Title: A robust low frequency integer wavelet transform based fractal encryption algorithm for image steganography
Authors: Ambika; Rajkumar L. Biradar
Addresses: Department of Computer Science and Engineering, Appa Institute of Engineering and Technology, H. No 8-1304/14 A, Sita Mate Nivas, Gandhi Nagar, Humnabad Road, Kalaburagi-585104, India ' Electronics and Telematics Department, G Narayanamma Institute of Technology and Science, Hyderabad-500008, Telangana State, India
Abstract: Image steganography is one of the emerging research areas in the field of information technology. In today's scenario, steganography is widely utilised in communication systems that send secret information through appropriate carriers. In this scenario, the secret information that embeds in the cover image is secret image. The primary objective of this paper is to develop a high level secure transmission technique to transmit messages through lossless channel. In this paper, an effective transform domain image steganography approach is proposed by employing lower frequency integer wavelet transform (IWT) and fractal encryption with the combination of L-shaped tromino theorem for enhancing the performance of information hiding method. The proposed methodology: IWT-fractal encryption delivers the advantage of better embedding capacity with low computational complexity and also provides better secret image quality. Experimental outcome shows that the proposed approach improved peak signal-to-noise ratio (PSNR) value up to 30 dB and entropy value up to 0.02-0.4 compared to the existing methods: genetic algorithm and discrete cosine transform (DCT)-Arnold transform. This experimental outcome confirms that the proposed technique delivers a high security level network with low computational complexity compared to other existing approaches.
Keywords: fractal encryption; image steganography; integer wavelet transform; L-shaped tromino.
International Journal of Advanced Intelligence Paradigms, 2021 Vol.19 No.3/4, pp.342 - 356
Received: 06 Jan 2018
Accepted: 17 Feb 2018
Published online: 09 Jul 2021 *