Hybrid distributed denial-of-service (DDoS) attack, which utilizes multiple types of DDoS attack to launch one attack event, has become more rampant. However, existing researches for DDoS attack detection mainly focus on the single attack scene and ignore the hybrid attack incident. To deal with the hybrid DDoS attack detect problem, we propose a distributed and collaborative DDoS detection framework(DICOF) to detect and classify multiple DDoS attack simultaneously. Firstly, we propose an entropy-based method to quickly identify the DDoS attack events by measuring the distribution of the total length of inbound and outbound packets for network traffics. Then, we adopt a GRU(Gated Recurrent Unit) based classification method to distinguish the type of different DDoS attacks contained in one attack event. Experiment results show that the DICOF is able to detect hybrid DDoS attack events at millisecond level and classify different DDoS attacks precisely.