Distributed Watchdogs Based on Blockchain for Securing Industrial Internet of Things

The Industrial Internet of Things (IIoT) could enhance automation and analytics in industrial environments. Despite the promising benefits of IIoT, securely managing software updates is a challenging problem for those critical applications. This is due to at least the intrinsic lack of software protection mechanisms in legacy industrial systems. In this paper, to address the challenges in building a secure software supply chain for industrial environments, we propose a new approach that leverages distributed watchdogs with blockchain systems in protecting software supply chains. For this purpose, we bind every entity with a unique identity in the blockchain and employ the blockchain as a delegated authenticator by mapping every reporting action to a non-fungible token transfer. Moreover, we present a detailed specification to clearly define the behavior of systems and to apply model checking.

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Security standard compliance and continuous verification for Industrial Internet of Things

International Journal of Distributed Sensor Networks ◽

10.1177/1550147720922731 ◽

2020 ◽

Vol 16 (6) ◽

pp. 155014772092273 ◽

Cited By ~ 1

Author(s):

Ani Bicaku ◽

Markus Tauber ◽

Jerker Delsing

Keyword(s):

Internet Of Things ◽

Best Practice ◽

Automatic Monitoring ◽

Industrial Internet Of Things ◽

Industrial Systems ◽

Best Practice Guidelines ◽

Industrial Internet ◽

Security Standard ◽

Compliance Verification ◽

Security Compliance

Due to globalization and digitalization of industrial systems, standard compliance is gaining more attention. In order to stay competitive and remain in business, different sectors within industry are required to comply with multiple regulations. Compliance aims to fulfill regulations by including all measures imposed by laws and standards. Every device, application, or service implements several technologies at many levels, and standards support interoperability across them. They help to create global markets for industries and enable networked development in order to be successful and sustainable. This work highlights the importance of standard compliance and continuous verification in industrial Internet of Things and implements an automatic monitoring and standard compliance verification framework. In this work, we focus on security, safety, and organizational aspects of industrial Internet of Things. We identify a number of standards and best practice guidelines, which are used to extract security, safety, and organizational measurable indicator points. In addition, a metric model is provided that forms the basis for the necessary information needed for compliance verification, including requirements, standards, and metrics. Also, we present the prototype of the monitoring and standard compliance verification framework used to show the security compliance of an industrial Internet of Things use case.

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Security Issues and Software Updates Management in the Industrial Internet of Things (IIoT) Era

Sensors ◽

10.3390/s20247160 ◽

2020 ◽

Vol 20 (24) ◽

pp. 7160

Author(s):

Imanol Mugarza ◽

Jose Luis Flores ◽

Jose Luis Montero

Keyword(s):

Internet Of Things ◽

Business Models ◽

Service Providers ◽

Leading Edge ◽

Cyber Attacks ◽

Industrial Internet Of Things ◽

Safety Standards ◽

Security Issues ◽

Industrial Internet ◽

Software Updates

New generation Industrial Automation and Control Systems (IACS) are providing advanced connectivity features, enabling new automation applications, services and business models in the Industrial Internet of Things (IIoT) era. Nevertheless, due to the extended attack surface and increasing number of cyber-attacks against industrial equipment, security concerns arise. Hence, these systems should provide enough protection and resiliency against cyber-attacks throughout their entire lifespan, which, in the case of industrial systems, may last several decades. A sound and complete management of security issues and software updates is fundamental to achieve such goal, since leading-edge security countermeasures implemented in the development phase may eventually become out-of-date. In this article, a review of the IEC 62443 industrial security standard concerning the security maintenance of IIoT systems and components is given, along with guidelines for the implementation of such processes. As concluded, the security issues and software updates management shall jointly be addressed by the asset owner, service providers and product suppliers. These security processes should also be compatible with the safety procedures established by safety standards.

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Mitigating Self-Heating in Solid State Drives for Industrial Internet-of-Things Edge Gateways

Electronics ◽

10.3390/electronics9071179 ◽

2020 ◽

Vol 9 (7) ◽

pp. 1179

Author(s):

Cristian Zambelli ◽

Lorenzo Zuolo ◽

Luca Crippa ◽

Rino Micheloni ◽

Piero Olivo

Keyword(s):

Solid State ◽

Internet Of Things ◽

Data Storage ◽

Storage Temperature ◽

Nand Flash ◽

Solid State Drives ◽

Industrial Internet Of Things ◽

Self Heating ◽

Industrial Internet ◽

Protection Mechanisms

Data storage in the Industrial Internet-of-Things scenario presents critical aspects related to the necessity of bringing storage devices closer to the point where data are captured. Concerns on storage temperature are to be considered especially when Solid State Drives (SSD) based on 3D NAND Flash technology are part of edge gateway architectures. Indeed, self-heating effects caused by oppressive storage demands combined with harsh environmental conditions call for proper handling at multiple abstraction levels to minimize severe performance slow downs and reliability threats. In this work, with the help of a SSD co-simulation environment that is stimulated within a realistic Industrial Internet-of-Things (IIoT) workload, we explore a methodology orthogonal to performance throttling that can be applied in synergy with the operating system of the host. Results evidenced that by leveraging on the SSD micro-architectural parameters of the queuing system it is possible to reduce the Input/Output operations Per Second (IOPS) penalty due to temperature protection mechanisms with minimum effort by the system. The methodology presented in this work opens further optimization tasks and algorithmic refinements for SSD and system designers not only in the IIoT market segment, but generally in all areas where storage power consumption is a concern.

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Reliability Evaluation Model Of Industrial Internet Of Things Systems

PROCEEDING INTERNATIONAL CONFERENCE ON ENGINEERING ◽

10.36728/icone.v1i1.1266 ◽

2020 ◽

Vol 1 (1) ◽

pp. 22-24

Author(s):

Dong-Seong Kim

Keyword(s):

Internet Of Things ◽

Performance Indicator ◽

Evaluation Model ◽

Industrial Internet Of Things ◽

Research Issues ◽

Industrial Systems ◽

Performance Accuracy ◽

Industrial Internet ◽

Industrial Iot ◽

Robust Systems

The Industrial Internet of Things (IIoT) allows digitizing manufacturing processes and increasing the digital connectivity of smart factory and industrial systems. The reliability of a system is considered as a key performance indicator that defines how accurately and perfectly the system works. Ensuring reliability in industrial IoT exposes several challenges as well as promising opportunities for advancing technologies and systematic designs such as algorithms, architectures, and devices. It depends on several factors, for example, ensuring performance, accuracy, stability, and availability. This article provides a systematic model for evaluating the reliability of IIoT systems. This model enables elucidate several open research issues regarding designing the reliable and robust systems.

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Automatic Configuration of OPC UA for Industrial Internet of Things Environments

Electronics ◽

10.3390/electronics8060600 ◽

2019 ◽

Vol 8 (6) ◽

pp. 600 ◽

Cited By ~ 7

Author(s):

Jose Miguel Gutierrez-Guerrero ◽

Juan Antonio Holgado-Terriza

Keyword(s):

Internet Of Things ◽

Data Exchange ◽

Software Systems ◽

Industrial Internet Of Things ◽

Human Errors ◽

Industrial Systems ◽

Modbus Protocol ◽

Industrial Internet ◽

Ethernet Network ◽

Ole For Process Control

Software technologies play an increasingly significant role in industrial environments, especially for the adoption of Industrial Internet of Things (IIoT). In this context, the application of mechanisms for the auto-configuration of industrial systems may be relevant for reducing human errors and costs in terms of time and money, improving the maintenance and the quality control. OPC UA (OLE for Process Control Unified Architecture) systems are usually integrated into an industrial system to provide a standard way for setting a secure and reliable data exchange between industrial devices of multiple vendors and software systems. In this paper, a novel mechanism for the auto-configuration of OPC UA systems is proposed from an initial setup of industrial devices interconnected to a basic Ethernet network. The auto-configuration of the OPC UA is self-managed over the TCP/IP protocol. This mechanism allows automating the configuration process of the OPC UA server automatically from the programmable logic controller (PLC) devices connected to a basic Ethernet network. Once the PLC devices are identified, they exchange information directly with OPC using a Modbus protocol over the same Ethernet network. To test the feasibility of this approach, a case study is prepared and evaluated.

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An Integrated Legacy of Modbus Devices to Industrial Internet of Things: Approach for Smart Industries

10.31219/osf.io/54tje ◽

2020 ◽

Author(s):

Karthik Muthineni

Keyword(s):

Internet Of Things ◽

Industrial Revolution ◽

Digital Technologies ◽

Industrial Internet Of Things ◽

Intelligent Decision Making ◽

Internet Of Everything ◽

Industrial Internet ◽

Intelligent Decision ◽

Network Platform ◽

Smart Factories

The new industrial revolution Industry 4.0, connecting manufacturing process with digital technologies that can communicate, analyze, and use information for intelligent decision making includes Industrial Internet of Things (IIoT) to help manufactures and consumers for efficient controlling and monitoring. This work presents the design and implementation of an IIoT ecosystem for smart factories. The design is based on Siemens Simatic IoT2040, an intelligent industrial gateway that is connected to modbus sensors publishing data onto Network Platform for Internet of Everything (NETPIE). The design demonstrates the capabilities of Simatic IoT2040 by taking Python, Node-Red, and Mosca into account that works simultaneously on the device.

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MONITORING AND PREDICTIVE ANALYTICS OF TECHNOLOGICAL EQUIPMENT ON THE BASED OF INDUSTRIAL INTERNET OF THINGS

ВЕСТНИК ВОРОНЕЖСКОГО ГОСУДАРСТВЕННОГО ТЕХНИЧЕСКОГО УНИВЕРСИТЕТА ◽

10.36622/vstu.2020.16.5.001 ◽

2020 ◽

pp. 7-12

Author(s):

С.Л. Добрынин ◽

В.Л. Бурковский

Keyword(s):

Internet Of Things ◽

Data Acquisition ◽

Predictive Analytics ◽

Actual State ◽

Monitoring And Control ◽

Industrial Internet Of Things ◽

Machining Time ◽

Industrial Internet ◽

Acquisition Device ◽

Data Acquisition Device

Произведен обзор технологий в рамках концепции четвертой промышленной революции, рассмотрены примеры реализации новых моделей управления технологическими процессами на базе промышленного интернета вещей. Описано техническое устройство основных подсистем системы мониторинга и контроля, служащей для повышения осведомленности о фактическом состоянии производственных ресурсов в особенности станков и аддитивного оборудования в режиме реального времени. Архитектура предлагаемой системы состоит из устройства сбора данных (УСД), реализующего быстрый и эффективный сбор данных от станков и шлюза, передающего ликвидную часть информации в облачное хранилище для дальнейшей обработки и анализа. Передача данных выполняется на двух уровнях: локально в цехе, с использованием беспроводной сенсорной сети (WSN) на базе стека протоколов ZigBee от устройства сбора данных к шлюзам и от шлюзов в облако с использованием интернет-протоколов. Разработан алгоритм инициализации протоколов связи между устройством сбора данных и шлюзом, а также алгоритм выявления неисправностей в сети. Расчет фактического времени обработки станочных подсистем позволяет более эффективно планировать профилактическое обслуживание вместо того, чтобы выполнять задачи обслуживания в фиксированные интервалы без учета времени использования оборудования We carried out a review of technologies within the framework of the concept of the fourth industrial revolution; we considered examples of the implementation of new models of process control based on the industrial Internet of things. We described the technical structure of the main subsystems of the monitoring and control system to increase awareness of the actual state of production resources in particular machine tools and additive equipment in real time. The architecture of the proposed system consists of a data acquisition device (DAD) that implements fast and efficient data collection from machines and a gateway that transfers the liquid part of information to the cloud storage for further processing and analysis. We carried out the data transmission at two levels, locally in the workshop, using a wireless sensor network (WSN) based on ZigBee protocol stack from the data acquisition device to the gateways and from the gateways to the cloud using Internet protocols. An algorithm was developed for initializing communication protocols between a data acquisition device and a gateway, as well as an algorithm for detecting network malfunctions. Calculating the actual machining time of machine subsystems allows us to more efficiently scheduling preventive maintenance rather than performing maintenance tasks at fixed intervals without considering equipment usage

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