Dynamic Fuzzy Rule Interpolation (D-FRI) offers a dynamic rule base for fuzzy systems which is especially useful for systems with changing requirements and limited prior knowledge. This suggests a possible application of D-FRI in the area of network security due to the volatility of the traffic. A honeypot is a valuable tool in the field of network security for baiting attackers and collecting their information. However, typically designed with fewer resources they are not considered as a primary security tool for use in network security. Consequently, such honeypots can be vulnerable to many security attacks. One such attack is a spoofing attack which can cause severe damage to the honeypot, making it inefficient. This paper presents a vigilant dynamic honeypot based on the D-FRI approach for use in predicting and alerting of spoofing attacks on the honeypot. First, it proposes a technique for spoofing attack identification based on the analysis of simulated attack data. Then, the paper employs the identification technique to develop a D-FRI based vigilant dynamic honeypot, allowing the honeypot to predict and alert that a spoofing attack is taking place in the absence of matching rules. The resulting system is capable of learning and maintaining a dynamic rule base for more accurate identification of potential spoofing attacks with respect to the changing traffic conditions of the network.