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Cited by 41Network Security and Intrusion DetectionInternet of Things and AIIoT and Edge/Fog Computing

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Prevention of Cyber Security with the Internet of Things Using Particle Swarm Optimization

Open access
Alterazi, Hassan A., Kshirsagar, Pravin R., Manoharan, Hariprasath, Selvarajan, Shitharth, Alhebaishi, Nawaf, Srivastava, Gautam, Lin, Jerry Chun-Wei·2022·Sensors
DOI 10.3390/s22166117PMC PMC9413110
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Abstract

High security for physical items such as intelligent machinery and residential appliances is provided via the Internet of Things (IoT). The physical objects are given a distinct online address known as the Internet Protocol to communicate with the network’s external foreign entities through the Internet (IP). IoT devices are in danger of security issues due to the surge in hacker attacks during Internet data exchange. If such strong attacks are to create a reliable security system, attack detection is essential. Attacks and abnormalities such as user-to-root (U2R), denial-of-service, and data-type probing could have an impact on an IoT system. This article examines various performance-based AI models to predict attacks and problems with IoT devices with accuracy. Particle Swarm Optimization (PSO), genetic algorithms, and ant colony optimization were used to demonstrate the effectiveness of the suggested technique concerning four different parameters. The results of the proposed method employing PSO outperformed those of the existing systems by roughly 73 percent.

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Metadata

Authors
Alterazi, H. A., Kshirsagar, P. R., Manoharan, H., Selvarajan, S., Alhebaishi, N., Srivastava, G., & Lin, J. C.-W.
Affiliations
  • King Abdulaziz University (SA)
  • Raisoni Group of Institutions (IN)
  • Department of Electronics and Communication Engineering, Panimalar Engineering College, Poonamallee, Chennai 600123, India
  • Kebri Dehar University (ET)
  • China Medical University (TW)
  • Western Norway University of Applied Sciences (NO)
Corresponding author
Lin, Jerry Chun-Wei
ORCID
Venue
Sensors
Publisher
MDPI AG
Published
2022-08-16
Volume
22
Issue
16
Pages
6117
ISSN
1424-8220 (ISSN-L)
DOI
10.3390/s22166117
PMC
PMC9413110
OpenAlex
W4292263417
Cited by
41
References
1
Citations by year
2026: 2 · 2025: 12 · 2024: 12 · 2023: 13 · 2022: 2
FWCI
4.33
Type
journal article
Language
en
Open access
Licence
Locations
  • Sensors (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • NORA - Norwegian Open Research Archives (submittedVersion, cc-by)
Funders
Western Norway University of Applied Sciences, Bergen, Norway
Topics
  • Physical Sciences › Computer Science › Computer Networks and Communications › Network Security and Intrusion Detection
  • Physical Sciences › Computer Science › Information Systems › Internet of Things and AI
  • Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
Keywords
Internet of Things security, cyberattack detection, particle swarm optimization, user-to-root attacks, denial-of-service attacks, genetic algorithm, ant colony optimization, attack prediction
MeSH terms
Internet of Things, Data Collection, Computer Security, Internet

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