after the mainframe, personal computer, internet, and mobile and social network [1]. Because the nodes in the blockchain follow the same accounting transaction rules and consensus under the consensus algorithm, adopt the one-way hash algorithm, and strictly generate blocks in chronological order, blockchain has the advantages of immutability and encryption security. Therefore, blockchain is applied to digital currency [2], smart finance [[3], [143]], smart homes [4], smart medical care [5], smart human resource [142], smart transportation [6], [7], and so on. International data corporation (IDC) reported that although the blockchain market worldwide was affected by COVID-19 in 2020, the global spending on blockchain solutions was nearly $4 billion US dollars. As the economy recovers, the rate of global blockchain market spending in 2023 will usher in a strong rebound and the global spending on blockchain solutions will reach $16 billion US dollars [8].