Industry and academia have increased the deployment of Network Functions Virtualization (NFV) on their environments, either for reducing expenditures or taking advantage of NFV flexibility for service provisioning. In NFV, Service Function Chainings (SFC) composed of Virtualized Network Functions (VNF) are defined to deliver services to different customers. Despite the advancements in SFC composition for service provisioning, there is still a lack of proposals for ensuring the integrity of NFV service delivery, i.e., detecting anomalies in SFC operation. Such anomalies could indicate a series of different threats, such as DDoS attacks, information leakage, and unauthorized access. In this PhD, we propose a framework composed of an SFC Integrity Module (SIM) for the standard NFV architecture, providing the integration of anomaly detection mechanisms to NFV orchestrators. We present recent results of this PhD regarding the implementation of an entropy-based anomaly detection mechanism using the SIM framework. The results presented in this paper are based on the execution of the proposed mechanism using a realistic SFC data set.