A security and privacy preserving approach based on social IoT evolving encoding using convolutional neural network
One of the most popular technological frameworks of the year is without a certain Internet of Things (IoT). It permeates numerous industries and has a profound impact on people's lives in all spheres. The “Internet of everything” age is by the IoT technology's rapid development, but it als...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2024-01-01
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| Series: | Automatika |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/00051144.2023.2295143 |
| _version_ | 1797358094267711488 |
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| author | Maniveena C R. Kalaiselvi |
| author_facet | Maniveena C R. Kalaiselvi |
| author_sort | Maniveena C |
| collection | DOAJ |
| description | One of the most popular technological frameworks of the year is without a certain Internet of Things (IoT). It permeates numerous industries and has a profound impact on people's lives in all spheres. The “Internet of everything” age is by the IoT technology's rapid development, but it also alters the function of terminal equipment at the network's edge. The name “Internet of Things” has evolved as a result enabling things to be intelligent and competent in talking with verified devices (IoT). Between smart devices, social IoT (IoT) devices interact and adopt social networking concepts. It takes a secure connection between the smart gadgets to enable sociability. To determine whether the suggested strategy is practical it is applied to a convolutional neural network (CNN)-based language similarity analysis model in the context. The model created using the encounter training method is more accurate than the original CNN. |
| first_indexed | 2024-03-08T14:54:51Z |
| format | Article |
| id | doaj.art-f08e536b429f4b9daf9df1669b05598b |
| institution | Directory Open Access Journal |
| issn | 0005-1144 1848-3380 |
| language | English |
| last_indexed | 2024-03-08T14:54:51Z |
| publishDate | 2024-01-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Automatika |
| spelling | doaj.art-f08e536b429f4b9daf9df1669b05598b2024-01-10T17:14:59ZengTaylor & Francis GroupAutomatika0005-11441848-33802024-01-0165132333210.1080/00051144.2023.2295143A security and privacy preserving approach based on social IoT evolving encoding using convolutional neural networkManiveena C0R. Kalaiselvi1Department of Computer Science and Engineering, Noorul Islam Centre for Higher Education, Kumaracoil, IndiaDepartment of Computer Science and Engineering, RMK College of Engineering and Technology, Gummidipoondi, IndiaOne of the most popular technological frameworks of the year is without a certain Internet of Things (IoT). It permeates numerous industries and has a profound impact on people's lives in all spheres. The “Internet of everything” age is by the IoT technology's rapid development, but it also alters the function of terminal equipment at the network's edge. The name “Internet of Things” has evolved as a result enabling things to be intelligent and competent in talking with verified devices (IoT). Between smart devices, social IoT (IoT) devices interact and adopt social networking concepts. It takes a secure connection between the smart gadgets to enable sociability. To determine whether the suggested strategy is practical it is applied to a convolutional neural network (CNN)-based language similarity analysis model in the context. The model created using the encounter training method is more accurate than the original CNN.https://www.tandfonline.com/doi/10.1080/00051144.2023.2295143Social IoTConvolutional neural networklanguage similarity analysis |
| spellingShingle | Maniveena C R. Kalaiselvi A security and privacy preserving approach based on social IoT evolving encoding using convolutional neural network Automatika Social IoT Convolutional neural network language similarity analysis |
| title | A security and privacy preserving approach based on social IoT evolving encoding using convolutional neural network |
| title_full | A security and privacy preserving approach based on social IoT evolving encoding using convolutional neural network |
| title_fullStr | A security and privacy preserving approach based on social IoT evolving encoding using convolutional neural network |
| title_full_unstemmed | A security and privacy preserving approach based on social IoT evolving encoding using convolutional neural network |
| title_short | A security and privacy preserving approach based on social IoT evolving encoding using convolutional neural network |
| title_sort | security and privacy preserving approach based on social iot evolving encoding using convolutional neural network |
| topic | Social IoT Convolutional neural network language similarity analysis |
| url | https://www.tandfonline.com/doi/10.1080/00051144.2023.2295143 |
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