Application of Machine Leaning for Intrusion Detection in Internet of Things

In recent years, the use of machine learning algorithms for intrusion detection in the Internet of Things has received significant attention. IoT systems are typically composed of many interconnected devices and sensors that collect and process data. The data collected by these devices and sensors can be used to train machine learning models that can be used to detect anomalies and intrusions. Despite the recent advances in security technologies, cyber-attacks are still occurring with alarming frequency in various industries. These attacks can have devastating consequences, from losing sensitive data to causing physical damage to critical infrastructure. This chapter will explore how machine learning can be used for intrusion detection in the IoT. We will also give ideas and suggestions about making machine learning models better for intrusion detection.