Diseño de un modelo de detección de intrusos en entornos IoT usando inteligencia artificial.

Abstract

Internet of Things (IoT) allows large numbers and variety of devices to connect, interact and exchange data, as the era of IoT develops rapidly in recent years, attackers mainly target network environments of this type , with the tremendous growth of IoT botnet for DDoS attacks in recent years, IoT security has become one of the most worrying topics in the field of network security and the need for new methods that detect attacks launched from compromised IoT devices. Artificial intelligence (AI), on the other hand, has found many applications and is being widely explored to provide security specifically for IoT devices. In general terms, there are two outlier detection techniques that use machine learning methods which are a) Statistical-based methods and b) Classification-based methods. This work proposal proposes the design of a model for intrusion detection in IoT environments, using the public data set Bat-IoT and machine learning algorithms.