Image Hiding Using Logistic Map Chaotic Function
محورهای موضوعی : Computer Engineering
1 - Department of Computer Engineering, Firoozkooh Branch, Islamic Azad University, Firoozkooh, Iran
کلید واژه: Image Hiding, Secret Image, Cover Image, Chaotic Function,
چکیده مقاله :
Steganography is the action of hiding a secret message within another cover message. The secret message and the cover image can be text, image, voice even signal. In this article an image is used as the secret message while the cover message is also a gray level image. This paper proposes a new method of steganography based on logistic chaotic maps. This function is used to determine the position of different bits of the secret image in the covering image. The main advantage of the proposed method is that the pixels of the secret image in the covering image is uniformly distributed, which increases the robustness of the proposed method to common attacks. The robustness and performance of the proposed method against common attacks in the area of steganography including corruption, clipping, and noise is tested. The high PSNR of the proposed method (about 45) expresses the high performance of the proposed method.
[1] R. Enayatifar, F. Mahmoudi, K. Mirzaei, Using the Chaotic Map in Image Steganography, 2009 International Conference on Information Management and Engineering, 2009, pp. 491-495.
[2] H.E. Rostam, H. Motameni, R. Enayatifar, Privacy-preserving in the Internet of Things based on steganography and chaotic functions, Optik, 258, (2022), 168864.
[3] H.S. Kwok, W.K.S. Tang, A fast image encryption system based on chaotic maps with finite precision representation, Chaos, Solitons & Fractals, 32(4), (2007) 1518-1529.
[4] A. Abdelwahab, L. Hassaan, A discrete wavelet transform based technique for image data hiding, 2008.
[5] H. Sajedi, Steganalysis based on steganography pattern discovery, Journal of Information Security and Applications,Vol. 30 ,(2016) ,3-14.
[6] P.C. Mandal, I. Mukherjee, G. Paul, B.N. Chatterji, Digital image steganography: A literature survey, Information Sciences ,609 ,(2022) 1451-1488.
[7] I.J. Kadhim, P. Premaratne, P.J. Vial, B. Halloran, Comprehensive survey of image steganography: Techniques, Evaluations, and trends in future research, Neurocomputing, 335, (2019) ,299-326.
[8] A.H. Abdullah, R. Enayatifar, M. Lee, A hybrid genetic algorithm and chaotic function model for image encryption, AEU - International Journal of Electronics and Communications, 66(10), (2012), 806-816.
[9] H. Ghanbari, R. Enayatifar, H. Motameni, Chaos-based image encryption using hybrid model of linear-feedback shift register system and deoxyribonucleic acid, Multimedia Tools and Applications (2022).
[10] R. Enayatifar, A.H. Abdullah, I.F. Isnin, Chaos-based image encryption using a hybrid genetic algorithm and a DNA sequence, Optics and Lasers in Engineering, 56, (2014), 83-93.
[11] R. Enayatifar, A.H. Abdullah, I.F. Isnin, A. Altameem, M. Lee, Image encryption using a synchronous permutation-diffusion technique, Optics and Lasers in Engineering, 90, (2017), 146-154.
[12] M. Yadollahi, R. Enayatifar, H. Nematzadeh, M. Lee, J.-Y. Choi, A novel image security technique based on nucleic acid concepts, Journal of Information Security and Applications, 53, (2020), 102505.
[13] D. Shah, T. Shah, Y. Naseer, S.S. Jamal, S. Hussain, Cryptographically strong S-P boxes and their application in steganography, Journal of Information Security and Applications, 67 ,(2022), 103174.
[14] V. Sabeti, M. Sobhani, S.M.H. Hasheminejad, An adaptive image steganography method based on integer wavelet transform using genetic algorithm, Computers and Electrical Engineering ,99, (2022), 107809.
[15] Y.-H. Yu, C.-C. Chang, I.-C. Lin, A new steganographic method for color and grayscale image hiding, Computer Vision and Image Understanding ,107(3) ,(2007), 183-194.
[16] Y.-S. Wu, C.-C. Thien, J.-C. Lin, Sharing and hiding secret images with size constraint, Pattern Recognition ,37(7), (2004), 1377-1385.
[17] R.-Z. Wang, Y.-D. Tsai, An image-hiding method with high hiding capacity based on best-block matching and k-means clustering, Pattern Recognition ,40(2), (2007), 398-409.
