RETRACTED: Feature Selection Model Based on Gorilla Troops Optimizer for Intrusion Detection Systems (Retracted Article)

被引:16
|
作者
Ahmed, Ibrahim [1 ]
Dahou, Abdelghani [2 ]
Chelloug, Samia Allaoua [3 ]
Al-qaness, Mohammed A. A. [4 ]
Abd Elaziz, Mohamed [5 ,6 ,7 ]
机构
[1] Zagazig Univ, Fac Sci, Dept Math, Zagazig 44519, Egypt
[2] Univ Ahmed DRAIA, Math & Comp Sci Dept, Adrar 01000, Algeria
[3] Princess Nourah bint Abdulrahman Univ, Coll Comp & Informat Sci, Dept Informat Technol, POB 84428, Riyadh 11671, Saudi Arabia
[4] Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan 430079, Peoples R China
[5] Galala Univ, Fac Comp Sci & Engn, Suze 435611, Egypt
[6] Ajman Univ, Artificial Intelligence Res Ctr AIRC, Ajman 346, U Arab Emirates
[7] Zagazig Univ, Fac Sci, Zagazig 44519, Egypt
关键词
SWARM OPTIMIZATION; ALGORITHM; NETWORK;
D O I
10.1155/2022/6131463
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Cyber security is a fundamental challenge to the Internet of things (IoT) and smart home environments .This paper presents a modified method to ystem (IDS).setection dntrusion ienhance the performance of the This modification is achieved by introducing an alternative feature selection (FS) . ptimizer (GTO) algorithm.oroops torilla gmodel based on the Recently, FS has played a significant role in increasing the detection of anomalies in IDSs. To evaluate the efficiency of the developed method, a set of experimental conducted using three datasets, including NSL-KDD, CICIDS2017, and Bot-IoT datasets.asresults w xtraction (FE) model to reduce the dimensions of these datasets as a first step.Teeature f used as a areetworks (CNN) neural nonvolutional cThe hen, the extracted features are passed to the FS model for detection. The results of the developed method are compared with the well-known IDS technique. The results show the superiority of the developed method over all other methods according to the performance metrics.
引用
收藏
页数:12
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