Year: 2006
Type: dissertation
Abstract: In this thesis we present an effective steganalysis technique for digital video sequences\nbased on the collusion attack. Steganalysis is the process of detecting with a high probability\nthe presence of covert data in multimedia. Existing algorithms for steganalysis target\ndetecting covert information in still images. When applied directly to video sequences\nthese approaches are suboptimal. In this thesis we present methods that overcome this\nlimitation by using redundant information present in the temporal domain to detect covert\nmessages in the form of Gaussian watermarks. In particular we target the spread spectrum\nsteganography method because of its widespread use. Our gains are achieved by exploiting\nthe collusion attack that has recently been studied in the field of digital video watermarking\nand more sophisticated pattern recognition tools. Through analysis and simulations we,\nevaluate the effectiveness of the video steganalysis method based on averaging based collusion\nscheme. Other forms of collusion attack in the form of weighted linear collusion and\nblock-based collusion schemes have been proposed to improve the detection performance.\nThe proposed steganalsyis methods were successful in detecting hidden watermarks\nbearing low SNR with high accuracy. The simulation results also show the improved performance\nof the proposed temporal based methods over the spatial methods. We conclude\nthat the essence of future video steganalysis techniques lies in the exploitation of the temporal\nredundancy.
Author: Udit Budhia
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W2298624861