A Novel Hybrid Deep Learning Model for Botnet Attacks Detection in a Secure IoMT Environment

Abstract

The Internet of Medical Things is growing fast.
This has made it easier to monitor peoples health from away
and has improved medical services.. It also means that medical
devices are connected to the internet, which makes them
vulnerable to cyber attacks. These attacks can compromise the
safety of information and the whole system.
To deal with this problem we are suggesting a way to detect
these kinds of attacks using a special kind of computer program.
This program uses two methods to look at the data from medical
devices. The first method looks at the data like a picture. The
second method looks at the data over time.
We used data from medical devices to test our program.
We also did some things to the data to make it easier for the
program to understand.
When we tested our program it worked well. It was better at
detecting attacks than programs. This means that our program
can help keep peoples health information safe and make sure
that medical systems are secure.
The Internet of Medical Things is very important, for
healthcare. Our program can help make it safer.