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Spotted hyena optimizer with deep learning driven cybersecurity for social networks

Recent developments on Internet and social networking have led to the growth of aggressive language and hate speech. Online provocation, abuses, and attacks are widely termed cyberbullying (CB). The massive quantity of user generated content makes it difficult to recognize CB. Current advancements...

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Main Authors: Mustafa Hilal, Anwer, Hassan Abdalla Hashim, Aisha, G. Mohamed, Heba, A. Alharbi, Lubna, K. Nour, Mohamed, Mohamed, Abdullah, S. Almasoud, Ahmed, Motwakel, Abdelwahed
Format: Article
Language:English
English
Published: Tech Science Press 2023
Subjects:
TK7885 Computer engineering
Online Access:http://irep.iium.edu.my/101889/19/101889_Spotted%20hyena%20optimizer%20with%20deep%20learning%20driven%20cybersecurity%20for%20social%20networks.pdf
http://irep.iium.edu.my/101889/13/101889_Spotted%20hyena%20optimizer%20with%20deep%20learning%20driven%20cybersecurity%20for%20social%20networks_Scopus.pdf
http://irep.iium.edu.my/101889/
http://doi.org/10.32604/csse.2023.031181
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spelling my.iium.irep.1018892023-12-11T06:00:54Z http://irep.iium.edu.my/101889/ Spotted hyena optimizer with deep learning driven cybersecurity for social networks Mustafa Hilal, Anwer Hassan Abdalla Hashim, Aisha G. Mohamed, Heba A. Alharbi, Lubna K. Nour, Mohamed Mohamed, Abdullah S. Almasoud, Ahmed Motwakel, Abdelwahed TK7885 Computer engineering Recent developments on Internet and social networking have led to the growth of aggressive language and hate speech. Online provocation, abuses, and attacks are widely termed cyberbullying (CB). The massive quantity of user generated content makes it difficult to recognize CB. Current advancements in machine learning (ML), deep learning (DL), and natural language processing (NLP) tools enable to detect and classify CB in social networks. In this view, this study introduces a spotted hyena optimizer with deep learning driven cybersecurity (SHODLCS) model for OSN. The presented SHODLCS model intends to accomplish cybersecurity from the identification of CB in the OSN. For achieving this, the SHODLCS model involves data pre-processing and TF-IDF based feature extraction. In addition, the cascaded recurrent neural network (CRNN) model is applied for the identification and classification of CB. Finally, the SHO algorithm is exploited to optimally tune the hyperparameters involved in the CRNN model and thereby results in enhanced classifier performance. The experimental validation of the SHODLCS model on the benchmark dataset portrayed the better outcomes of the SHODLCS model over the recent approaches. Tech Science Press 2023 Article PeerReviewed application/pdf en http://irep.iium.edu.my/101889/19/101889_Spotted%20hyena%20optimizer%20with%20deep%20learning%20driven%20cybersecurity%20for%20social%20networks.pdf application/pdf en http://irep.iium.edu.my/101889/13/101889_Spotted%20hyena%20optimizer%20with%20deep%20learning%20driven%20cybersecurity%20for%20social%20networks_Scopus.pdf Mustafa Hilal, Anwer and Hassan Abdalla Hashim, Aisha and G. Mohamed, Heba and A. Alharbi, Lubna and K. Nour, Mohamed and Mohamed, Abdullah and S. Almasoud, Ahmed and Motwakel, Abdelwahed (2023) Spotted hyena optimizer with deep learning driven cybersecurity for social networks. Computer Systems Science and Engineering, 45 (2). pp. 2033-2047. ISSN 0267-6192 http://doi.org/10.32604/csse.2023.031181 10.32604/csse.2023.031181
institution Universiti Islam Antarabangsa Malaysia
building IIUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider International Islamic University Malaysia
content_source IIUM Repository (IREP)
url_provider http://irep.iium.edu.my/
language English
English
topic TK7885 Computer engineering
spellingShingle TK7885 Computer engineering
Mustafa Hilal, Anwer
Hassan Abdalla Hashim, Aisha
G. Mohamed, Heba
A. Alharbi, Lubna
K. Nour, Mohamed
Mohamed, Abdullah
S. Almasoud, Ahmed
Motwakel, Abdelwahed
Spotted hyena optimizer with deep learning driven cybersecurity for social networks
description Recent developments on Internet and social networking have led to the growth of aggressive language and hate speech. Online provocation, abuses, and attacks are widely termed cyberbullying (CB). The massive quantity of user generated content makes it difficult to recognize CB. Current advancements in machine learning (ML), deep learning (DL), and natural language processing (NLP) tools enable to detect and classify CB in social networks. In this view, this study introduces a spotted hyena optimizer with deep learning driven cybersecurity (SHODLCS) model for OSN. The presented SHODLCS model intends to accomplish cybersecurity from the identification of CB in the OSN. For achieving this, the SHODLCS model involves data pre-processing and TF-IDF based feature extraction. In addition, the cascaded recurrent neural network (CRNN) model is applied for the identification and classification of CB. Finally, the SHO algorithm is exploited to optimally tune the hyperparameters involved in the CRNN model and thereby results in enhanced classifier performance. The experimental validation of the SHODLCS model on the benchmark dataset portrayed the better outcomes of the SHODLCS model over the recent approaches.
format Article
author Mustafa Hilal, Anwer
Hassan Abdalla Hashim, Aisha
G. Mohamed, Heba
A. Alharbi, Lubna
K. Nour, Mohamed
Mohamed, Abdullah
S. Almasoud, Ahmed
Motwakel, Abdelwahed
author_facet Mustafa Hilal, Anwer
Hassan Abdalla Hashim, Aisha
G. Mohamed, Heba
A. Alharbi, Lubna
K. Nour, Mohamed
Mohamed, Abdullah
S. Almasoud, Ahmed
Motwakel, Abdelwahed
author_sort Mustafa Hilal, Anwer
title Spotted hyena optimizer with deep learning driven cybersecurity for social networks
title_short Spotted hyena optimizer with deep learning driven cybersecurity for social networks
title_full Spotted hyena optimizer with deep learning driven cybersecurity for social networks
title_fullStr Spotted hyena optimizer with deep learning driven cybersecurity for social networks
title_full_unstemmed Spotted hyena optimizer with deep learning driven cybersecurity for social networks
title_sort spotted hyena optimizer with deep learning driven cybersecurity for social networks
publisher Tech Science Press
publishDate 2023
url http://irep.iium.edu.my/101889/19/101889_Spotted%20hyena%20optimizer%20with%20deep%20learning%20driven%20cybersecurity%20for%20social%20networks.pdf
http://irep.iium.edu.my/101889/13/101889_Spotted%20hyena%20optimizer%20with%20deep%20learning%20driven%20cybersecurity%20for%20social%20networks_Scopus.pdf
http://irep.iium.edu.my/101889/
http://doi.org/10.32604/csse.2023.031181
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score 13.211869

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