GA-Based LSB-Matching Steganography to Hold Second-Order Statistics

Author

Liu, Guangjie ; Zhang, Zhan ; Dai, Yuewei ; Wang, Zhiquan

Author_Institution

Sch. of Autom., Nanjing Univ. of Sci. & Technol., Nanjing, China

Volume

1

fYear

2009

fDate

18-20 Nov. 2009

Firstpage

510

Lastpage

513

Abstract

How to design more secure steganographical algorithms all along is the hot topic. In this paper, a modified LSB-matching method is proposed to hold second-order statistics described by Markov Chain distance. To achieve it, the genetic algorithm is used to find the optimum tuning vector to match LSBs of image pixels and message bits. Experiments show the proposed algorithm has better security in K-L and M-C distance meanings, and the blind steanalysis tests also show that our new algorithm is more secure than LSB and LSB-matching methods.

Keywords

Markov processes; blind source separation; genetic algorithms; image coding; image matching; statistical analysis; steganography; K-L distance meanings; LSB-matching steganography; M-C distance meanings; Markov chain distance; blind steanalysis tests; genetic algorithm; image pixels; message bits; optimum tuning vector; second-order statistics; Algorithm design and analysis; Automation; Genetic algorithms; Higher order statistics; Information security; Quantization; Statistical distributions; Steganography; Stochastic processes; Testing; LSB-matching; Markov chain; genetic algorithm; steganography;

fLanguage

English

Publisher

ieee

Conference_Titel

Multimedia Information Networking and Security, 2009. MINES '09. International Conference on

Conference_Location

Hubei

Print_ISBN

978-0-7695-3843-3

Electronic_ISBN

978-1-4244-5068-8

Type

conf

DOI

10.1109/MINES.2009.281

Filename

5368008