Title :
Spatio-temporal rich model for motion vector steganalysis
Author :
Tasdemir, Kasim ; Kurugollu, Fatih ; Sezer, Sakir
Author_Institution :
Inst. of Electron., Commun. & Inf., Queen´s Univ. Belfast, Belfast, UK
Abstract :
We propose a spatio-temporal rich model of motion vector planes as a part of a full steganalytic system against motion vector based steganography. Superior detection accuracy of the rich model over the previous methods has been lately demonstrated for digital images in both spatial and DCT domain. It has not been heretofore used for detection of motion vector steganography. We also introduced a transformation so as to extend the feature set with temporal residuals. We carried out the tests along with most recent motion vector steganalysis and steganography methods. Test results show that the proposed model delivers an outstanding performance compared to the previous methods.
Keywords :
discrete cosine transforms; motion estimation; steganography; DCT domain; digital images; motion vector planes; motion vector steganalysis; motion vector steganography; spatial domain; spatiotemporal rich model; superior detection accuracy; Accuracy; Adaptation models; Correlation; Feature extraction; Forensics; Payloads; Security; motion vector; rich model; steganalysis; video;
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2015 IEEE International Conference on
Conference_Location :
South Brisbane, QLD
DOI :
10.1109/ICASSP.2015.7178264