In recent years, cyber-attacks have increased significantly in both volume and sophistication, making the detection of security violations a crucial feature in computer systems. This is particularly true in the Internet of Things (IoT), where devices are vulnerable to failures and malicious attacks due to their resource-constrained nature. Given the proliferation of new security threats, anomaly-based detection approaches are essential for intrusion detection and prevention systems to effectively defend against attackers. This paper proposes an information-theoretic approach based on entropy to establish an anomaly detection model. A real case study in IoT networks based on Routing Over Low power and Lossy networks (RPL) illustrates the application of the proposed approach. Preliminary experimental results demonstrate that our method is both practical and extendable.