74 research outputs found

    Blockchain Technology for Intelligent Transportation Systems: A Systematic Literature Review

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    The use of Blockchain technology has recently become widespread. It has emerged as an essential tool in various academic and industrial fields, such as healthcare, transportation, finance, cybersecurity, and supply chain management. It is regarded as a decentralized, trustworthy, secure, transparent, and immutable solution that innovates data sharing and management. This survey aims to provide a systematic review of Blockchain application to intelligent transportation systems in general and the Internet of Vehicles (IoV) in particular. The survey is divided into four main parts. First, the Blockchain technology including its opportunities, relative taxonomies, and applications is introduced; basic cryptography is also discussed. Next, the evolution of Blockchain is presented, starting from the primary phase of pre-Bitcoin (fundamentally characterized by classic cryptography systems), followed by the Blockchain 1.0 phase, (characterized by Bitcoin implementation and common consensus protocols), and finally, the Blockchain 2.0 phase (characterized by the implementation of smart contracts, Ethereum, and Hyperledger). We compared and identified the strengths and limitations of each of these implementations. Then, the state of the art of Blockchain-based IoV solutions (BIoV) is explored by referring to a large and trusted source database from the Scopus data bank. For a well-structured and clear discussion, the reviewed literature is classified according to the research direction and implemented IoV layer. Useful tables, statistics, and analysis are also presented. Finally, the open problems and future directions in BIoV research are summarized

    Convergence of Blockchain and Edge Computing for Secure and Scalable IIoT Critical Infrastructures in Industry 4.0

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    This is the author accepted manuscript. The final version is available from IEEE via the DOI in this recordCritical infrastructure systems are vital to underpin the functioning of a society and economy. Due to ever-increasing number of Internet-connected Internet-of-Things (IoTs) / Industrial IoT (IIoT), and high volume of data generated and collected, security and scalability are becoming burning concerns for critical infrastructures in industry 4.0. The blockchain technology is essentially a distributed and secure ledger that records all the transactions into a hierarchically expanding chain of blocks. Edge computing brings the cloud capabilities closer to the computation tasks. The convergence of blockchain and edge computing paradigms can overcome the existing security and scalability issues. In this paper, we first introduce the IoT/IIoT critical infrastructure in industry 4.0, and then we briefly present the blockchain and edge computing paradigms. After that, we show how the convergence of these two paradigms can enable secure and scalable critical infrastructures. Then, we provide a survey on state-of-the-art for security and privacy, and scalability of IoT/IIoT critical infrastructures. A list of potential research challenges and open issues in this area is also provided, which can be used as useful resources to guide future research.Engineering and Physical Sciences Research Council (EPSRC

    Integration of Blockchain and Auction Models: A Survey, Some Applications, and Challenges

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    In recent years, blockchain has gained widespread attention as an emerging technology for decentralization, transparency, and immutability in advancing online activities over public networks. As an essential market process, auctions have been well studied and applied in many business fields due to their efficiency and contributions to fair trade. Complementary features between blockchain and auction models trigger a great potential for research and innovation. On the one hand, the decentralized nature of blockchain can provide a trustworthy, secure, and cost-effective mechanism to manage the auction process; on the other hand, auction models can be utilized to design incentive and consensus protocols in blockchain architectures. These opportunities have attracted enormous research and innovation activities in both academia and industry; however, there is a lack of an in-depth review of existing solutions and achievements. In this paper, we conduct a comprehensive state-of-the-art survey of these two research topics. We review the existing solutions for integrating blockchain and auction models, with some application-oriented taxonomies generated. Additionally, we highlight some open research challenges and future directions towards integrated blockchain-auction models

    Decentralized Federated Learning: Fundamentals, State-of-the-art, Frameworks, Trends, and Challenges

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    In the last decade, Federated Learning (FL) has gained relevance in training collaborative models without sharing sensitive data. Since its birth, Centralized FL (CFL) has been the most common approach in the literature, where a central entity creates a global model. However, a centralized approach leads to increased latency due to bottlenecks, heightened vulnerability to system failures, and trustworthiness concerns affecting the entity responsible for the global model creation. Decentralized Federated Learning (DFL) emerged to address these concerns by promoting decentralized model aggregation and minimizing reliance on centralized architectures. However, despite the work done in DFL, the literature has not (i) studied the main aspects differentiating DFL and CFL; (ii) analyzed DFL frameworks to create and evaluate new solutions; and (iii) reviewed application scenarios using DFL. Thus, this article identifies and analyzes the main fundamentals of DFL in terms of federation architectures, topologies, communication mechanisms, security approaches, and key performance indicators. Additionally, the paper at hand explores existing mechanisms to optimize critical DFL fundamentals. Then, the most relevant features of the current DFL frameworks are reviewed and compared. After that, it analyzes the most used DFL application scenarios, identifying solutions based on the fundamentals and frameworks previously defined. Finally, the evolution of existing DFL solutions is studied to provide a list of trends, lessons learned, and open challenges

    Improving efficiency and security of IIoT communications using in-network validation of server certificate

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    The use of advanced communications and smart mechanisms in industry is growing rapidly, making cybersecurity a critical aspect. Currently, most industrial communication protocols rely on the Transport Layer Security (TLS) protocol to build their secure version, providing confidentiality, integrity and authentication. In the case of UDP-based communications, frequently used in Industrial Internet of Things (IIoT) scenarios, the counterpart of TLS is Datagram Transport Layer Security (DTLS), which includes some mechanisms to deal with the high unreliability of the transport layer. However, the (D)TLS handshake is a heavy process, specially for resource-deprived IIoT devices and frequently, security is sacrificed in favour of performance. More specifically, the validation of digital certificates is an expensive process from the time and resource consumption point of view. For this reason, digital certificates are not always properly validated by IIoT devices, including the verification of their revocation status; and when it is done, it introduces an important delay in the communications. In this context, this paper presents the design and implementation of an in-network server certificate validation system that offloads this task from the constrained IIoT devices to a resource-richer network element, leveraging data plane programming (DPP). This approach enhances security as it guarantees that a comprehensive server certificate verification is always performed. Additionally, it increases performance as resource-expensive tasks are moved from IIoT devices to a resource-richer network element. Results show that the proposed solution reduces DTLS handshake times by 50–60 %. Furthermore, CPU use in IIoT devices is also reduced, resulting in an energy saving of about 40 % in such devices.This work was financially supported by the Spanish Ministry of Science and Innovation through the TRUE-5G project PID2019-108713RB-C54/AEI/10.13039/501100011033. It was also partially supported by the Ayudas Cervera para Centros Tecnológicos grant of the Spanish Centre for the Development of Industrial Technology (CDTI) under the project EGIDA (CER-20191012), and by the Basque Country Government under the ELKARTEK Program, project REMEDY - Real tiME control and embeddeD securitY (KK-2021/00091)

    High-level Architecture and Compelling Technologies for an Advanced Web-based Vehicle Routing and Scheduling System for Urban Freight Transportation

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    The search for a more efficient routing and scheduling, the improvement of service’s level and the increasing complexity of real-world distributive contexts are contingent variables that generate the need for a system’s architecture that may be holistic, innovative, scalable and reliable. Hence, new technologies and a lucid awareness of involved actors and infrastructures, provide the basis to create a more efficient routing and scheduling architecture for enterprises

    Lightweight mutual authentication and privacy preservation schemes for IOT systems.

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    Internet of Things (IoT) presents a holistic and transformative approach for providing services in different domains. IoT creates an atmosphere of interaction between humans and the surrounding physical world through various technologies such as sensors, actuators, and the cloud. Theoretically, when everything is connected, everything is at risk. The rapid growth of IoT with the heterogeneous devices that are connected to the Internet generates new challenges in protecting and preserving user’s privacy and ensuring the security of our lives. IoT systems face considerable challenges in deploying robust authentication protocols because some of the IoT devices are resource-constrained with limited computation and storage capabilities to implement the currently available authentication mechanism that employs computationally expensive functions. The limited capabilities of IoT devices raise significant security and privacy concerns, such as ensuring personal information confidentiality and integrity and establishing end-to-end authentication and secret key generation between the communicating device to guarantee secure communication among the communicating devices. The ubiquity nature of the IoT device provides adversaries more attack surfaces which can lead to tragic consequences that can negatively impact our everyday connected lives. According to [1], authentication and privacy protection are essential security requirements. Therefore, there is a critical need to address these rising security and privacy concerns to ensure IoT systems\u27 safety. This dissertation identifies gaps in the literature and presents new mutual authentication and privacy preservation schemes that fit the needs of resource-constrained devices to improve IoT security and privacy against common attacks. This research enhances IoT security and privacy by introducing lightweight mutual authentication and privacy preservation schemes for IoT based on hardware biometrics using PUF, Chained hash PUF, dynamic identities, and user’s static and continuous biometrics. The communicating parties can anonymously communicate and mutually authenticate each other and locally establish a session key using dynamic identities to ensure the user’s unlinkability and untraceability. Furthermore, virtual domain segregation is implemented to apply security policies between nodes. The chained-hash PUF mechanism technique is implemented as a way to verify the sender’s identity. At first, this dissertation presents a framework called “A Lightweight Mutual Authentication and Privacy-Preservation framework for IoT Systems” and this framework is considered the foundation of all presented schemes. The proposed framework integrates software and hardware-based security approaches that satisfy the NIST IoT security requirements for data protection and device identification. Also, this dissertation presents an architecture called “PUF Hierarchal Distributed Architecture” (PHDA), which is used to perform the device name resolution. Based on the proposed framework and PUF architecture, three lightweight privacy-preserving and mutual authentication schemes are presented. The Three different schemes are introduced to accommodate both stationary and mobile IoT devices as well as local and distributed nodes. The first scheme is designed for the smart homes domain, where the IoT devices are stationary, and the controller node is local. In this scheme, there is direct communication between the IoT nodes and the controller node. Establishing mutual authentication does not require the cloud service\u27s involvement to reduce the system latency and offload the cloud traffic. The second scheme is designed for the industrial IoT domain and used smart poultry farms as a use case of the Industrial IoT (IIoT) domain. In the second scheme, the IoT devices are stationary, and the controller nodes are hierarchical and distributed, supported by machine-to-machine (M2M) communication. The third scheme is designed for smart cities and used IoV fleet vehicles as a use case of the smart cities domain. During the roaming service, the mutual authentication process between a vehicle and the distributed controller nodes represented by the Roadside Units (RSUs) is completed through the cloud service that stores all vehicle\u27s security credentials. After that, when a vehicle moves to the proximity of a new RSU under the same administrative authority of the most recently visited RSU, the two RSUs can cooperate to verify the vehicle\u27s legitimacy. Also, the third scheme supports driver static and continuous authentication as a driver monitoring system for the sake of both road and driver safety. The security of the proposed schemes is evaluated and simulated using two different methods: security analysis and performance analysis. The security analysis is implemented through formal security analysis and informal security analysis. The formal analysis uses the Burrows–Abadi–Needham logic (BAN) and model-checking using the automated validation of Internet security protocols and applications (AVISPA) toolkit. The informal security analysis is completed by: (1) investigating the robustness of the proposed schemes against the well-known security attacks and analyze its satisfaction with the main security properties; and (2) comparing the proposed schemes with the other existing authentication schemes considering their resistance to the well-known attacks and their satisfaction with the main security requirements. Both the formal and informal security analyses complement each other. The performance evaluation is conducted by analyzing and comparing the overhead and efficiency of the proposed schemes with other related schemes from the literature. The results showed that the proposed schemes achieve all security goals and, simultaneously, efficiently and satisfy the needs of the resource-constrained IoT devices

    Advances in Information Security and Privacy

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    With the recent pandemic emergency, many people are spending their days in smart working and have increased their use of digital resources for both work and entertainment. The result is that the amount of digital information handled online is dramatically increased, and we can observe a significant increase in the number of attacks, breaches, and hacks. This Special Issue aims to establish the state of the art in protecting information by mitigating information risks. This objective is reached by presenting both surveys on specific topics and original approaches and solutions to specific problems. In total, 16 papers have been published in this Special Issue

    Building the Hyperconnected Society- Internet of Things Research and Innovation Value Chains, Ecosystems and Markets

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    This book aims to provide a broad overview of various topics of Internet of Things (IoT), ranging from research, innovation and development priorities to enabling technologies, nanoelectronics, cyber-physical systems, architecture, interoperability and industrial applications. All this is happening in a global context, building towards intelligent, interconnected decision making as an essential driver for new growth and co-competition across a wider set of markets. It is intended to be a standalone book in a series that covers the Internet of Things activities of the IERC – Internet of Things European Research Cluster from research to technological innovation, validation and deployment.The book builds on the ideas put forward by the European Research Cluster on the Internet of Things Strategic Research and Innovation Agenda, and presents global views and state of the art results on the challenges facing the research, innovation, development and deployment of IoT in future years. The concept of IoT could disrupt consumer and industrial product markets generating new revenues and serving as a growth driver for semiconductor, networking equipment, and service provider end-markets globally. This will create new application and product end-markets, change the value chain of companies that creates the IoT technology and deploy it in various end sectors, while impacting the business models of semiconductor, software, device, communication and service provider stakeholders. The proliferation of intelligent devices at the edge of the network with the introduction of embedded software and app-driven hardware into manufactured devices, and the ability, through embedded software/hardware developments, to monetize those device functions and features by offering novel solutions, could generate completely new types of revenue streams. Intelligent and IoT devices leverage software, software licensing, entitlement management, and Internet connectivity in ways that address many of the societal challenges that we will face in the next decade
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