scholarly journals DLT Based Authentication Framework for Industrial IoT Devices

Sensors ◽  
2020 ◽  
Vol 20 (9) ◽  
pp. 2621
Author(s):  
Cristian Lupascu ◽  
Alexandru Lupascu ◽  
Ion Bica
Keyword(s):  
Cost Reduction ◽  
Industrial Sector ◽  
Cyber Attacks ◽  
Multiple Stakeholders ◽  
Manufacturing Efficiency ◽  
Industrial Internet ◽  
Industrial Iot ◽  
Architectural Framework ◽  
Security By Design ◽  
Iot Devices

The latest technological progress in the industrial sector has led to a paradigm shift in manufacturing efficiency and operational cost reduction. More often than not, this cost reduction comes at the price of dismissing information security, especially when multiple stakeholders are involved and the complexity increases. As a further matter, most of the legacy systems and smart factoring processes lack a security by design approach, making them highly vulnerable to cyber-attacks. Taking into consideration the aforementioned issues, we propose an architectural framework for Industrial Internet of Things (IIoT) that provides authentication and guaranteed integrity. Our proposal properly addresses the security by design principle while combining some of the emerging technologies like Secure Multi-Party Computation (SMPC) for grounded policy rules and Distributed Ledger Technology (DLT) for an immutable and transparent registry.

Decades of Internet of Things towards 21st Century: A Research-Based Introspective

2021 ◽  
Author(s):  
NAGAJAYANTHI BOOBALAKRISHNAN
Keyword(s):  
Internet Of Things ◽  
Cyber Attacks ◽  
Embedded Internet ◽  
Industrial Iot ◽  
Voice User ◽  
Block Chain ◽  
Iot Devices ◽  
Data Ecosystem ◽  
The Internet Of Things ◽  
Exchange Data

Abstract Internet connects people to people, people to machine, and machine to machine for a life of serendipity through a Cloud. Internet of Things networks objects or people and integrates them with software to collect and exchange data. The Internet of things (IoT) influences our lives based on how we ruminate, respond, and anticipate. IoT 2020 heralds from the fringes to the data ecosystem and panaches a comfort zone. IoT is overwhelmingly embraced by businessmen and consumers due to increased productivity and convenience. Internet of Things facilitates intelligent device control with cloud vendors like Amazon and Google using artificial intelligence for data analytics, and with digital assistants like Alexa and Siri providing a voice user interface. Smart IoT is all about duplex connecting, processing, and implementing. With 5G, lightning faster rate of streaming analytics is realistic. An amalgamation of technologies has led to this techno-industrial IoT revolution. Centralized IoT architecture is vulnerable to cyber-attacks. With Block Chain, it is possible to maintain transparency and security of the transaction's data. Standardization of IoT devices is achievable with limited vendors based on Platform, Connectivity, and Application. Robotic Process Automation (RPA) using bots has automated laborious tasks in 2019. Embedded Internet using Facial Recognition could reduce the pandemic crisis. Security concerns are addressed with micro-segmentation approaches. IoT, an incredible vision of the future makes systems adaptive with customized features, responsive with increased efficiency, and procurable with optimized cost. This paper delivers a comprehensive insight into the technical perspectives of IoT, focusing on interoperability, flexibility, scalability, mobility, security, transparency, standardization, and low energy.

Modular hardware platform for the development of industrial Internet of Things (IoT) devices

2021 ◽  
Vol 2021 (12) ◽  
pp. 20-25
Author(s):  
Vadim Putrolaynen ◽  
Maksim Belyaev ◽  
Dmitriy Kirienko ◽  
Pavel Lun'kov
Keyword(s):  
Primary Data ◽  
Industrial Internet Of Things ◽  
Hardware Platform ◽  
Platform Architecture ◽  
Industrial Internet ◽  
Industrial Iot ◽  
Distributed Array ◽  
Transmission Data ◽  
Iot Devices ◽  
Information Harvesting

The modular hardware platform architecture for the development of industrial IoT devices is presented as an example of information harvesting and its analysis. Variants of modules implementing typical functions of such devices are given: data acquisition from a distributed array of sensors; preprocessing, aggregation and data transmission; data mining; storage of primary data and analysis results.

A Reliable IDS System Using Blockchain for SDN-Enabled IIoT Systems

2021 ◽  
pp. 173-194
Author(s):  
Ambika N.
Keyword(s):  
Internet Of Things ◽  
Learning Strategy ◽  
Group Development ◽  
Subspace Learning ◽  
Blockchain Technology ◽  
Industrial Internet ◽  
Learning Procedure ◽  
Industrial Iot ◽  
Iot Devices ◽  
The Internet Of Things

The internet of things is the technology that aims to provide a common platform to the devices of varying capabilities to communicate. Industrial internet of things (IIoT) systems can perform better using these devices in combination with SDN network and blockchain technology. The suggestion uses random space learning (RSL) comprising three stages. The random subspace learning strategy is a troupe learning procedure called attributes bagging. It improves forecast and order errands as it utilizes group development of base classifiers rather than a solitary classifier, and it takes arbitrary subsets of properties rather than the whole arrangement of attributes. The system uses the blockchain methodology to secure the system. SDN networks aim to better the transmission of data in industrial IoT devices. Misrouting and forged attacks are some of the common attacks in these systems. The proposal provides better reliability than the previous contribution by 2.7%.

scholarly journals Searchable Encryption with Access Control in Industrial Internet of Things (IIoT)

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Jawhara Bader ◽  
Anna Lito Michala
Keyword(s):  
Internet Of Things ◽  
Manufacturing Process ◽  
State Of The Art ◽  
Industrial Sector ◽  
Monitoring Systems ◽  
Industrial Internet Of Things ◽  
Industrial Internet ◽  
Enhance Efficiency ◽  
Iot Devices ◽  
The Internet Of Things

The technological advancements in the Internet of Things (IoT) and related technologies lead to revolutionary advancements in many sectors. One of these sectors, is the industrial sector red that leverages IoT technologies forming the Industrial Internet of Things (IIoT). IIoT has the potential to enhance the manufacturing process by improving the quality, trace-ability, and integrity of the industrial processes. The enhancement of the manufacturing process is achieved by deploying IoT devices (sensors) across the manufacturing facilities; therefore, monitoring systems are required to collect (from multiple locations) and analyse the data, most likely in the cloud. As a result, IIoT monitoring systems should be secure, preserve the privacy, and provide real-time responses for critical decision-making. In this review, we identified a gap in the state-of-the-art of secure IIoT and propose a set of criteria for secure and privacy preserving IIoT systems to enhance efficiency and deliver better IIoT applications.

scholarly journals State-of-the-Art Software-Based Remote Attestation: Opportunities and Open Issues for Internet of Things

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1598
Author(s):  
Sigurd Frej Joel Jørgensen Ankergård ◽  
Edlira Dushku ◽  
Nicola Dragoni
Keyword(s):  
Internet Of Things ◽  
Smart Cities ◽  
Cyber Attacks ◽  
Resource Constrained ◽  
Remote Attestation ◽  
Comprehensive Overview ◽  
Research Issues ◽  
Advantages And Disadvantages ◽  
Iot Devices ◽  
Specialized Hardware

The Internet of Things (IoT) ecosystem comprises billions of heterogeneous Internet-connected devices which are revolutionizing many domains, such as healthcare, transportation, smart cities, to mention only a few. Along with the unprecedented new opportunities, the IoT revolution is creating an enormous attack surface for potential sophisticated cyber attacks. In this context, Remote Attestation (RA) has gained wide interest as an important security technique to remotely detect adversarial presence and assure the legitimate state of an IoT device. While many RA approaches proposed in the literature make different assumptions regarding the architecture of IoT devices and adversary capabilities, most typical RA schemes rely on minimal Root of Trust by leveraging hardware that guarantees code and memory isolation. However, the presence of a specialized hardware is not always a realistic assumption, for instance, in the context of legacy IoT devices and resource-constrained IoT devices. In this paper, we survey and analyze existing software-based RA schemes (i.e., RA schemes not relying on specialized hardware components) through the lens of IoT. In particular, we provide a comprehensive overview of their design characteristics and security capabilities, analyzing their advantages and disadvantages. Finally, we discuss the opportunities that these RA schemes bring in attesting legacy and resource-constrained IoT devices, along with open research issues.

Collaborative Platform for Remote Manufacturing Systems Using Industrial Internet and Digital Twin in the COVID-19 Era

2021 ◽  
Author(s):  
Jay Lee ◽  
Xiaodong Jia ◽  
Qibo Yang ◽  
Keyi Sun ◽  
Xiang Li
Keyword(s):  
Manufacturing Systems ◽  
Manufacturing System ◽  
The Real ◽  
Digital Twin ◽  
Manufacturing Efficiency ◽  
Industrial Internet ◽  
Industrial Operations ◽  
Promising Solution ◽  
Technology Group ◽  
Collaborative Platform

Abstract In the wake of COVID-19, significant influence on the manufacturing industries has been observed in the past year due to the restrictions of in-person communications and interactions. As a consequence, manufacturing efficiency has reduced remarkably all over the world. Despite the great harm to the industrial operations under the pandemic, the opportunities for remote collaborative manufacturing system also arise. Effective and efficient remote manufacturing systems for the real industries have been highly demanded. Through the integration of industrial internet and digital twin systems, the remote manufacturing system can be largely facilitated. This paper proposes a general framework for the remote manufacturing system during the COVID-19 era. The concept of the intelligent collaborative remote manufacturing system is firstly reviewed, as well as discussions of the current pandemic situation and its influence on the industries. The current commercial platforms of the systems are also presented. A case study on the lighthouse factories at the Foxconn Technology Group is finally presented for understanding the implementation of the proposed strategy. The effectiveness of the framework has been validated in the real industrial scenarios, and great economic and operational benefits have been obtained. The proposed framework offers a promising solution for the remote manufacturing system under the current pandemic.

A Smart Monitoring Industrial IOT Devices from Outsider Threats

2021 ◽  
pp. 913-923
Author(s):  
T. Anandhi ◽  
D. Radha Krishna ◽  
Koushik Pilli ◽  
P. Ajitha ◽  
A. Sivasangari ◽  
...  
Keyword(s):  
Industrial Iot ◽  
Iot Devices

scholarly journals Special Issue on New Industry 4.0 Advances in Industrial IoT and Visual Computing for Manufacturing Processes

2019 ◽  
Vol 9 (20) ◽  
pp. 4323 ◽  
Author(s):  
López de Lacalle ◽  
Posada
Keyword(s):  
Internet Of Things ◽  
Industry 4.0 ◽  
Research Community ◽  
Manufacturing Processes ◽  
Special Issue ◽  
Industrial Internet Of Things ◽  
Visual Computing ◽  
Industrial Internet ◽  
Industrial Iot ◽  
New Industry

The new advances of IIOT (Industrial Internet of Things), together with the progress in visual computing technologies, are being addressed by the research community with interesting approaches and results in the Industry 4.0 domain[...]

scholarly journals Towards Near-Real-Time Intrusion Detection for IoT Devices using Supervised Learning and Apache Spark

Electronics ◽  
2020 ◽  
Vol 9 (3) ◽  
pp. 444 ◽  
Author(s):  
Valerio Morfino ◽  
Salvatore Rampone
Keyword(s):  
Machine Learning ◽  
Random Forest ◽  
Learning Algorithms ◽  
Hybrid Approach ◽  
Cyber Attacks ◽  
Machine Learning Algorithms ◽  
Apache Spark ◽  
Identification Accuracy ◽  
Supervised Machine Learning ◽  
Iot Devices

In the fields of Internet of Things (IoT) infrastructures, attack and anomaly detection are rising concerns. With the increased use of IoT infrastructure in every domain, threats and attacks in these infrastructures are also growing proportionally. In this paper the performances of several machine learning algorithms in identifying cyber-attacks (namely SYN-DOS attacks) to IoT systems are compared both in terms of application performances, and in training/application times. We use supervised machine learning algorithms included in the MLlib library of Apache Spark, a fast and general engine for big data processing. We show the implementation details and the performance of those algorithms on public datasets using a training set of up to 2 million instances. We adopt a Cloud environment, emphasizing the importance of the scalability and of the elasticity of use. Results show that all the Spark algorithms used result in a very good identification accuracy (>99%). Overall, one of them, Random Forest, achieves an accuracy of 1. We also report a very short training time (23.22 sec for Decision Tree with 2 million rows). The experiments also show a very low application time (0.13 sec for over than 600,000 instances for Random Forest) using Apache Spark in the Cloud. Furthermore, the explicit model generated by Random Forest is very easy-to-implement using high- or low-level programming languages. In light of the results obtained, both in terms of computation times and identification performance, a hybrid approach for the detection of SYN-DOS cyber-attacks on IoT devices is proposed: the application of an explicit Random Forest model, implemented directly on the IoT device, along with a second level analysis (training) performed in the Cloud.

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