Sensor networks are often deployed in unattended environments, thus leaving these networks vulnerable to false data injection attacks in which an adversary injects forged reports into the network through compromised nodes, with the goal of deceiving the base station or depleting the resources of forwarding nodes. Several research solutions have been recently proposed to detect and drop such forged reports during the forwarding process. Each design can provide the equivalent resilience in terms of node compromising. However, their energy consumption characteristics differ from each other. Thus, employing only a single filtering scheme for a network is not a recommendable strategy in terms of energy saving. In this paper, we propose a fuzzy-based adaptive filtering scheme selection method for energy saving. A fuzzy rule-based system is exploited to choose one of three filtering schemes by considering the false traffic ratio, the security threshold value, distance, and the detection power of the filtering scheme. The adaptive selection of the filtering schemes can conserve energy, and guarantee sufficient resilience.