A modified image steganographic method based on chaotic text encryption using lifting wavelet transform
by K. Sheela Sobana Rani; M. Yuvaraju; V. Sathya; R. Lavanya; R. Gayathri
Electronic Government, an International Journal (EG), Vol. 17, No. 4, 2021

Abstract: Steganography is an art of concealing text into cover image over a covert channel, enabling covert communication. In this paper, a modified steganographic approach using lifting wavelet transform (LWT) is proposed. The key for encrypting the text are generated randomly using chaotic maps. The concept of confusion and diffusion is applied using one of the widely used dynamic systems namely Lorenz, Chen and Lu. By applying chaos strategy effectively in secret communication, the strength of the anticipated algorithm is improved to a significant level. The encrypted text can be concealed into the cover image using adaptive least significant bit (ALSB) algorithm. The stego image obtained at the end of data embedding process undergoes few security statistical analyses such as peak signal to noise ratio (PSNR), mean square error (MSE), elapsed time and correlation calculations. With the significant knowledge of above parameters, it is observed that the suggested methodology proves to have advantages over existing ones, providing higher level of security against some existing attacks.

Online publication date: Tue, 12-Oct-2021

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the Electronic Government, an International Journal (EG):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com