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Publication Type : Conference Proceedings
Publisher : Advances in Signal Processing and Intelligent Recognition Systems, Springer International Publishing
Source : Advances in Signal Processing and Intelligent Recognition Systems, Springer International Publishing, Volume 678, Cham, p.155-166 (2018)
ISBN : 9783319679341
Campus : Coimbatore
School : School of Engineering
Department : Computer Science
Year : 2018
Abstract : Security is essential to all varieties of data that is transmitted through an open network or the internet. Steganography is such a technique which provides security for any kind of data by hiding it inside a cover object. The images with confidential information like medical reports, passport, academic certificates, Aadhar card and agreements between governments need to be secured while transferring through the internet. In this paper, dual cover steganography is used to provide a better security which prevents the confidential data from attackers. This approach uses two layers of covers, image, and DNA. Using improved DNA insertion method the document image is hidden inside a DNA sequence. The BPN, capacity, payload and embedding time are calculated for the DNA sequence. The improved insertion method is used in this paper since it gives the very low cracking probability. The fake DNA is hidden inside a cover image using matrix embedding with hamming code algorithm for both spatial and transform domain of an image. The Mean Square Error (MSE), Peak Signal Noise Ratio (PSNR), Maximum difference, average difference, structural content are calculated and compared. To ensure the security of document image the statistical attack called histogram analysis attack is performed and compared. This comparison shows that the matrix embedding with hamming code in the frequency domain provides better security for the second layer of hiding the data.
Cite this Research Publication : R. E. Vinodhini, Malathi P., and T. Kumar, G., “An Improved Approach for Securing Document Images Using Dual Cover”, Advances in Signal Processing and Intelligent Recognition Systems, vol. 678. Springer International Publishing, Cham, pp. 155-166, 2018.