• Lavi Sharma
• Harshita Kamboj

The massive number of sensors deployed in the Internet of Things (IoT) produce gigantic amounts of data for facilitating a wide range of applications. Deep Learning (DL) would undoubtedly play a role in generating valuable inferences from this massive volume of data and hence will assist in creating smarter IoT. Spamming is the use of messaging or electronic messaging system that send huge amount of data. Spam often fills the internet with multiple copies of a message and are sent to different recipients repeatedly without their request and urges to open them. Spam is type of virus, it is sent for commercial purposes. It can be sent in massive volume by botnets, networks of infected computers. This paper proposed deep learning technique of spam detection for IOT devices application. The simulation is performed using the Python Spyder Software.

"AN ADAPTIVE APPROACH BASED ON DEEP LEARNING FOR DETECTING OF SPAM IN THE IOT NETWORK", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 8, page no.a805-a809, August-2022, Available :http://www.jetir.org/papers/JETIR2208098.pdf

"AN ADAPTIVE APPROACH BASED ON DEEP LEARNING FOR DETECTING OF SPAM IN THE IOT NETWORK", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 8, page no. ppa805-a809, August-2022, Available at : http://www.jetir.org/papers/JETIR2208098.pdf