The Low-rate Denial of Service (LDoS) attacks reduce network services capabilities by periodically sending high intensity pulse data flows. For the hidden performance of LDoS attacks, it is more difficult for traditional DoS detection methods to detect. At the same time the accuracy of the current detection methods for the LDoS attacks is relatively low. However, when the LDoS attacks occur, the frequency distribution and the fluctuation pattern of the TCP traffic have a special change. As the fact that the LDoS attacks led to the abnormal frequency distribution and the abnormal fluctuation pattern of the TCP traffic, we propose a new collaborative detection method (NCDM) for LDoS attacks. In NCDM, the 2 Distance is used to measure the frequency distribution and the Mean Deviation is used to measure the fluctuation pattern, then judgment criteria are proposed to collaborative detect the LDoS attacks. Base on the NS2 simulator platform and DARPA99 datasets, the experiments show that this method can detect LDoS attacks effectively and has a low false-negative rate and falsepositives rate. Index Terms-The Low-rate Denial of Service (LDoS); 2 Distance; Mean Deviation; Judgment Criterion; Collaborative Detection Dan Tang received his M.S. degree in Huazhong University of Science and Technology (HUST) in June 2006. Currently he is a PhD candidate in HUST. His research interests include the areas of computer network security, computer information security, and architecture of future Internet. Kai Chen is a lecturer of School of CS at HUST. He received the Ph.D. degree in Huazhong University of Science and Technology in 2012. His current research interests include computer network application, computer network security and computer network protocol analysis.Xiaosu Chen is a professor of Huazhong University of Science and Technology. His research interests include computer network application, computer network security, computer network protocol analysis, and image recognition.Huiyu Liu is a lecturer of School of CS at HUST. In 2011, He received the Ph.D. degree in Systems Architecture from HUST. His research interests include network security, cloud computing and semantic network.Xinhua Li Currently he is pursuing the PhD. degree in HUST. His current research interests include image recognition, computer network security and network protocol analysis.