A steganographic method using Bernoulli's chaotic maps. (August 2016)

• Record Type: Journal Article
• Authors: Martínez-González, Ricardo Francisco; Díaz-Méndez, José Alejandro; Palacios-Luengas, Leonardo; López-Hernández, Juan; Vázquez-Medina, Rubén
• Is Part Of: Computers & electrical engineering. Volume 54(2016)
• Page Start: 435
• Page End: 449
• Publication Date: 2016-08
• Subjects: Steganographic method -- Bernoulli map -- Pixel substitution -- Statistical analysis; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2015.12.005
• Languages: English
• ISSNs: 0045-7906

Abstract

Highlights: A steganographic method for hiding information is proposed using four Bernoulli's chaotic maps. It is applied a two-step scheme: Pixel selection and masking of sensitive information. A module function is applied to the chaotic maps considering an iterated process. There is no evidence of periodicity in the sequences produced by the modified Bernoulli's maps. It is assumed that each map uses two 64-bits variables, and the key space has been estimated in 2 508 . Graphical abstract: Abstract: This paper proposes an alternative for building a data hiding algorithm into digital images. The method is based on chaos theory and the least significant bit technique for embedding a secret message in a image. Specifically the Bernoulli's chaotic maps are used, to perform the following processes: (i) encrypt the bits of the message before embedding them into the cover image, (ii) a random selection of the image's compositions ( R, G or B ) must be performed and the insertion of the secret message in a random way to (iii) rows and (iv) columns of the image. Several experimental results are shown under different evaluation criteria, such as entropy, autocorrelation, homogeneity, contrast, energy, peak signal-to-noise ratio, mean squared error and maximum absolute squared deviation. Experimental results show a good improvement in the peak-signal-to-noise-ratio and Image Fidelity value of the proposed algorithm in comparison to the results obtained from similar algorithms.