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.

Digital certificates are regarded as the most secure and scalable way of implementing authentication services in the Internet today. They are used by most popular security protocols, including Transport Layer Security (TLS) and Datagram Transport Layer Security (DTLS). The lifecycle management of digital certificates relies on centralized Certification Authority (CA)-based Public Key Infrastructures (PKIs). However, the implementation of PKIs and certificate lifecycle management procedures in Industrial Internet of Things (IIoT) environments presents some challenges, mainly due to the high resource consumption that they imply and the lack of trust in the centralized CAs. This paper identifies and describes the main challenges to implement certificate-based public key cryptography in IIoT environments and it surveys the alternative approaches proposed so far in the literature to address these challenges. Most proposals rely on the introduction of a Trusted Third Party to aid the IIoT devices in tasks that exceed their capacity. The proposed alternatives are complementary and their application depends on the specific challenge to solve, the application scenario, and the capacities of the involved IIoT devices. This paper revisits all these alternatives in light of industrial communication models, identifying their strengths and weaknesses, and providing an in-depth comparative analysis.

Industrial networks are introducing Internet of Things (IoT) technologies in their manufacturing processes in order to enhance existing methods and obtain smarter, greener and more effective processes. Global predictions forecast a massive widespread of IoT technology in industrial sectors in the near future. However, these innovations face several challenges, such as achieving short response times in case of time-critical applications. Concepts like in-network computing or edge computing can provide adequate communication quality for these industrial environments, and data plane programming has been proved as a useful mechanism for their implementation. Specifically, P4 language is used for the definition of the behavior of programmable switches and network elements. This paper presents a solution for industrial IoT (IIoT) network communications to reduce response times using in-network computing through data plane programming and P4. Our solution processes Message Queuing Telemetry Transport (MQTT) packets sent by a sensor in the data plane and generates an alarm in case of exceeding a threshold in the measured value. The implementation has been tested in an experimental facility, using a Netronome SmartNIC as a P4 programmable network device. Response times are reduced by 74% while processing, and delay introduced by the P4 network processing is insignificant. View Full-Text

Industry 4.0 heavily builds on massive deployment of Industrial Internet of Things (IIoT) devices to monitor every aspect of the manufacturing processes. Since the data gathered by these devices impact the output of critical processes, identity management and communications security are critical aspects, which commonly rely on the deployment of X.509 certificates. Nevertheless, the provisioning and management of individual certificates for a high number of IIoT devices involves important challenges. In this paper, we present a solution to improve the management of digital certificates in IIoT environments, which relies on partially delegating the certificate enrolment process to an edge server. However, in order to preserve end-to-end security, private keys are never delegated. Additionally, for the protection of the communications between the edge server and the IIoT devices, an approach based on Identity Based Cryptography is deployed. The proposed solution considers also the issuance of very short-lived certificates, which reduces the risk of using expired or compromised certificates, and avoids the necessity of implementing performance expensive protocols such as Online Certificate Status Protocol (OCSP). The proposed solution has been successfully tested as an efficient identity management solution for IIoT environments in a real industrial environment.

The market prediction for network deployments has positioned Software-Defined Networks (SDN) as the first of the options for changing local, transport, or cloud networks. Since the OpenFlow protocol gained traction and evolved in the last versions, the possibilities for expanding network capabilities to deploy custom services have risen considerably. With next-generation SDN (NG-SDN), flexibility has grown as data plane programming languages, such as P4, and Data-Control Plane Interface (DCPI) protocols like P4Runtime have appeared. Furthermore, the ability to program the data plane has opened the possibilities to develop new network telemetry approaches, such as In-band Network Telemetry (INT). A transition to partially incorporated SDN, also known as hybrid SDN, often involves considerable complexity, especially when legacy devices implement non-open standards and protocols. Therefore, incorporating programmable SDN devices and deploying network telemetry protocols on top of existing legacy devices is still challenging. This research focuses on deploying and integrating the INT protocol using programmable P4 switches over a hybrid SDN network. We describe and implement the required control plane applications and data plane configuration, and discuss the constraints that need to be managed so that P4 programmable switches can interact with the rest of the MPLS legacy devices. In this sense, we discuss P4 switch placement alternatives to maximize their performance and usability in a hybrid SDN network. Then, we validate the INT-based monitoring system by ensuring traffic forwarding using several INT header placements. In these tests, we demonstrate the feasibility of merging P4 switches running INT traffic and legacy devices, presenting the requirements to accomplish hybrid next-generation SDN (HNG-SDN) architectures. Besides, we provide new monitoring features, such as MPLS label verification, and we also use telemetry data to feed back traffic forwarding applications for traffic engineering purposes. We finally show the time that packets spend in the pipeline comparing different parsing and actions performed in different cases.

Electromagnetic (EM) disturbances and compatibility issues are the most common problems affecting communication and signaling systems. The duration of field testing to solve these railway EM interference (EMI) problems may vary between three and 12 months, with the cost of the complete process between €25,000 and €1.5 million [1]. Currently, the railway industry demands the building of strategies and tools to promote paths toward zero on-site testing [2] and reduce the duration of field tests; however, there is a lack of laboratory testing resources for these approaches.

The aim of this article is to present an architecture to support reconfigurable multimedia services for a practical emergency environment use case of rescue operations. Specifically, radio communication and video surveillance services are provided by means of a small device carried by a mobile vehicle. This solution is validated by implementing a digital mobile radio (DMR) standard radio hotspot and a video streaming server in an unmanned aerial vehicle (UAV) that conveys a device with scarce resources in order to minimize power consumption. To achieve a fast and flexible deployment of the envisioned services, a virtualization-based approach is proposed. Namely, a Kubernetes orchestrator is used to manage the life-cycle of services deployed on a small resource device, endowing the architecture with scalability and management flexibility. This article describes the executed performance tests that measured key parameters such as deployment time and recovery time after disconnection. Highly promising results were obtained, showing that the proposed architecture can be deployed in less than 4 minutes and can recover from network disconnections in less than 10 seconds. Thus, the performance, reliability and flexibility of the overall solution are demonstrated.

The Industry 4.0 revolution envisions fully interconnected scenarios in the manufacturing industry to improve the efficiency, quality, and performance of the manufacturing processes. In parallel, the consolidation of 5G technology is providing substantial advances in the world of communication and information technologies. Furthermore, 5G also presents itself as a key enabler to fulfill Industry 4.0 requirements. In this article, the authors first propose a 5G-enabled architecture for Industry 4.0. Smart Networks for Industry (SN4I) is introduced, an experimental facility based on two 5G key-enabling technologies—Network Functions Virtualization (NFV) and Software-Defined Networking (SDN)—which connects the University of the Basque Country’s Aeronautics Advanced Manufacturing Center and Faculty of Engineering in Bilbao. Then, the authors present the deployment of a Wireless Sensor Network (WSN) with strong access control mechanisms into such architecture, enabling secure and flexible Industrial Internet of Things (IIoT) applications. Additionally, the authors demonstrate the implementation of a use case consisting in the monitoring of a broaching process that makes use of machine tools located in the manufacturing center, and of services from the proposed architecture. The authors finally highlight the benefits achieved regarding flexibility, efficiency, and security within the presented scenario and to the manufacturing industry overall. View Full-Text

Industry 4.0 uses a subset of the IoT, called Industrial IoT (IIoT) to achieve connectivity, interoperability and decentralisation. The deployment of industrial networks rarely considers security by design, but this becomes imperative in smart manufacturing as connectivity increases. The combination of OT and IT infrastructures in Industry 4.0 adds new security threats beyond those of traditional industrial networks. Defence-in-Depth (DiD) strategies tackle the complexity of this problem by providing multiple defence layers, each of these focusing on a particular set of threats. Additionally, the severe requirements of IIoT networks demand lightweight encryption algorithms. Nevertheless, these ciphers must provide E2E (End-to-End) security, as data pass through intermediate entities, or middleboxes, before reaching its destination. If compromised, middleboxes could expose vulnerable information to potential attackers if it is not encrypted throughout this path. This paper presents an analysis of the most relevant security strategies in Industry 4.0, focusing primarily on DiD. With these in mind, it proposes a combination of DiD, a lightweight E2E encryption algorithm called Attribute-Based-Encryption (ABE) and object security (i.e., OSCORE) to get a full E2E security approach. This analysis is a critical first step to develop more complex and lightweight security frameworks suitable for Industry 4.0.

Although the risk assessment discipline has been studied from long ago as a means to support security investment decision-making, no holistic approach exists to continuously and quantitatively analyze cyber risks in scenarios where attacks and defenses may target different parts of Internet of Things (IoT)-based smart grid systems. In this paper, we propose a comprehensive methodology that enables informed decisions on security protection for smart grid systems by the continuous assessment of cyber risks. The solution is based on the use of attack defense trees modelled on the system and computation of the proposed risk attributes that enables an assessment of the system risks by propagating the risk attributes in the tree nodes. The method allows system risk sensitivity analyses to be performed with respect to different attack and defense scenarios, and optimizes security strategies with respect to risk minimization. The methodology proposes the use of standard security and privacy defense taxonomies from internationally recognized security control families, such as the NIST SP 800-53, which facilitates security certifications. Finally, the paper describes the validation of the methodology carried out in a real smart building energy efficiency application that combines multiple components deployed in cloud and IoT resources. The scenario demonstrates the feasibility of the method to not only perform initial quantitative estimations of system risks but also to continuously keep the risk assessment up to date according to the system conditions during operation.