Optimal Deep Learning-based Cyberattack Detection and Classification Technique on Social Networks

被引:13
作者
Albraikan, Amani Abdulrahman [1 ]
Hassine, Siwar Ben Haj [2 ]
Fati, Suliman Mohamed [3 ]
Al-Wesabi, Fahd N. [2 ,4 ]
Hilal, Anwer Mustafa [5 ]
Motwakel, Abdelwahed [5 ]
Hamza, Manar Ahmed [5 ]
Al Duhayyim, Mesfer [6 ]
机构
[1] Princess Nourah Bint Abdulrahman Univ, Coll Comp & Informat Sci, Dept Comp Sci, Riyadh 11671, Saudi Arabia
[2] King Khalid Univ, Coll Sci & Arts, Dept Comp Sci, Mahayil Asir, Saudi Arabia
[3] Prince Sultan Univ, Coll Comp & Informat Sci, Dept Informat Syst, Riyadh, Saudi Arabia
[4] Sanaa Univ, Fac Comp & IT, Sanaa, Yemen
[5] Prince Sattam Bin Abdulaziz Univ, Preparatory Year Deanship, Dept Comp & Self Dev, Alkharj, Saudi Arabia
[6] Prince Sattam Bin Abdulaziz Univ, Coll Community Aflaj, Dept Nat & Appl Sci, Alkharj, Saudi Arabia
来源
CMC-COMPUTERS MATERIALS & CONTINUA | 2022年 / 72卷 / 01期
关键词
Cybersecurity; cyberbullying; social networks; parameter tuning; deep learning; metaheuristics; MODEL;
D O I
10.32604/cmc.2022.024488
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Cyberbullying (CB) is a distressing online behavior that disturbs mental health significantly. Earlier studies have employed statistical and Machine Learning (ML) techniques for CB detection. With this motivation, the current paper presents an Optimal Deep Learning-based Cyberbullying Detection and Classification (ODL-CDC) technique for CB detection in social networks. The proposed ODL-CDC technique involves different processes such as pre-processing, prediction, and hyperparameter optimization. In addition, GloVe approach is employed in the generation of word embedding. Besides, the pre-processed data is fed into Bidirectional Gated Recurrent tuning of BiGRNN model is carried out with the help of Search and Rescue Optimization (SRO) algorithm. In order to validate the improved classification performance of ODL-CDC technique, a comprehensive experimental analysis was carried out upon benchmark dataset and the results were inspected under varying aspects. A detailed comparative study portrayed the superiority of the proposed ODL-CDC technique over recent techniques, in terms of performance, with the maximum accuracy of 92.45%.
引用
收藏
页码:907 / 923
页数:17
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