In this poster, based on our previous work in building a lightweight DDoS (Distributed Denial-of-Services) attacks detection mechanism for web server using TCM-KNN (Transductive Confidence Machines for K-Nearest Neighbors) and genetic algorithm based instance selection methods, we further propose a more efficient and effective instance selection method, named E-FCM (Extend Fuzzy C-Means). By using this method, we can obtain much cheaper training time for TCM-KNN while ensuring high detection performance. Therefore, the optimized mechanism is more suitable for lightweight DDoS attacks detection in real network environment. Categories and Subject Descriptors C.2.0 [Computer-Communication Network]: Security and Protection General Terms Security, Algorithms Keywords Web server anomaly detection, E-FCM algorithm, TCM-KNN algorithm, Instance selection