TCP Flood Attack Detection on Internet of Things devices using CNN-GRU Deep Learning Model
Muhammad Saqib Ishaq, Ibrahim Khan, Syed Irfan Ullah, Tahseen Ullah · 2023
Our research proposes a Hybrid Deep Learning CNN-GRU model which is developed and tested on nine different IoT devices. The Dataset is created from (N-BaIoT) Narrow band Internet of Things Devices to detect softwarebased attacks including Bashlite and Mirai. TCP flood attack is primarily addressed, thus achieving maximum accuracy on all nine internet of things devices’ real time data. Our study presents a framework utilizing advanced Deep Learning AI based algorithms to identify several unknown patterns in the incorporated datasets allowing detection of TCP attacks from different IoT devices both effectually and competently.