The recent advancements in technologies such as Artificial Intelligence, the Internet of Things (IoT), drones, and embedded systems have led to significant changes in industrial systems architectures.
This shift from simple systems to complex systems with hundreds of devices has made securing these systems difficult.

Intrusion Detection Systems (IDS) are mandatory tools to secure them. IDS is an area where AI is used to detect malicious traffic on heterogeneous systems involving IoT, embedded systems, and more classic LAN.
Machine learning (ML) and deep learning (DL) have been extensively explored as a means to automate IDS giving them an edge to detect new forms of attacks.
In this research, we will focus on IDS for networks dedicated to agriculture.