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In the last century the automotive industry has arguably transformed society, being one of the most complex, sophisticated and technologically advanced industries, with innovations ranging from hybrid, electric and self-driving smart cars to the development of IoT-connected cars. Due to its complexity, it requires the involvement of many Industry 4...
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Since the early 1990s, Manufacturing Execution Systems (MES) have been playing a pivotal role in managing production activities and integrating business from the top floor to the shop floor, reducing manufacturing costs by increasing overall equipment effectiveness and minimizing unplanned downtime. Cyber-physical systems, the Internet of things an...
In the Industry 4.0 revolution, advanced manufacturing capabilities integrate technology and data to create intelligent production systems, such as automation, cloud computing, the Internet of Things and cyber-physical systems. Small and medium-sized enterprises, which are the backbone of economic growth, especially must apply the advanced technolo...
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... To create a reliable ITS, it is crucial to smoothly incorporate and interoperate with emerging technologies such as IoT, cloud computing [78], and Blockchain [69], [212]. This issue focuses on identifying and discussing the integration hurdles that must be overcome that the automotive industry encounters. ...
... Time Constraints Applications and services that operate under strict deadlines, such as navigation, traffic flow, congestion control, and efficient implementation of vehicular networks demand hard real-time guarantees [226] Integration Challenges with Emerging Technologies AI, IoT, cloud computing, edge computing, and Blockchain [78], [69], [212] H. Additional Challenges ...
According to research, the vast majority of road accidents (90%) are the result of human error, with only a small percentage (2%) being caused by malfunctions in the vehicle. Smart vehicles have gained significant attention as potential solutions to address such issues. In the future of transportation, travel comfort and road safety will be ensured while also offering several value-added services. The automotive industry has undergone a significant transformation through the use of emerging technologies and wireless communication channels, resulting in vehicles becoming more interconnected, intelligent, and safe. However, these technologies and communication systems are susceptible to numerous security attacks. The objective of this paper is to present a comprehensive overview of the smart vehicle’s architecture, encompassing emerging technologies and security challenges and solutions associated with smart vehicles. There has been a significant surge in the utilization of machine learning techniques in smart vehicles. We categorically discuss common security measures, including machine learning and deep learning based solutions that have been mentioned in the literature and implemented against security threats on smart vehicles. This paper has also been titled a tutorial due to its layout, which begins with covering preliminary knowledge, terminologies, and encompassing technologies required to comprehend smart vehicles. Following this, the paper addresses the overall challenges associated with smart vehicles and then focuses on security issues. In terms of solutions, the paper discusses overall solutions to security issues in smart vehicles before delving into a specific solution based on machine learning and deep learning.
... Moreover, Decentralized Applications (DApps) are applications whose backend is executed in a blockchain, unlike traditional applications where the backend runs on centralized servers [10,11]. DApps acquire all the decentralization properties provided by the blockchain, resulting in applications that preserve data privacy and are transparent and resistant to Denial of Service (DoS) attacks [12]. ...
Blockchain has been widely criticized due to the use of inefficient consensus protocols and energy-intensive mechanisms that derived into a global enormous power consumption. Fortunately, since the first blockchain was conceived in 2008 (the one that supports Bitcoin), hardware and consensus protocols have evolved, decreasing energy consumption significantly. This article describes a green blockchain solution and quantifies energy savings when deploying the system on traditional computers and embedded Single-Board Computers (SBCs). To illustrate such savings, it is proposed a solution for tackling the problem of academic certificate forgery, which has a significant cost to society, since it harms the trustworthiness of certificates and academic institutions. The proposed solution is aimed at recording and verifying academic records (ARs) through a decentralized application (DApp) that is supported by a smart contract deployed in the Ethereum blockchain. The application stores the raw data (i.e., the data that are not managed by the blockchain) on a decentralized storage system based on Inter-Planetary File System (IPFS). To demonstrate the efficiency of the developed solution, it is evaluated in terms of performance (transaction latency and throughput) and efficiency (CPU usage and energy consumption), comparing the results obtained with a traditional Proof-of-Work (PoW) consensus protocol and the new Proof-of-Authority (PoA) protocol. The results shown in this paper indicate that the latter is clearly greener and demands less CPU load. Moreover, this article compares the performance of a traditional computer and two SBCs (a Raspberry Pi 4 and an Orange Pi One), showing that is possible to make use of the latter low-power devices to implement blockchain nodes for proposed DApp, but at the cost of higher response latency that varies greatly depending on the used SBCs [...]
... This model is then tested through a case study on the port of Barcelona to assess its validity and relevance. Most of the studies in this category consider Industry 4.0 as a whole and discuss various smart technologies in general; however, the works of [24,25] focus specifically on blockchain technology. The first study is a review of blockchain technology within the context of the automotive industry, with an extensive look into the potential of this technology in enhancing many aspects of the automotive industry, including the manufacturing process. ...
... Fraga and his colleagues [24] studied the automotive industry. This complex and technologically advanced sector has developed innovations such as hybrid, electric, and self-driving cars, in addition to IoT connectivity. ...
... First, [52] explored the application of blockchain characterized by its decentralized and tamper-resistant ledger system and introduced various benefits, such as process automation through smart contracts and the reduction in fraud in payment systems. Furthermore, [24] highlights the significance of blockchain in bolstering cybersecurity measures. Blockchain offers improved data security, privacy, and accountability by ensuring tamper-proof data and fostering trust among stakeholders through consistent data structures. ...
In recent years, calls have increased for adherence to standards that ensure sustainability, including the global initiative presented by the United Nations with 17 Sustainable Development Goals (SDGs) to ensure a more sustainable future. Achieving these goals is extremely important, as institutions have sought to integrate technology, especially business intelligence, into their operations to ensure their achievement. This study aims to provide a systematic literature review of the intersection of information systems and sustainability in business intelligence. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology was utilized to select high-quality studies from various databases, including ScienceDirect, IEEE Xplore, and Scopus, to be included in this review. The methodology resulted in 32 studies taxonomized into four main categories covering different aspects of the intersection of information systems and sustainability. This study discusses integrating information systems and sustainability in various sectors, such as tourism, health, urban, and other sectors, with different technologies, such as Blockchain, IoT, Industry 4.0, and other innovations. Moreover, the information system types implemented to support sustainability practices in different domains are highlighted.
... Previous studies explored ML and blockchain technologies as cybersecurity defense mechanisms for IVNs [34][35][36]. ML-based solutions are analyzed based on intrusion/malware detection, topology (centralized or distributed), and technical dimension (traditional ML and DL), while blockchain-based solutions are analyzed based on secure data storage, secure onboard communication, secure data access, consensual protocol (proof of work; proof of stake), and deployment/miner [37,38]. ...
... Kim et al. [42] proposed the adoption of current blockchain technology in BMSs (battery management systems), which can be used as a cybersecurity reference for the development of battery systems. Other studies investigate how new blockchain algorithms could solve current automotive challenges, such as growing ledgers, increasing scalability, and reducing complexity and latency [37,38,43]. ...
Modern vehicles are increasingly interconnected through various communication channels, which requires secure access for authorized users, the protection of driver assistance and autonomous driving system data, and the assurance of data integrity against misuse or manipulation. While these advancements offer numerous benefits, recent years have exposed many intrusion incidents, revealing vulnerabilities and weaknesses in current systems. To sustain and enhance the performance, quality, and reliability of vehicle systems, software engineers face significant challenges, including in diverse communication channels, software integration, complex testing, compatibility, core reusability, safety and reliability assurance, data privacy, and software security. Addressing cybersecurity risks presents a substantial challenge in finding practical solutions to these issues. This study aims to analyze the current state of research regarding automotive cybersecurity, with a particular focus on four main themes: frameworks and technologies, standards and regulations, monitoring and vulnerability management, and testing and validation. This paper highlights key findings, identifies existing research gaps, and proposes directions for future research that will be useful for both researchers and practitioners.
... With the development of the automotive consumer loan market, the assessment of individual credit risk has become increasingly important [2,5]. In recent years, the automotive finance market has become one of the most significant segments of the credit market [6]. Although early credit scoring models have been applied in the automotive finance field as well [7], the rapidly changing and complex market demands more precise and dynamic models to adapt to risk assessment [8]. ...
In this study, we propose a predictive model for automotive consumer loans risk assessment, leveraging Generative Adversarial Networks (GANs) and Stacked Autoencoder Neural Networks (SAEs). We address issues of high dimensionality and sparsity inherent in big data environments and tackle the class imbalance problem using GANs. Feature selection is effectively carried out using SAEs. Experimental results prove the superiority of our approach over traditional neural networks and our model without GANs or SAEs. The proposed model shows significant potential for application in personal credit risk assessment within automotive finance and beyond. Future work is aimed at extending and improving our model and applying it to other domains.
... Other researchers highlighted other less significant barriers to Industry 4.0 implementation, such as data ownership concerns as a result of big data use, the lack of know-how of employees, the courage of top management to implement Industry 4.0 technologies [26], and security and privacy issues [27]. In conclusion, the following enablers were deduced to represent the enabling elements of digital readiness as a pillar of digital infrastructure, as shown in Table 1. ...
This research paper examines the digital infrastructure required to achieve project management success by analyzing the enabling elements of this digital infrastructure in terms of three pillars: digital readiness, digital fitness, and digital tools. A comprehensive literature review was conducted to identify these enabling elements and to develop a list of project management success indicators through which the success of project management can be measured. To evaluate and rank the digital infrastructure enabling elements, a Multi-Criteria Analysis (MCA) was implemented using a hybrid approach combining Fuzzy Analytic Hierarchy Process (FAHP) and Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS). The study used the digital infrastructure enabling elements as MCA alternatives and the project management success indicators identified in the literature review as MCA criteria. The results indicated that the enabling elements associated with digital tools are the most significant for project management success, with a FTOPSIS closeness coefficient (CCi) of 0.8525, followed by those related to digital fitness (CCi = 0.6481) and digital readiness (CCi = 0.1602). These findings have proven to be robust, as they remained consistent even when weights of the MCA criteria were adjusted in three new scenarios proposed in a scenario analysis. This research highlights the critical role of digital enabling elements in enhancing project management practice and achieving project management success. It also offers a strategic framework for organizations to develop and strengthen their digital infrastructure.
... Digital technologies and globalization play important roles in this evolution; global carmakers and automotive spare part manufacturers are taking note of this evolution and investing heavily in these changing. (Fraga-Lamas & Fernández-Caramés, 2019). Randall Miller (2019) explains that digital technologies and globalization effects to automotive industry in many ways, such as global manufacturing expansion force manufacturer moves production base to the lower labor cost country, digital technology change sale system to online sales to get customers from wider area, higher competition between global brand and local brand due to more knowledge and technologies transfer. ...
... Blockchain-based token systems can incentivize sharing high-quality threat intelligence [42]. transparency, and decentralization-provide unique advantages in enhancing security across different domains. ...
... The morphological analysis of Cluster 1 involving six more frequent and least frequent keywords in the articles is presented in Table 7. For example, distributed ledger and IoT/IIoT have occurred three times (Akrasi-Mensah et al. 2023;Fraga-Lamas & Fernández-Caramés, 2019). The authors have extantly considered BC technology's potential to adapt cybersecurity, authenticity, storage optimization, and smart contracts. ...
... However, transparency in BC-IoT-based systems can cause data privacy challenges (Tsang et al. 2021); here, the role of DT is vital to remove such under-confidence in using these technologies. (Fraga-Lamas & Fernández-Caramés, 2019) suggested that providing global access to BC guarantees transparency in SC. Here, an oracle-based system's trustless execution, transparency, and immutability are not applicable (Caldarelli 2022). ...
... However, as depicted in Fig. 11, the uncontrolled IoT devices with the BC can lead to misinformation or tampered data breaching DT at off-chain and on-chain as a potential point of failure (Kafeel et al. 2023). (Caldarelli 2022;Fraga-Lamas & Fernández-Caramés, 2019) also outlined the use of RFID sensors in SC as the biggest concern for Oracle-based reporting, ensuring data security for inbound and outbound systems. On the other hand, Industrial IoT networks integrated with permissioned BC can enable auditability and traceability for the stakeholders, but the security of information stored on the cloud is questionable (Akrasi-Mensah et al. 2023). ...
Blockchain has gained the attention of scholars and industry practitioners due to its immutability, transparency, and operational features, which can improve overall supply chain efficiency. However, a holistic review of blockchain-based supply chains through the lens of digital trust has remained elusive, making participants reluctant to share information due to growing attacks on digital systems and fraud. Therefore, this study examines digital trust in using blockchain technology for supply chain operations by following a five-stage review process consisting of a
systematic literature review protocol. The study performs a bibliometric and morphological analysis of 123 articles published between 2012 and 2023 to explore the current state and provide future research directions to develop safe, secure, reliable, and transparent blockchain-based supply chains. Further, our analysis reveals five characteristics of digital trust: transparency, cybersecurity, data protection, accountability, reliability and provenance, and regulatory compliance, which are essential to ensuring digital trust for supply chain sustainability, four research pathways, and keyword combinations for future research with other industry 4.0 technologies. Although blockchain applications for secure and trusted environments have been recognized, very little attention has been given to the detailed discussion on digitally trusted blockchain-based supply chains. The present
study contributes to the literature by synthesizing the available literature on blockchain-based supply chains from the perspective of digital trust, thereby analyzing the current state and providing future opportunities for researchers
and practitioners working in industry sectors and developing blockchain-based supply chains.
... DIM is still a key open issue [3], and a solution based on Distributed Ledger Technologys (DLTs) can be very powerful if some of the key issues (e.g., power, network stability, some form of security attack, etc.) can be properly addressed [4]. One type of DLT is blockchain, and the authors in [5] address security concerns and support identity management with blockchain for metaverses consisting of interconnected sub-metaverses. ...
Blockchain network (BCN)-based Self-Sovereign Identity (SSI) has emerged lately as an identity and access management framework that is based on Distributed Ledger Technology (DLT) and allows users to control their own data. Federated Learning (FL), on the other hand, provides a collaborative framework to update Machine Learning (ML) models without relying explicitly on data exchange between the users. This paper investigates identity management and authentication for vehicle users in the context of FL. We propose a novel approach based on blockchain-based SSI, which focuses on maintaining the authenticity and integrity of vehicle users' identities and data exchanged between the users and the aggregation server during the execution of the FL iterations. A primary objective of this paper is to achieve shorter durations for credential operations in an FL setting as the system size scales out. Integrating BCN-based SSI into the FL framework addresses several critical FL challenges, ensuring enhanced system security and operational integrity. This synergy of BCN-based SSI with federated learning enables robust identity verification providing a solution to fundamental trustworthiness issues in FL without sacrificing the benefits of decentralized data control, improving both the performance and reliability of the FL system. Experimental results suggest that the proposed FL-based system, together with credential management on a blockchain platform, has the potential to significantly improve data integrity and ensure the authentication of users. More specifically, the results of the FL system demonstrate that it takes longer (on the order of a hundred seconds) as the number of rounds and clients increase, while the implemented Decentralized Identifier (DID) system relying on BCN-based SSI has dramatically shorter dedicated time for completing credential operations.
