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Edge computing provides a unified platform for computing, networking, and storage resources, enabling data to be processed in a timely and efficient manner near the source. Thus, it has become the basic platform for industrial Internet of things (IIoT). However, computing′s unique features have also introduced new security problems. To solve the pr...
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... authors in the literature [32] proposed a three-tier network architecture composed of an edge network, edge network management center, and cloud server. The architecture of edge computing is shown in Figure 2. The edge network management center is located between the cloud and the terminal equipment. ...
Citations
... Blockchain can provide robust access control mechanisms and identity management solutions [41]. Through the use of smart contracts, blockchain can enforce fine-grained access controls, allowing healthcare providers and authorized entities to access specific medical data based on predefined permissions. ...
Medical data security and privacy are becoming more important as healthcare organizations digitize. The security and integrity of sensitive medical data are at risk due to traditional centralized databases' susceptibility to data breaches, hacking attempts, and unauthorized access. The chapter gives a full overview and study of how blockchain technology can be used to secure medical records. Blockchain, as a decentralized and tamper-proof ledger, offers potential solutions to the existing security challenges. The chapter explores various blockchain-based approaches, protocols, and frameworks designed to enhance data security, access control, privacy, and data sharing in the healthcare domain. The analysis includes an evaluation of the advantages, limitations, and implementation considerations of blockchain technology, along with a discussion of potential future research directions.
... This work suggests that permissioned blockchain platforms should be preferred for IoT due to the security and privacy offered by it. In another work, Ren [20] proposed a blockchain based identity management and access control approach utilizing Bloom filter for edge computing environment. It is worth mentioning that edge computing is a paradigm to process data generated by IoT devices in real-time to fulfill the requirements of mission-critical applications such as smart grids or driverless cars. ...
The popularity of IoT has opened avenues for many new solutions such as social network of devices and web of things where IoT devices may have multiple logical identities. Managing multiple logical identities of voluminous number of IoT devices securely is a challenging task. As a result, efficient identity management of IoT devices has become an important research topic. The existing literature on identity management of IoT devices is currently restricted to only one logical identity per device. The paper presents a solution using blockchain for managing multiple identities of IoT devices. The usage of blockchain also helps in authentication of mobile IoT devices using logical identities. The implementation of the solution is carried out using Hyperledger blockchain platform and its performance is evaluated using a simulator developed in Python. The results validate the feasibility and efficiency of the proposed solution.
... Embracing such encrypted communication protocols not only shields sensitive information from external threats but also fosters trust in the secure exchange of data across the decentralized architecture of edge computing, contributing to the overall resilience of the network against evolving cyber threats.• Distributed Identity ManagementDeploying decentralized identity management solutions is pivotal for secure authentication and authorization in edge computing[43]. The unique challenges of edge environments necessitate adaptive identity frameworks and technologies such as blockchain offer compelling solutions. ...
Security issues in cloud networks and edge computing have become very common. This research focuses on analyzing such issues and developing the best solutions. A detailed literature review has been conducted in this regard. The findings have shown that many challenges are linked to edge computing, such as privacy concerns, security breaches, high costs, low efficiency, etc. Therefore, there is a need to implement proper security measures to overcome these issues. Using emerging trends, like machine learning, encryption, artificial intelligence, real-time monitoring, etc., can help mitigate security issues. They can also develop a secure and safe future in cloud computing. It was concluded that the security implications of edge computing can easily be covered with the help of new technologies and techniques.
... Access control and identity management: Implement strict access controls based on the principle of least privilege, limiting user access to necessary data and services. Enforce multi-factor authentication (MFA) to add an extra layer of security to user accounts [70,71]. ...
Cloud computing technology is rapidly becoming ubiquitous and indispensable. However, its widespread adoption also exposes organizations and individuals to a broad spectrum of potential threats. Despite the multiple advantages the cloud offers, organizations remain cautious about migrating their data and applications to the cloud due to fears of data breaches and security compromises. In light of these concerns, this study has conducted an in-depth examination of a variety of articles to enhance the comprehension of the challenges related to safeguarding and fortifying data within the cloud environment. Furthermore, the research has scrutinized several well-documented data breaches, analyzing the financial consequences they inflicted. Additionally, it scrutinizes the distinctions between conventional digital forensics and the forensic procedures specific to cloud computing. As a result of this investigation, the study has concluded by proposing potential opportunities for further research in this critical domain. By doing so, it contributes to our collective understanding of the complex panorama of cloud data protection and security, while acknowledging the evolving nature of technology and the need for ongoing exploration and innovation in this field. This study also helps in understanding the compound annual growth rate (CAGR) of cloud digital forensics, which is found to be quite high at ≈16.53% from 2023 to 2031. Moreover, its market is expected to reach ≈USD 36.9 billion by the year 2031; presently, it is ≈USD 11.21 billion, which shows that there are great opportunities for investment in this area. This study also strategically addresses emerging challenges in cloud digital forensics, providing a comprehensive approach to navigating and overcoming the complexities associated with the evolving landscape of cloud computing.
... Second, vehicle-to-everything (V2X) relieves severe performance and energy constraints on the edge side and offers redundancy for autonomous driving workloads besides the edge system design [44]. By offering a unified platform for networking, processing, and storage resources, edge computing makes it possible to analyze data quickly and effectively close to its source [45]. As a result, the industrial Internet of things now uses it as its foundational platform (IIoT). ...
... But the special qualities of computing have also brought up new security issues. In [45], an edge computing-based blockchain-based identity management and access control method is devised to address the issue. To achieve network entity registration and authentication, self-certified cryptography is used. ...
The safety of maritime environments in context with effective and secure wireless communication networks is required for ships, coastal stations, and maritime authorities. The dynamic nature of marine environments, where ships traverse vast and unpredictable expanses of oceans and seas, presents big challenges to safety and risk management. Wireless communication technology is widely employed in maritime activities for communication via ocean networks and underwater wireless sensor networks (UWSNs). Maintaining the safety of the maritime environment, effective anomaly detection, prompt risk mitigation, and real-time communication becomes more difficult due to its dynamic nature. International trade and transportation are facilitated by the maritime industry. In addition to protecting lives and averting environmental disasters, maritime safety is important for maintaining the effectiveness and dependability of shipping routes. To handle the intricacies of maritime safety, this work proposes a novel preventive framework for anomaly detection and risk management in Maritime Wireless Communications (MWC). The proposed framework is based on edge computing and machine learning models. The framework makes use of edge computing technology to process data locally, lowering latency and enabling real-time communication in maritime environments. A proactive safety approach has been adopted to ensure the well-being of seafarers, safeguard vessels, and protect the marine environment. As maritime cybersecurity threats continue to evolve, the proposed research aims to enhance the cybersecurity posture of MWC. The framework will incorporate measures to detect and respond to potential cyber threats, ensuring the integrity and security of communication channels under international maritime cybersecurity standards. The proposed anomaly detection framework incorporates machine learning models such as Long Short-Term Memory (LSTM) and Isolation Forests (IF). The proposed framework also places a strong emphasis on preventative safety measures, including cybersecurity safeguards to protect communication channels in the constantly changing digital marine operations environment. To demonstrate the effectiveness of the proposed framework, the experiments were performed based on a publicly available dataset and implemented in the context of marine communications. The results show significant accuracy as well as high precision, recall, and F1-score metrics generated by the LSTM and IF models. The results highlight that the proposed framework can detect anomalies and potential threats in real-time marine communications.
... There are few studies on the access control of Internet edge nodes. They ignore the potential risks of edge nodes, and the default edge nodes are safe and reliable [8,9]. Edge nodes should be confirmed through trusted mechanism when accessing the Internet. ...
The purpose of introducing blockchain into electronic archives sharing and utilization is to break the information barrier between electronic archives sharing departments by relying on technologies such as smart contract and asymmetric encryption. Aiming at the problem of dynamic permission management in common access control methods, a new access control method based on smart contract under blockchain is proposed, which improves the intelligence level under blockchain technology. Firstly, the Internet attribute access control model based on smart contract is established. For the dynamic access of heterogeneous devices, the management contract, permission judgment contract and access control contract are designed; Secondly, the access object credit evaluation algorithm based on particle swarm optimization radial basis function (PSO-RBF) neural network is used to dynamically generate the access node credit threshold combined with the access policy, so as to realize the intelligent access right management method. Finally, combined with the above models and algorithms, the workflow of electronic archives sharing and utilization model of multi blockchain is constructed. The experimental results show that the time-consuming of the process increases linearly with the number of continuous access to electronic archives blocks, and the secure access control of sharing and utilization is feasible, secure and effective.
... For example, (Nyamtiga 2018) only address the problem of data anonymity and integrity in IoT systems with integrated edge computing and use blockchain technology to achieve secure storage of IoT data. [9] face the problem of large-scale data transmission and storage under industrial IoT, and edge computing processes the source data and then blockchain to achieve secure storage and management of data. ...
In order to solve the problem of data security and management between IoT edge nodes and massive heterogeneous devices, combined with the wide application of blockchain technology in distributed system data security management, a blockchain-based Internet of Things access control model (SC-ABAC) is proposed by combining smart contracts and attribute-based access control. The traditional consensus algorithm PoW (Proof of Work) and SC-ABAC access control management process are optimized. By quantitative analysis, the time to call contracts in the query process increases linearly, the time of the policy addition and judgment process is constant, and the energy consumption of the optimized consensus mechanism is smaller than that of the PoW unit. This model provides decentralized, fine-grained, and dynamic access control management in IoT environments, enabling distributed systems to reach consensus faster and ensure data consistency.
... The IIoT generates a massive amount of data, including sensitive industrial data, customer information, and operational details. Ensuring data privacy and protecting it from unauthorized access, breaches, or data leaks is crucial to maintain trust and compliance with privacy regulations (Ren et al. 2019). Therefore, access control mechanisms are incorporated with this to maintain security measurements (Alcaraz 2019). ...
Smart industry paradigms are encouraged for automated and error-less manufacturing and job shop processing with the Industrial Internet of Things. The smart manufacturing environment employs independent machines and devices for providing cost-effective outcomes. The independent operating nature of the machines/devices is lured easily through the external hijackers that degrade the production outcome. By considering the real-time smart industrial process, this paper introduces Performance-focused Process Transaction Framework. The main motive of this work is to ensure secure job transactions in the smart industry with reduced task failures and improved production efficiency. The machines' performance is observed and measured based on the previous job completion rate and successive allocation intervals. Reward-based learning is induced in this framework for monitoring the operation state of the machine/device. The centralized controller makes use of the rewards and states for deciding the allocation without adversary interruption. In this job transaction process, the machine's adversary behavior is vital in determining production efficiency. The adverse behaving nature of the devices is detected in an early stage for reducing task failures. Further, the proposed framework's performance is verified using the metrics like true negative rate, adversary impact, processing time, and task allocation rate.
... However, IIoT domains do not necessarily trust each other because one domain is usually reluctant to allow other domains access to its resources. This can result in IIoT [14] IIoT Centralized No Yes No Li et al. [15] IoT Single-chain Yes Yes No Ren et al. [16] IIoT Single-chain Yes Yes No ...
... However, it was not modeled or validated. Ren et al. [16] combined blockchain and edge computing concepts and proposed a cross-domain trust model based on the Consortium chain, which reduces the traditional cross-domain access process. With the increase in IIoT devices and domains, there are higher requirements for system scalability, computing power, and storage capacity. ...
The Industrial Internet of Things (IIoT) accelerates smart manufacturing and boosts production efficiency through heterogeneous industrial equipment, intelligent sensors, and actuators. The Industrial Internet of Things is transforming from a traditional factory model to a new manufacturing mode, which allows cross-domain data-sharing among multiple system departments to enable smart manufacturing. A complete industrial product comes from the combined efforts of many different departments. Therefore, secure and reliable cross-domain access control has become the key to ensuring the security of cross-domain communication and resource-sharing. Traditional centralized access control schemes are prone to single-point failure problems. Recently, many researchers have integrated blockchain technology into access control models. However, most blockchain-based approaches use a single-chain structure, which has weak data management capability and scalability, while ensuring system security, and low access control efficiency, making it difficult to meet the needs of multi-domain cooperation in IIoT scenarios. Therefore, this paper proposes a decentralized cross-domain access model based on a master–slave chain with high scalability. Moreover, the model ensures the security and reliability of the master chain through a reputation-based node selection mechanism. Access control efficiency is improved by a grouping strategy retrieval method in the access control process. The experimental benchmarks of the proposed scheme use various performance metrics to highlight its applicability in the IIoT environment. The results show an 82% improvement in the throughput for the master–slave chain structure over the single-chain structure. There is also an improvement in the throughput and latency compared to the results of other studies.
... On the other hand, for the RBAC model, V. Veitas et al. [608] are a good representative of the contributions in this scope regarding data confidentiality, integrity, and availability with the objective of recovering an exact situation following the occurrence of an event or on demand. In addition to these, from the IT sector, we can highlight many surveys on this matter such as Y. Ren et al. [609], J. Qiu et al. [610], V. Hu [611] or Y. Zhu et al. [612] or even certain papers focusing on the combination of both RBAC and ABAC as in S. Long et al. [613] or A. Al-alaj et al. [614]. ...
Over the last few decades, automotive embedded Information and Communication Technology (ICT) systems have been used to enhance vehicle performance and enrich people’s driving experience, increasing the panel of software features within them. However, even though until now automakers have kept up with the innovation pace in terms of the functionalities that have been offered to passengers, the majority of automakers’ efforts have concentrated on bringing in these new functionalities by adding an unceasingly larger set of ECUs. All of this has been done without evolving any of the embedded software architecture consequently, due to budgetary constraints, legislative limitations, retro-compatibility problems, and a lack of awareness of the trending IT innovation. This unbalanced progress has then led to a substantial increase in in-vehicle architectural complexity, which has become a major concern for automakers nowadays as it makes the vehicle repairing process more complex, decreases software traceability and clashes with the objective of having higher business flexibility, modularity, and dynamicity within the vehicles. In this paper, we are going to go through literature, both academic and industrial, and propose a comprehensive study into automotive system transformation. We begin by giving a detailed analysis of the causes of evolution under five axes - i.e., society, business, industry, application, and technical. Then, we discuss the convergence of cars and software life cycles and propose a three-layered analysis of automotive ICT systems consisting of architecture design, software pipelines, and run-time management. Finally, we are going to propose certain detailed guidelines on the evolution perspectives for automotive systems through deriving from the convergence of advances in IT, as well as current and future automotive environmental constraints.
