XGB-RF: A Hybrid Machine Learning Approach for IoT Intrusion Detection

被引:30
作者
Faysal, Jabed Al [1 ]
Mostafa, Sk Tahmid [2 ]
Tamanna, Jannatul Sultana [2 ]
Mumenin, Khondoker Mirazul [2 ]
Arifin, Md. Mashrur [2 ]
Awal, Md. Abdul [2 ]
Shome, Atanu [1 ]
Mostafa, Sheikh Shanawaz [3 ]
机构
[1] Khulna Univ KU, Comp Sci & Engn Discipline CSE, Khulna 9208, Bangladesh
[2] Khulna Univ KU, Elect & Commun Engn ECE Discipline, Khulna 9208, Bangladesh
[3] ITI Interact Technol Inst, Lab Robot & Syst Engn & Sci, LARSyS, M ITI,ARDITI, P-9000 Funchal, Portugal
来源
TELECOM | 2022年 / 3卷 / 01期
关键词
IoT security; botnet detection; random forest; XGB; feature selection; Mirai; ATTACK DETECTION; INTERNET; THINGS;
D O I
10.3390/telecom3010003
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
In the past few years, Internet of Things (IoT) devices have evolved faster and the use of these devices is exceedingly increasing to make our daily activities easier than ever. However, numerous security flaws persist on IoT devices due to the fact that the majority of them lack the memory and computing resources necessary for adequate security operations. As a result, IoT devices are affected by a variety of attacks. A single attack on network systems or devices can lead to significant damages in data security and privacy. However, machine-learning techniques can be applied to detect IoT attacks. In this paper, a hybrid machine learning scheme called XGB-RF is proposed for detecting intrusion attacks. The proposed hybrid method was applied to the N-BaIoT dataset containing hazardous botnet attacks. Random forest (RF) was used for the feature selection and eXtreme Gradient Boosting (XGB) classifier was used to detect different types of attacks on IoT environments. The performance of the proposed XGB-RF scheme is evaluated based on several evaluation metrics and demonstrates that the model successfully detects 99.94% of the attacks. After comparing it with state-of-the-art algorithms, our proposed model has achieved better performance for every metric. As the proposed scheme is capable of detecting botnet attacks effectively, it can significantly contribute to reducing the security concerns associated with IoT systems.
引用
收藏
页码:52 / 69
页数:18
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