Research Article
Adaptive Carving Method for Live FLV Streaming
@INPROCEEDINGS{10.1007/978-3-030-00916-8_51, author={Haidong Ge and Ning Zheng and Lin Cai and Ming Xu and Tong Qiao and Tao Yang and Jinkai Sun and Sudeng Hu}, title={Adaptive Carving Method for Live FLV Streaming}, proceedings={Collaborative Computing: Networking, Applications and Worksharing. 13th International Conference, CollaborateCom 2017, Edinburgh, UK, December 11--13, 2017, Proceedings}, proceedings_a={COLLABORATECOM}, year={2018}, month={10}, keywords={Live streaming video Recovery Forensic Network traffic}, doi={10.1007/978-3-030-00916-8_51} }- Haidong Ge
Ning Zheng
Lin Cai
Ming Xu
Tong Qiao
Tao Yang
Jinkai Sun
Sudeng Hu
Year: 2018
Adaptive Carving Method for Live FLV Streaming
COLLABORATECOM
Springer
DOI: 10.1007/978-3-030-00916-8_51
Abstract
Currently, most video carving methods are to recover video files from disk file system, but these methods often do not work well for video form network streams, especially for live streaming video. In this paper, an adaptive video carving method is proposed to recover the live FLV (Flash Video) streaming video from network traffic. Firstly, to recover videos when there is no packet loss during data capture, a method based on network data structure is proposed. Secondly, to solve the problem of packet loss or corruption during data capture, another video carving method is proposed based on both the FLV structure and network data structure. Finally, to achieve good balance between computational complexity and recovery accuracy, an adaptive method based above two methods is proposed. The experimental results show that the proposed methods achieve good performance both in consuming time and recovery rate.
