Recently， with the advancement of multi-source capturing devices and sensing technologies， screen recapturing has become a primary channel for video information leakage during dissemination. The screen-recapturing process causes irreversible physical damage to video watermark information， making it difficult to trace the source of information leakage， which poses a significant challenge in the field of video forensics. The existing anti-screen-recapturing video watermarking techniques are still in the preliminary research stage， and are mainly relying on handcrafted frequency-domain features， which struggle to resist cross-device screen-recapturing attacks effectively. Therefore， an end-to-end anti-screen-recapturing video watermarking method was proposed on the basis of a spatio-temporal feature enhancement network. First， to enrich watermark embedding features， a spatio-temporal feature enhancement network module was designed by integrating an optical flow estimation network and a high-pass filter， thereby optimizing the watermark information embedding strategy. Then， by introducing key factors of screen-recapturing channel noise to simulate screen-recapturing distortion， an anti-screen-recapturing attack noise layer was designed to enhance cross-device robustness against such attacks. Experimental results in real-world screen-recapturing attack scenarios demonstrate that the proposed method achieves a decoding accuracy of over 95%， with both robustness and image quality outperforming the mainstream solutions such as Robust Inherent Video Information Embedding （RIVIE） and Automatic， Robust and Blind Video waterMarking resisting camera recording （ARB-VM）.

Concerning the problem of inaccurate identification of taxi shift behaviors， an accurate identification method of taxi shift behaviors based on trajectory data mining was proposed. Firstly， after analyzing the characteristics of taxi parking state data， a method for detecting taxi parking points in non-operating state was proposed. Secondly， by clustering the parking points， the potential taxi shift locations were obtained. Finally， based on the judgment indices of taxi shift event and the kernel density estimation of the taxi shift time， the locations and times of the taxi shift were identified effectively. Taking the trajectory data of 4 416 taxis in Fuzhou as the experimental samples， a total of 5 639 taxi shift locations were identified. These taxi shift locations are in the main working areas of citizens， transportation hubs， business districts and scenic spots. And the identified taxi shift time is mainly from 4：00 to 6：00 in the morning and from 16：00 to 18：00 in the evening， which is consistent with the travel patterns of Fuzhou citizens. Experimental results show that， the proposed method can effectively detect the time-space distribution of taxi shift， and provide reasonable suggestions for the planning and management of urban traffic resources. The proposed method can also help the people to take a taxi more conveniently， improve the operating efficiency of taxis， and provide references for the site selection optimization of urban gas stations， charging stations and other car related facilities.

Since the common continuous data protection system just backups the modified data directly and consumes a large amount of storage space, this paper presented a continuous data protection system based on Timely Recovery to Any Point-in-time 4 (TRAP-4). This system captured the modified data from the user by volume filter driver, and the data would be backed up to the backup center after calculation and compression. The recovery process can recover the data volume to any time-point through reverse decompressing and reorganizing the compressed data. Experiment shows this system can effectively save the storage space compared to common method. And, as the block size increases and decreases to modify the file, the system further reduces the storage space usage.

Chaotic sequence, with its good correlation performance, being sensitive to initial condition and hard to be decrypted, has been used as an ideal spread spectrum code in direct spread spectrum communication system. In order to take full advantages of the chaotic sequences ranging, based on the analysis of the basic principle of the pseudo code ranging and by using the digital matched filter to achieve the chaotic sequences acquisition, two chaotic spread spectrum ranging schemes were designed and their ranging processes, acquisition time and ranging accuracy were analyzed. The results show that taking the chaotic code as the spread spectrum code of ranging is feasible, with the strongpoint of high security, low interception, and it is also suitable for multi-target ranging, etc.