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Title:
benchmarking for steganography by kernel fisher discriminant criterion
Author: Huang Wei ; Zhao Xianfeng ; Feng Dengguo ; Sheng Rennong
Source: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Conference Name: 7th China International Conference on Information Security and Cryptography, Inscrypt 2011
Conference Date: November 30, 2011 - December 3, 2011
Issued Date: 2012
Conference Place: Beijing, China
Keyword: Algorithms ; Cryptography ; Steganography
Indexed Type: EI
ISSN: 0302-9743
ISBN: 9783642347030
Department: (1) Institute of Software Chinese Academy of Sciences Beijing 100190 China; (2) State Key Laboratory of Information Security Institute of Information Engineering Chinese Academy of Sciences Beijing 100029 China; (3) Beijing Institute of Electronic Technology and Application Beijing 100091 China
Abstract: In recent years, there have been many steganographic schemes designed by different technologies to enhance their security. And a benchmarking scheme is needed to measure which one is more detectable. In this paper, we propose a novel approach of benchmarking for steganography via Kernel Fisher Discriminant Criterion (KFDC), independent of the techniques in steganalysis. In KFDC, besides between-class variance resembles what Maximum Mean Discrepancy (MMD)merely concentrated on, within-class variance plays another important role. Experiments show that KFDC is qualified for the indication of the detectability of steganographic algorithms. Then, we use KFDC to illustrate detailed analysis on the security of JPEG and spatial steganographic algorithms. © 2012 Springer-Verlag Berlin Heidelberg.
English Abstract: In recent years, there have been many steganographic schemes designed by different technologies to enhance their security. And a benchmarking scheme is needed to measure which one is more detectable. In this paper, we propose a novel approach of benchmarking for steganography via Kernel Fisher Discriminant Criterion (KFDC), independent of the techniques in steganalysis. In KFDC, besides between-class variance resembles what Maximum Mean Discrepancy (MMD)merely concentrated on, within-class variance plays another important role. Experiments show that KFDC is qualified for the indication of the detectability of steganographic algorithms. Then, we use KFDC to illustrate detailed analysis on the security of JPEG and spatial steganographic algorithms. © 2012 Springer-Verlag Berlin Heidelberg.
Language: 英语
Content Type: 会议论文
URI: http://ir.iscas.ac.cn/handle/311060/15855
Appears in Collections:软件所图书馆_会议论文

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Recommended Citation:
Huang Wei,Zhao Xianfeng,Feng Dengguo,et al. benchmarking for steganography by kernel fisher discriminant criterion[C]. 见:7th China International Conference on Information Security and Cryptography, Inscrypt 2011. Beijing, China. November 30, 2011 - December 3, 2011.
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