Due to the huge revolution of IoT devices and their widely used fields.
They brought to the internet billions of unsecured and easily hack-able
devices, because of to the lack or poor security precautions, they be come attractive to attackers. So detection and prevention techniques
are important in order to protect IoT Devices from these threads.
This thesis study the different IDS detection techniques and their dif ferent characteristics and limitations. Also, this thesis will propose
a machine learning approach based on the Random Forest that can
be used as network anomaly detection approach that can be used at
Gateway level to detect Intruders
