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Industrial Internet of Things (IIoT) plays an indispensable role for Industry 4.0, where people are committed to implement a general, scalable, and secure IIoT system to be adopted across various industries. However, existing IIoT systems are vulnerable to single point of failure and malicious attacks, which cannot provide stable services. Due to the resilience and security promise of blockchain, the idea of combining blockchain and Internet of Things (IoT) gains considerable interest. However, blockchains are power-intensive and low-throughput, which are not suitable for power-constrained IoT devices. To tackle these challenges, we present a blockchain system with credit-based consensus mechanism for IIoT. We propose a credit-based proof-of-work (PoW) mechanism for IoT devices, which can guarantee system security and transaction efficiency simultaneously. In order to protect sensitive data confidentiality, we design a data authority management method to regulate the access to sensor data. In addition, our system is built based on directed acyclic graph-structured blockchains, which is more efficient than the Satoshi-style blockchain in performance. We implement the system on Raspberry Pi, and conduct a case study for the smart factory. Extensive evaluation and analysis results demonstrate that creditbased PoW mechanism and data access control are secure and efficient in IIoT.

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Wireless process control has been a popular topic recently in the field of industrial control. In the industrial field, wireless technologies are considered despite the lack of an ideal industrial wireless standard. However, application development of industrial wireless networks is slow due to the lack of an ideal standard. Open standards are the foundation of industrial wireless application extensions. This paper first summarizes a standardized process for industrial wireless network technologies and then introduces network composition, network topology, protocol stack architecture, and some key protocol technologies of WIA-PA, which is an international specification of industrial wireless networks for process automation. Furthermore, a comparison between WIA-PA and other main industrial wireless network specifications like WirelessHART and ISA100.11a is provided. Architecture and key technologies of a WIA-PA are also introduced. Our first-hand experiences in developing WIA-PA testbed based on the modularization method are given. Finally, experiment results illustrate the performance and efficiency of WIA-PA.

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In this paper, a fully distributed hierarchical control strategy is proposed for operating networked gridsupporting inverters (GSIs) in islanded ac microgrids (MGs). The primary control level implements frequency and voltage control of an ac MG through a cascaded structure, consisting of a droop control loop, a virtual impedance control loop, a mixed H 2 /H ∞-based voltage control loop, and a sliding-mode-control-based current loop. Compared to conventional proportional-plus-integral-based cascaded control, the proposed cascaded control does not require a precise model for the GSI system. The proposed secondary control level implements distributed-consensus-based economic automatic generation control and distributed automatic voltage control, which integrates the conventional secondary control and tertiary control into a single control level by bridging a gap between traditional secondary control and tertiary control. Simulation results demonstrate the effectiveness of the proposed hierarchical control strategy. Index Terms-Automatic voltage control (AVC), distributed consensus, distributed hierarchical control, droop control, economic automatic generation control (EAGC), grid-supporting inverter (GSI).

Abstract-Due to the growing dependencies of information network technology, networked control systems are undergoing a severe blow of cyberattacks, and simply modeling cyberattacks is inadequate and impractical for the detection requirements, because of various vulnerabilities in these systems and the diversities of cyberattacks. Actually, a feasible viewpoint is to identify misbehaviors by constructing a normal model of industrial communication behaviors. However, one of the chief difficulties is how to completely and appropriately summarize industrial communication behaviors according to the specific communication characteristics. In view of process control and data acquisition, this paper associates industrial communication characteristics with the time sequence, and further extracts two distinct behaviors: function control behavior and process data behavior. Based on these double behavior characteristics, we introduce one-class classification to detect the corresponding anomalies, respectively. Besides, we also present the weighted mixed Kernel function and parameter optimization method to improve classification performance. Experimental results clearly demonstrate that the proposed approach has significant advantages of classification accuracy and detection efficiency.Index Terms-Function control behavior, process data behavior, one-class classification, networked control systems.