A Survey on Internet of Things (IoT): Layer-Specific, Domain-Specific and Industry-Defined Architectures

Kaur, Harmanjot; Kumar, Rohit

doi:10.1007/978-981-15-1275-9_22

Cited by 9 publications

(5 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Before delving into the solutions to IoT threats, attacks and problems, it is important to look at the various layers of the IoT architecture and the threats that are peculiar to them. This can be a daunting task as there are numerous ways that architectures have been classified according to layers [16,17] and domains [18][19][20], while some classifications are specific to the industries in which such architectures are used [21][22][23], as shown in Figure 1. Layer-specific architectures can feature between three and eight layers.…”

Section: Background Studymentioning

confidence: 99%

A Systematic Review of Data-Driven Attack Detection Trends in IoT

Haque

El-Moussa

Komninos

et al. 2023

Sensors

View full text Add to dashboard Cite

The Internet of Things is perhaps a concept that the world cannot be imagined without today, having become intertwined in our everyday lives in the domestic, corporate and industrial spheres. However, irrespective of the convenience, ease and connectivity provided by the Internet of Things, the security issues and attacks faced by this technological framework are equally alarming and undeniable. In order to address these various security issues, researchers race against evolving technology, trends and attacker expertise. Though much work has been carried out on network security to date, it is still seen to be lagging in the field of Internet of Things networks. This study surveys the latest trends used in security measures for threat detection, primarily focusing on the machine learning and deep learning techniques applied to Internet of Things datasets. It aims to provide an overview of the IoT datasets available today, trends in machine learning and deep learning usage, and the efficiencies of these algorithms on a variety of relevant datasets. The results of this comprehensive survey can serve as a guide and resource for identifying the various datasets, experiments carried out and future research directions in this field.

show abstract

Section: Background Studymentioning

confidence: 99%

A Systematic Review of Data-Driven Attack Detection Trends in IoT

Haque

El-Moussa

Komninos

et al. 2023

Sensors

View full text Add to dashboard Cite

show abstract

“…There were numerous IoT reference architectures proposed by diverse parties, making it difficult for a system builder to pick amongst them. Domain-specific architectures, layer-specific architectures and industrial/commercial defined architectures are the three basic ways to categorize IoT architectures [52] [60] [66] [67] [68].…”

Section: Architecturesmentioning

confidence: 99%

Internet of Things: Towards a Solid Ecosystem of Interconnected Things

Chakroun¹,

Sayah²,

Kallab³

et al. 2022

AIT

View full text Add to dashboard Cite

The Internet of Things (IoT) is a technological revolution that has changed everything we do and given us a new perspective on our daily lives, but despite the fact that numerous publications have focused on characterizing the many edges and technologies that make up an IoT system, the IoT ecosystem is still seen as too complex to be recognized as a stand-alone environment due to its significant diversity; hence, the objective of this research is to address such a complex environment in a way that highlights its components and distinguishes them both individually and in relation to their broader context. Therefore, the definition of IoT and its emergence were discussed and organized around the timeline of Internet development phases demonstrating that IoT has been a need that has accompanied the presence of the Internet since its early stages, and then its growth and impact were discussed and highlighted with estimates and numbers. On the technical side, each of the following groups, IoT components, protocols, and architectures, was defined, discussed, and grouped in such a way that their intergroup organization, as well as their placement and contribution to the overall ecosystem, was highlighted. This, in addition to the various examples mentioned throughout the discussion, will provide the reader with a better understanding of the Internet of Things and how deeply it has become entwined in our daily lives and routines as a result of its numerous applications.

show abstract

“…This layer connects the perception layer and edge layer using advanced communication technologies [19]. Two methods may be adopted for communication in this layer.…”

Section: Connectivity Layermentioning

confidence: 99%

Deep Learning for the Industrial Internet of Things (IIoT): A Comprehensive Survey of Techniques, Implementation Frameworks, Potential Applications, and Future Directions

Latif

Driss

Boulila

et al. 2021

Sensors

View full text Add to dashboard Cite

The Industrial Internet of Things (IIoT) refers to the use of smart sensors, actuators, fast communication protocols, and efficient cybersecurity mechanisms to improve industrial processes and applications. In large industrial networks, smart devices generate large amounts of data, and thus IIoT frameworks require intelligent, robust techniques for big data analysis. Artificial intelligence (AI) and deep learning (DL) techniques produce promising results in IIoT networks due to their intelligent learning and processing capabilities. This survey article assesses the potential of DL in IIoT applications and presents a brief architecture of IIoT with key enabling technologies. Several well-known DL algorithms are then discussed along with their theoretical backgrounds and several software and hardware frameworks for DL implementations. Potential deployments of DL techniques in IIoT applications are briefly discussed. Finally, this survey highlights significant challenges and future directions for future research endeavors.

show abstract

A Survey on Internet of Things (IoT): Layer-Specific, Domain-Specific and Industry-Defined Architectures

Cited by 9 publications

References 21 publications

A Systematic Review of Data-Driven Attack Detection Trends in IoT

A Systematic Review of Data-Driven Attack Detection Trends in IoT

Internet of Things: Towards a Solid Ecosystem of Interconnected Things

Deep Learning for the Industrial Internet of Things (IIoT): A Comprehensive Survey of Techniques, Implementation Frameworks, Potential Applications, and Future Directions

Contact Info

Product

Resources

About