CLASSIFICATION OF IOT NETWORK TRAFFIC USING MACHINE LEARNING ALGORITHMS
Author(s):
R. Kavitha, P. Saranya
Keywords:
Abstract
The identification of IoT devices in network data is one such essential operation. It enables the administrator to keep monitors on the actions of IoT devices, which can be helpful for the effective implementation of Quality of Service, detect malicious IoT devices, etc. In this study, a machine learning based classification of IoT network traffic is proposed. IoT traffic classification is separated using a larger data set. The input dataset is first pre-processed to remove any noise. Chi-square-based feature extraction is used during the extraction process. The Chi-Square technique is used to process the extraction areas in order to extract various features and choose the necessary features in order to improve classification. The KNN and MLP classifiers are employed for determine the precise classification. The output of the proposed technique is implemented by using the Python software. As a result this approach achieves good accuracy but takes large training times in packet level due to large amounts of data and unbalanced data.
Article Details
Unique Paper ID: 161140

Publication Volume & Issue: Volume 10, Issue 2

Page(s): 669 - 675
Article Preview & Download


Share This Article

Conference Alert

NCSST-2023

AICTE Sponsored National Conference on Smart Systems and Technologies

Last Date: 25th November 2023

SWEC- Management

LATEST INNOVATION’S AND FUTURE TRENDS IN MANAGEMENT

Last Date: 7th November 2023

Go To Issue



Call For Paper

Volume 10 Issue 1

Last Date for paper submitting for March Issue is 25 June 2023

About Us

IJIRT.org enables door in research by providing high quality research articles in open access market.

Send us any query related to your research on editor@ijirt.org

Social Media

Google Verified Reviews