A System Architecture for Software-Defined Industrial Internet of Things

Wireless sensor networks have been a driving force of the Industrial Internet of Things (IIoT) advancement in the process control and manufacturing industry. The emergence of IIoT opens great potential for the ubiquitous field device connectivity and manageability with an integrated and standardized architecture from low-level device operations to high-level data-centric application interactions. This technological development requires software definability in the key architectural elements of IIoT, including wireless field devices, IIoT gateways, network infrastructure, and IIoT sensor cloud services. In this paper, a novel software-defined IIoT (SD-IIoT) is proposed in order to solve essential challenges in a holistic IIoT system, such as reliability, security, timeliness scalability, and quality of service (QoS). A new IIoT system architecture is proposed based on the latest networking technologies such as WirelessHART, WebSocket, IETF constrained application protocol (CoAP) and software-defined networking (SDN). A new scheme based on CoAP and SDN is proposed to solve the QoS issues. Computer experiments in a case study are implemented to show the effectiveness of the proposed system architecture.Comment: To be published by IEEE ICUWB-201

Intrusion Detection Framework for Industrial Internet of Things Using Software Defined Network

The Industrial Internet of Things (IIoT) refers to the employment of the Internet of Things in industrial management, where a substantial number of machines and devices are linked and synchronized with the help of software programs and third platforms to improve the overall productivity. The acquisition of the industrial IoT provides benefits that range from automation and optimization to eliminating manual processes and improving overall efficiencies, but security remains to be forethought. The absence of reliable security mechanisms and the magnitude of security features are significant obstacles to enhancing IIoT security. Over the last few years, alarming attacks have been witnessed utilizing the vulnerabilities of the IIoT network devices. Moreover, the attackers can also sink deep into the network by using the relationships amidst the vulnerabilities. Such network security threats cause industries and businesses to suffer financial losses, reputational damage, and theft of important information. This paper proposes an SDN-based framework using machine learning techniques for intrusion detection in an industrial IoT environment. SDN is an approach that enables the network to be centrally and intelligently controlled through software applications. In our framework, the SDN controller employs a machine-learning algorithm to monitor the behavior of industrial IoT devices and networks by analyzing traffic flow data and ultimately determining the flow rules for SDN switches. We use SVM and Decision Tree classification models to analyze our framework’s network intrusion and attack detection performance. The results indicate that the proposed framework can detect attacks in industrial IoT networks and devices with an accuracy of 99.7%

A framework for deriving semantic web services

Web service-based development represents an emerging approach for the development of distributed information systems. Web services have been mainly applied by software practitioners as a means to modularize system functionality that can be offered across a network (e.g., intranet and/or the Internet). Although web services have been predominantly developed as a technical solution for integrating software systems, there is a more business-oriented aspect that developers and enterprises need to deal with in order to benefit from the full potential of web services in an electronic market. This ‘ignored’ aspect is the representation of the semantics underlying the services themselves as well as the ‘things’ that the services manage. Currently languages like the Web Services Description Language (WSDL) provide the syntactic means to describe web services, but lack in providing a semantic underpinning. In order to harvest all the benefits of web services technology, a framework has been developed for deriving business semantics from syntactic descriptions of web services. The benefits of such a framework are two-fold. Firstly, the framework provides a way to gradually construct domain ontologies from previously defined technical services. Secondly, the framework enables the migration of syntactically defined web services toward semantic web services. The study follows a design research approach which (1) identifies the problem area and its relevance from an industrial case study and previous research, (2) develops the framework as a design artifact and (3) evaluates the application of the framework through a relevant scenario

Software-defined cloud manufacturing for industry 4.0

AbstractMany of the world's leading industrial nations have invested in national initiatives to foster advanced manufacturing, innovation, and design for the globalized world. Much of this investment has been driven by visions such as Industry 4.0, striving to achieve a future where intelligent factories and smart manufacturing are the norm. Within this realm, innovations such as the Industrial Internet of Things, Cloud-based Design and Manufacturing (CBDM), and Social Product Development (SPD) have emerged with a focus on capitalizing on the benefits and economies of scale provided by Internet Protocol (IP) communication technologies. Another emerging idea is the notion of software-defined systems such as software-defined networks, which exploit abstraction and inexpensive hardware advancements in an effort to build more flexible systems. Recently, the authors have begun considering how the notion of software-defined systems might be harnessed to achieve flexible cloud manufacturing systems. As a result, this paper introduces the notion of Software-Defined Cloud Manufacturing (SDCM). We describe a basic SDCM architecture based on leveraging abstraction between manufacturing hardware and cloud-based applications, services, and platforms. The goal of SDCM is to advance Cloud-Based Manufacturing and other Industry 4.0 pillars by providing agility, flexibility, and adaptability while also reducing various complexity challenges

Isolating SDN Control Traffic with Layer-2 Slicing in 6TiSCH Industrial IoT Networks

Recent standardization efforts in IEEE 802.15.4-2015 Time Scheduled Channel Hopping (TSCH) and the IETF 6TiSCH Working Group (WG), aim to provide deterministic communications and efficient allocation of resources across constrained Internet of Things (IoT) networks, particularly in Industrial IoT (IIoT) scenarios. Within 6TiSCH, Software Defined Networking (SDN) has been identified as means of providing centralized control in a number of key situations. However, implementing a centralized SDN architecture in a Low Power and Lossy Network (LLN) faces considerable challenges: not only is controller traffic subject to jitter due to unreliable links and network contention, but the overhead generated by SDN can severely affect the performance of other traffic. This paper proposes using 6TiSCH tracks, a Layer-2 slicing mechanism for creating dedicated forwarding paths across TSCH networks, in order to isolate the SDN control overhead. Not only does this prevent control traffic from affecting the performance of other data flows, but the properties of 6TiSCH tracks allows deterministic, low-latency SDN controller communication. Using our own lightweight SDN implementation for Contiki OS, we firstly demonstrate the effect of SDN control traffic on application data flows across a 6TiSCH network. We then show that by slicing the network through the allocation of dedicated resources along a SDN control path, tracks provide an effective means of mitigating the cost of SDN control overhead in IEEE 802.15.4-2015 TSCH networks

SecureCyber: An SDN-Enabled SIEM for Enhanced Cybersecurity in the Industrial Internet of Things

The proliferation of smart technologies has undeniably brought forth numerous advantages. However, it has also introduced critical security issues and vulnerabilities that need to be addressed. In response, the development of appropriate and continuously adaptable countermeasures is essential to ensure the uninterrupted operation of critical environments. This paper presents an innovative approach through the introduction of an Software-Defined Networking (SDN)-enabled Security Information and Event Management (SIEM) system. The proposed SIEM solution effectively combines the power of Artificial Intelligence (AI) and SDN to protect Industrial Internet of Things (IIoT) applications. Leveraging AI capabilities, the SDN-enabled SIEM is capable of detecting a wide range of cyberattacks and anomalies that pose potential threats to IIoT environments. On the other hand, SDN plays a crucial role in mitigating identified risks and ensuring the security of IIoT applications. In particular, AI-driven insights and analysis guide the SDN-C in selecting appropriate mitigation actions to neutralize detected threats effectively. The experimental results demonstrate the efficiency of the proposed solution