.png){kind=icon}
.png){kind=icon}
Return
A novel method for intrusions detection in IoT enabled environment
.png){kind=icon}
PRE
AI
DOI：10.1504/IJESDF.2026.153335.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
One of the most significant study areas in recent years has been the internet of things. It is suggested to use a supervised machine learning intrusion detection system (IDS) to identify IoT attacks with a high detection accuracy of 99.99% and an MCC of 99.97%. Using the minimum-maximum normalisation technique for feature scaling, an efficient intrusion detection system (IDS) for the internet of things (IoT) is built to prevent information leakage on the test set. Because of this, it is necessary to provide a greater contribution to this context for the internet of things environment by assessing various AI-based algorithms on datasets that are capable of properly capturing the various aspects of the environment. Not only that, but we also looked at the effects of various approaches for feature engineering, such as correlation analysis and information gain.
Keywords:
internet of things
IoT
machine learning
deep learning
network security
Journal
I
IF:
0.5
Papers:
26
Citations:
133