Development of adaptive AdaBoost classifier with optimal feature selection for enhanced intrusion detection in IoT
by Mantripragada Yaswanth Bhanu Murthy; Thonduri Vineela; Godavarthi Amar Tej; Movva Vasantha Lakshmi
International Journal of Information and Computer Security (IJICS), Vol. 19, No. 1/2, 2022

Abstract: The fundamental intention of this paper is to model IDS in IoT platforms using an adaptive AdaBoost classifier. In the data collection phase, the intrusion dataset of IoT is collected from the standard benchmark sources. Further, data cleaning is performed, which is to identify and remove errors and duplicate data. The subsequent phase after data cleaning is optimal feature selection, in which the relevant features by eradicating the redundant information are extracted to minimise the classifier complexity. The main contribution of the proposed model is the development of an adaptive AdaBoost classifier, where the tuning of the number of estimators is done by the novel hybrid active electrolocation-based group search optimisation (AE-GSO). From the results, the accuracy of the AE-GSO-AdaBoost is 0.93%, 1.89%, 0.83%, and 1.25% advanced than AdaBoost, RNN, DBN, and DNN, respectively. Based on the comparative study of state-of-the-art works, the numerical outcomes describe the promising part of the suggested techniques, offering comparable detection accuracy to the traditional methods between the accuracy and other performance metrics.

Online publication date: Fri, 04-Nov-2022

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Information and Computer Security (IJICS):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com