scholarly journals A Security Analysis Method for Industrial Internet of Things

2018 ◽  
Vol 14 (9) ◽  
pp. 4093-4100 ◽  
Author(s):  
Haralambos Mouratidis ◽  
Vasiliki Diamantopoulou
2021 ◽  
Vol 2021 ◽  
pp. 1-6
Author(s):  
Yuting Li ◽  
Qingfeng Cheng ◽  
Wenbo Shi

Internet of Things brings convenience to the social life, at the same time, putting forward higher requirements for the security of data transmission and storage. Security incidents based on industrial Internet of Things have occurred frequently recently, which should be given full consideration. The identity-based authenticated key agreement protocol can solve these security threats to a certain extent. Recently, a lightweight identity-based authenticated key agreement protocol for Industrial Internet of Things, called ID-2PAKA protocol, was claimed to achieve secure authentication and meet security properties. In this paper, we show that the ID-2PAKA protocol is insecure in identity authentication and cannot resisting ephemeral key compromise impersonation attack.


Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5166 ◽  
Author(s):  
Karanjeet Choudhary ◽  
Gurjot Singh Gaba ◽  
Ismail Butun ◽  
Pardeep Kumar

Continuous development of the Industrial Internet of Things (IIoT) has opened up enormous opportunities for the engineers to enhance the efficiency of the machines. Despite the development, many industry administrators still fear to use Internet for operating their machines due to untrusted nature of the communication channel. The utilization of internet for managing industrial operations can be widespread adopted if the authentication of the entities are performed and trust is ensured. The traditional schemes with their inherent security issues and other complexities, cannot be directly deployed to resource constrained network devices. Therefore, we have proposed a strong mutual authentication and secret key exchange protocol to address the vulnerabilities of the existing schemes. We have used various cryptography operations such as hashing, ciphering, and so forth, for providing secure mutual authentication and secret key exchange between different entities to restrict unauthorized access. Performance and security analysis clearly demonstrates that the proposed work is energy efficient (computation and communication inexpensive) and more robust against the attacks in comparison to the traditional schemes.


2021 ◽  
Vol 11 (20) ◽  
pp. 9393
Author(s):  
Shantanu Pal ◽  
Zahra Jadidi

Industrial Internet of Things (IIoT) can be seen as an extension of the Internet of Things (IoT) services and applications to industry with the inclusion of Industry 4.0 that provides automation, reliability, and control in production and manufacturing. IIoT has tremendous potential to accelerate industry automation in many areas, including transportation, manufacturing, automobile, marketing, to name a few places. When the benefits of IIoT are visible, the development of large-scale IIoT systems faces various security challenges resulting in many large-scale cyber-attacks, including fraudulent transactions or damage to critical infrastructure. Moreover, a large number of connected devices over the Internet and resource limitations of the devices (e.g., battery, memory, and processing capability) further pose challenges to the system. The IIoT inherits the insecurities of the traditional communication and networking technologies; however, the IIoT requires further effort to customize the available security solutions with more focus on critical industrial control systems. Several proposals discuss the issue of security, privacy, and trust in IIoT systems, but comprehensive literature considering the several aspects (e.g., users, devices, applications, cascading services, or the emergence of resources) of an IIoT system is missing in the present state of the art IIoT research. In other words, the need for considering a vision for securing an IIoT system with broader security analysis and its potential countermeasures is missing in recent times. To address this issue, in this paper, we provide a comparative analysis of the available security issues present in an IIoT system. We identify a list of security issues comprising logical, technological, and architectural points of view and consider the different IIoT security requirements. We also discuss the available IIoT architectures to examine these security concerns in a systematic way. We show how the functioning of different layers of an IIoT architecture is affected by various security issues and report a list of potential countermeasures against them. This study also presents a list of future research directions towards the development of a large-scale, secure, and trustworthy IIoT system. The study helps understand the various security issues by indicating various threats and attacks present in an IIoT system.


2020 ◽  
Author(s):  
Karthik Muthineni

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.


Author(s):  
С.Л. Добрынин ◽  
В.Л. Бурковский

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


2021 ◽  
Vol 173 ◽  
pp. 150-159
Author(s):  
Keming Mao ◽  
Gautam Srivastava ◽  
Reza M. Parizi ◽  
Mohammad S. Khan

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