Segmentation Based Video Steganalysis to Detect Motion Vector Modification
Joint Authors
Wang, Peipei
Cao, Yun
Zhao, Xianfeng
Source
Security and Communication Networks
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-10-16
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Information Technology and Computer Science
Abstract EN
This paper presents a steganalytic approach against video steganography which modifies motion vector (MV) in content adaptive manner.
Current video steganalytic schemes extract features from fixed-length frames of the whole video and do not take advantage of the content diversity.
Consequently, the effectiveness of the steganalytic feature is influenced by video content and the problem of cover source mismatch also affects the steganalytic performance.
The goal of this paper is to propose a steganalytic method which can suppress the differences of statistical characteristics caused by video content.
The given video is segmented to subsequences according to block’s motion in every frame.
The steganalytic features extracted from each category of subsequences with close motion intensity are used to build one classifier.
The final steganalytic result can be obtained by fusing the results of weighted classifiers.
The experimental results have demonstrated that our method can effectively improve the performance of video steganalysis, especially for videos of low bitrate and low embedding ratio.
American Psychological Association (APA)
Wang, Peipei& Cao, Yun& Zhao, Xianfeng. 2017. Segmentation Based Video Steganalysis to Detect Motion Vector Modification. Security and Communication Networks،Vol. 2017, no. 2017, pp.1-12.
https://search.emarefa.net/detail/BIM-1203166
Modern Language Association (MLA)
Wang, Peipei…[et al.]. Segmentation Based Video Steganalysis to Detect Motion Vector Modification. Security and Communication Networks No. 2017 (2017), pp.1-12.
https://search.emarefa.net/detail/BIM-1203166
American Medical Association (AMA)
Wang, Peipei& Cao, Yun& Zhao, Xianfeng. Segmentation Based Video Steganalysis to Detect Motion Vector Modification. Security and Communication Networks. 2017. Vol. 2017, no. 2017, pp.1-12.
https://search.emarefa.net/detail/BIM-1203166
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1203166