Protecting video streams while incurring minimal impact on the compression performance is very important for practical video distribution. Selective encryption is one of the most promising techniques that can offer the required security while maintaining format compliance after encryption with no or little impact on the compression performance. Also, selective encryption techniques can be employed in video surveillance systems to alleviate concerns over privacy invasion by applying the encryption to specific regions of interest. This thesis presents advanced selective encryption techniques for a range of video applications and new methods to effectively and efficiently protect privacy 111 video surveillance systems by applying selective encryption. Background knowledge on video encryption is introduced and previous work is reviewed. Two improved video encryption methods are first demonstrated: one randomly selects one of two equivalent zig-zag scan orders for video preview applications; the other is based on encrypting the sign bits of motion vectors to enhance the scrambling effect. Then, two recently proposed fast selective encryption methods for H.264/AVC are analyzed to show that they are not as efficient as only encrypting the sign bits of nonzero coefficients. A tunable selective encryption scheme for H.264/AVC is developed to provide a tunable scrambling effect by simply adjusting three parameters, so that for different scenarios the user can easily adjust the scrambling effect according to specific requirements. Finally, to more effectively protect privacy in video surveillance systems, it is proposed to el1crypt intra prediction modes within regions of interest in addition to encrypting sign bits of nonzero coefficients, as only encrypting sign bits produces a relatively weak scrambling effect. A re-encoding method is presented to remove the drift error in the non-privacy region caused by the encryption. A spiral binary mask mechanism is also proposed to more efficiently signal the position of the privacy region.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:602966 |
| Date | January 2013 |
| Creators | Wang, Yongsheng |
| Publisher | Queen's University Belfast |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
Page generated in 0.3219 seconds