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Subject: Engineering
Title:
video steganalysis exploiting motion vector reversion-based features
Author: Cao Yun ; Zhao Xianfeng ; Feng Dengguo
Source: IEEE Signal Processing Letters
Issued Date: 2012
Volume: 19, Issue:1, Pages:35-38
Indexed Type: ei,sci
Department: (1) State Key Laboratory of Information Security, Institute of Software, Chinese Academy of Sciences, Beijing 100190, China; (2) Graduate University, Chinese Academy of Sciences, Beijing 100049, China
English Abstract: Unlike traditional image or video steganography in spatial/transform domain, motion vector (MV)-based methods target the internal dynamics of video compression and embed messages while performing motion estimation. However, we have noticed that some existing methods adopt nonoptimal selection rules and modify MVs in somewhat arbitrary manners which violate the encoding principles a lot. Aiming at these weaknesses, we design a calibration-based approach and propose MV reversion-based features for steganalysis. Experimental results demonstrate that the proposed features are very sensitive to the tendency of MV reversion during calibration and can be used to effectively detect some typical MV-based steganography even with low embedding rates. © 2011 IEEE.
Language: 英语
WOS ID: WOS:000297583800006
Citation statistics:
Content Type: 期刊论文
URI: http://ir.iscas.ac.cn/handle/311060/14755
Appears in Collections:软件所图书馆_期刊论文

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Recommended Citation:
Cao Yun,Zhao Xianfeng,Feng Dengguo. video steganalysis exploiting motion vector reversion-based features[J]. IEEE Signal Processing Letters,2012-01-01,19(1):35-38.
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