Steganalysis in Multiple Sources of Cover Images

Author

Zugen Liu

Author_Institution

Software Coll., Shenyang Normal Univ., Shenyang, China

Volume

1

fYear

2009

fDate

12-14 Aug. 2009

Firstpage

218

Lastpage

221

Abstract

45 dimensional feature vectors were extracted from DCT and spatial domains of images to defeat steganographic schemes in this paper. Compared with commonly used steganalytic algorithms, the presented method offers much better performances in double JPEG compressed covers and their stegos. However, when our method was applied to detect whether multiple sources of images containing hidden data or not, it showed very poor performances. An improved training technique was proposed and a robuster steganalytic algorithm was designed.

Keywords

data compression; discrete cosine transforms; feature extraction; image classification; image coding; steganography; support vector machines; DCT; JPEG image; cover image; discrete cosine transform; feature vector extraction; hidden data; spatial domain; steganalysis; steganographic scheme; support vector machine classifier; training technique; Algorithm design and analysis; Discrete cosine transforms; Feature extraction; Histograms; Pixel; Robustness; Statistical distributions; Statistics; Steganography; Transform coding; Steganalysis; feature vector; robust;

fLanguage

English

Publisher

ieee

Conference_Titel

Hybrid Intelligent Systems, 2009. HIS '09. Ninth International Conference on

Conference_Location

Shenyang

Print_ISBN

978-0-7695-3745-0

Type

conf

DOI

10.1109/HIS.2009.50

Filename

5254296