To address the issues of not considering chromatic domain information and low accuracy in current video froensic compression methods, a surveillance video recompression forensics method for the latest versatile video coding (VVC) standard based on the information fusion of chroma domain and luminance domain, referred to as CLF-SVRF, is proposed. Based on the coding principles of the VVC standard, the basic bitstream characteristics in VVC video bitstream that are closely related to compression time are analyzed and determined from the dimensions of chroma domain and luminance domain in surveillance videos. The basic bitstream characteristics include the partitioning type and prediction mode of coding unit (CU) in chroma domain and luminance domain. Combining with the Lagrangian rate distortion optimization technique, the variations in the partitioning type and prediction mode of CU in chroma domain and luminance domain as the compression time increases are analyzed. It is further determined that the partitioning type and prediction mode of CU in chroma domain and luminance domain can be used as basic bitstream characteristics for detecting the video compression time. Then, considering the requirement of video surveillance applications for low complexity forensics methods, a low complexity advanced bitstream characteristics is constructed based on the partitioning type and prediction mode of CU in chroma domain and luminance domain. The advanced bitstream characteristics are input into the support vector machine to complete the recompression forensics of surveillance videos. The experimental results show that compared with the current advanced methods, the CLF-SVRF method can improve the accuracy of surveillance video recompression forensics by 13.53% on average. At the same time, it can significantly reduce the time required for forensic recompression, and reduce the recompression forensics time by 47.42% on average.