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Analyzing the influence of users, devices, and search engines on viral spread in the social internet of things
ID
Gan, Chenquan
(
Author
),
ID
Chen, Hongming
(
Author
),
ID
Qian, Yi
(
Author
),
ID
Tian, Liang
(
Author
),
ID
Zhu, Qingyi
(
Author
),
ID
Jain, Deepak Kumar
(
Author
),
ID
Štruc, Vitomir
(
Author
)
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https://www.sciencedirect.com/science/article/pii/S2542660525003567
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Abstract
The Social Internet of Things (SIoT) seamlessly integrates the Internet of Things (IoT) with social networks, intensifying the interconnections among objects, humans, and their interactions. While SIoT facilitates rapid information access and sharing through search engines, it also increases the risk of computer virus propagation. It is, therefore, critical to understand how viruses propagate in SIoT networks and which factors contribute the most to viral spread. While such understanding is of paramount importance, comprehensive studies on this topic are still limited in the literature. To address this gap, we study in this paper the long-term behavior of viral spread in SIoT, examining the roles of users, devices, and search engines. Specifically, we propose a novel dynamical virus propagation model that accounts for key factors, such as user awareness, device security levels, search engines, and external storage media. In comparison to competing solutions, the proposed model offers a unique perspective on viral spread in SIoT by focusing on multiple influential factors, their interactions, while also considering the inherent characteristics of the SIoT framework. A comprehensive theoretical analysis of the model is conducted to identify patterns and the key aspects of virus propagation in SIoT. To further validate the findings, a virus propagation algorithm is also designed, and multiple simulations are conducted on two real network datasets (Facebook and P2P), demonstrating the validity of the theoretical findings.
Language:
English
Keywords:
artificial intelligence
,
social networks
,
internet of things
,
viral spread
Work type:
Article
Typology:
1.01 - Original Scientific Article
Organization:
FE - Faculty of Electrical Engineering
Publication status:
Published
Publication version:
Version of Record
Year:
2026
Number of pages:
18 str.
Numbering:
Vol. 35, art. 101842
PID:
20.500.12556/RUL-177397
UDC:
004.8
ISSN on article:
2542-6605
DOI:
10.1016/j.iot.2025.101842
COBISS.SI-ID:
262607619
Publication date in RUL:
22.12.2025
Views:
31
Downloads:
2
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Record is a part of a journal
Title:
Internet of things
Publisher:
Elsevier B.V.
ISSN:
2542-6605
COBISS.SI-ID:
8909153
Licences
License:
CC BY 4.0, Creative Commons Attribution 4.0 International
Link:
http://creativecommons.org/licenses/by/4.0/
Description:
This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
Secondary language
Language:
Slovenian
Keywords:
umetna inteligenca
,
socialna omrežja
,
internet stvari
,
širjenje virusov
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