Original scientific paper
https://doi.org/10.1080/00051144.2023.2295143
A security and privacy preserving approach based on social IoT evolving encoding using convolutional neural network
C Maniveena
; Department of Computer Science and Engineering, Noorul Islam Centre for Higher Education, Kumaracoil, India
*
R. Kalaiselvi
; Department of Computer Science and Engineering, RMK College of Engineering and Technology, Gummidipoondi, India
* Corresponding author.
Abstract
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.
Keywords
Social IoT; Convolutional neural network; language similarity analysis
Hrčak ID:
322976
URI
Publication date:
8.1.2024.
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