Comparison of Classification Model for the Detection of Cyber-attack using Ensemble Learning Models

doi:10.4108/eai.1-2-2022.173293

	Comparison of Classification Model for the Detection of Cyber-attack using Ensemble Learning Models
	Akhtar, Muhammad Shoaib; Feng, Tao
刊名	EAI ENDORSED TRANSACTIONS ON SCALABLE INFORMATION SYSTEMS
	2022
关键词	cyberattack machine learning ensemble learning
ISSN号	2032-9407
DOI	10.4108/eai.1-2-2022.173293
英文摘要	Incorporating digital technologies into security systems is a positive development. It's time for the digital system to be appropriately protected from potential threats and attacks. An intrusion detection system can identify both external and internal anomalies in the network. There are a variety of threats out there, both active and passive. If these dangers aren't addressed, attacks and data theft could occur from the point of origin all the way to the point of destination. Machine learning is still in its infancy, despite its wide range of applications. It is possible to predict the future by using machine learning. A cyber-attack detection system is depicted in this study using machine learning models. Machine learning algorithms were trained to predict cyber-attack scores using data from prior cyber-attacks on an open source website. In order to detect an attack at its earliest possible stage, this research also examined multiple linear machine learning algorithm-based categorization models. Classifiers' accuracy is also compared in the presentation, as is the presentation itself. Balance procedures were followed. Radio Frequency and GBC have the best accuracy, at 87.93%, followed by ABC at 86.11%, BT at 81.03%, ET at 70.31%, and DT at 70.31 percent (84.48 percent).
WOS研究方向	Computer Science
语种	英语
出版者	INST COMPUTER SCIENCES, SOCIAL INFORMATICS & TELECOMMUNICATIONS ENG-ICST
WOS记录号	WOS:000750869600001
内容类型	期刊论文
源URL	[http://ir.lut.edu.cn/handle/2XXMBERH/155613]
专题	计算机与通信学院
作者单位	Lanzhou Univ Technol, Sch Comp & Commun, Lanzhou 730050, Peoples R China
推荐引用方式 GB/T 7714	Akhtar, Muhammad Shoaib,Feng, Tao. Comparison of Classification Model for the Detection of Cyber-attack using Ensemble Learning Models[J]. EAI ENDORSED TRANSACTIONS ON SCALABLE INFORMATION SYSTEMS,2022.
APA	Akhtar, Muhammad Shoaib,&Feng, Tao.(2022).Comparison of Classification Model for the Detection of Cyber-attack using Ensemble Learning Models.EAI ENDORSED TRANSACTIONS ON SCALABLE INFORMATION SYSTEMS.
MLA	Akhtar, Muhammad Shoaib,et al."Comparison of Classification Model for the Detection of Cyber-attack using Ensemble Learning Models".EAI ENDORSED TRANSACTIONS ON SCALABLE INFORMATION SYSTEMS (2022).