Document Type : Research Article
Department of Computer Engineering, Faculty of Engineering, Alzahra University, Tehran, Iran.
A steganography system must embed the message in an unseen and unrecognizable manner in the cover signal. Embedding information in transform coefficients, especially Discrete Wavelet Transform (DWT), is one of the most successful approaches in this field. The proposed method in this paper has two main steps. In the first step, the XOR logical function was used to embed two bits of data in the adjacent DWT coefficient pair. No change in the coefficients will occur if the XOR result of the two bits of low-value data of the two adjacent coefficients is identical to the two bits of secret data. Otherwise, one or both of the coefficient(s) will need a one-unit increase or decrease. In the second step, the genetic algorithm was used to select, between the two possible solutions, a new value for the adjacent coefficient pair that needs to be changed. Using the genetic algorithm, the selections were made such that the generated stego image experienced the least change relative to the cover image. The results of comparing this method with the existing methods in low- and high-level embedding showed that the proposed method was successful in producing stego images with high-quality criteria. In addition, the SPAM steganalysis method did not show high accuracy in its detection. One of the benefits of the proposed method is the need for a short key to embed and extract the secret message. This issue increases the security and feasibility of the proposed method.
 Abbas Cheddad, Joan Condell, Kevin Curran, and Paul Mc Kevitt. Digital image steganography: Survey and analysis of current methods. Signal processing, 90(3):727–752, 2010.
 Mehdi Hussain, Ainuddin Wahid Abdul Wahab, Yamani Idna Bin Idris, Anthony TS Ho, and KiHyun Jung. Image steganography in spatial domain: A survey. Signal Processing: Image Communication, 65:46–66, 2018.
 Eugene T Lin and Edward J Delp. A review of data hiding in digital images. In PICS, volume 299, pages 274–278, 1999.
 Gyan Singh Yadav and Aparajita Ojha. Hamiltonian path based image steganography scheme with improved imperceptibility and undetectability. Applied Soft Computing, 73:497–507, 2018.
 Gandharba Swain and Saroj Kumar Lenka. Classification of image steganography techniques in spatial domain: a study. Journal of Computer Science & Engineering Technology (IJCSET), 5(03):219–232, 2014.
 S Arunkumar, V Subramaniyaswamy, V Vijayakumar, Naveen Chilamkurti, and R Logesh. Svd-based robust image steganographic scheme using riwt and dct for secure transmission of medical images. Measurement, 139:426–437, 2019.
 Manashee Kalita and Themrichon Tuithung. A comparative study of steganography algorithms of spatial and transform domain. International Journal of Computer Applications, 975:8887, 2016.
 Katzenbeisser Stefan, Petitcolas Fabien AP, et al.Information hiding techniques for steganography and digital watermarking. 2000.
 Shiv K Sahu, Shachi Sahu, Vahid Nourani, Chief Advisory Board, Uma Shanker, Rama Shanker, Vinita Kumari, Kapil Kumar Bansal, Deepak Garg, Vijay Anant Athavale, et al.Untitled-international journal of engineering and advanced.
 St´ephane Mallat. A wavelet tour of signal processing. Elsevier, 1999.
 Ingrid Daubechies. Ten lectures on wavelets.SIAM, 1992.
 Aparna Vyas and Joonki Paik. Review of the application of wavelet theory to image processing. IEIE Transactions on Smart Processing and Computing, 5(6):403–417, 2016.
 Inas Jawad Kadhim, Prashan Premaratne, and Peter James Vial. High capacity adaptive image steganography with cover region selection using dual-tree complex wavelet transform. Cognitive Systems Research, 60:20–32, 2020.
 KB Raja, Kiran Kumar, Satish Kumar, MS Lakshmi, H Preeti, KR Venugopal, and Lalit M Patnaik. Genetic algorithm based steganography using wavelets. In International Conference on Information Systems Security, pages 51–63. Springer, 2007.
 Elham Ghasemi, Jamshid Shanbehzadeh, and Nima Fassihi. High capacity image steganography based on genetic algorithm and wavelet transform. In Intelligent Control and Innovative Computing, pages 395–404. Springer, 2012.
 Avinash K Gulve and Madhuri S Joshi. An image steganography method hiding secret data into coefficients of integer wavelet transform using pixel value differencing approach. Mathematical Problems in Engineering, 2015, 2015.
 Hayat Al-Dmour and Ahmed Al-Ani. A steganography embedding method based on edge identification and xor coding. Expert systems with Applications, 46:293–306, 2016.
 Aref Miri and Karim Faez. Adaptive image steganography based on transform domain via genetic algorithm. Optik, 145:158–168, 2017.
 Aref Miri and Karim Faez. An image steganography method based on integer wavelet transform. Multimedia Tools and Applications, 77(11):13133–13144, 2018.
 Sabyasachi Pramanik, RP Singh, and Ramkrishna Ghosh. Application of bi-orthogonal wavelet transform and genetic algorithm in image steganography. Multimedia Tools & Applications, 79, 2020.
 Pranab K Muhuri, Zubair Ashraf, and Swati Goel. A novel image steganographic method based on integer wavelet transformation and particle swarm optimization. Applied Soft Computing, 92:106257, 2020.
 Hamidreza Rashidy Kanan and Bahram Nazeri. A novel image steganography scheme with high embedding capacity and tunable visual image quality based on a genetic algorithm. Expert systems with applications, 41(14):6123–6130, 2014.
 Ran-Zan Wang, Chi-Fang Lin, and Ja-Chen Lin. Image hiding by optimal lsb substitution and genetic algorithm. Pattern recognition, 34(3):671–683, 2001.
 Pratik D Shah and RS Bichkar. A secure spatial domain image steganography using genetic algorithm and linear congruential generator. In International Conference on Intelligent Computing and Applications, pages 119–129. Springer, 2018.
 Ranyiah Wazirali, Waleed Alasmary, Mohamed MEA Mahmoud, and Ahmad Alhindi. An optimized steganography hiding capacity and imperceptibly using genetic algorithms. IEEE Access, 7:133496–133508, 2019.
 Lifang Yu, Yao Zhao, Rongrong Ni, and Zhenfeng Zhu. Pm1 steganography in jpeg images using genetic algorithm. Soft Computing, 13(4):393–400, 2009.
 V Sabeti, S Faiazi, and H Shirinkhah. Improving security of lsbm steganography using of genetic algorithm, mmulti-key and blocking. 2020.
 Rinita Roy and Sumit Laha. Optimization of stego image retaining secret information using genetic algorithm with 8-connected psnr. Procedia Computer Science, 60:468–477, 2015.
 Amrita Khamrui, Diotima Dutta Gupta, Shatadal Ghosh, and Sambhunath Nandy. A spatial domain image authentication technique using genetic algorithm. In International Conference on Computational Intelligence, Communications, and Business Analytics, pages 577–584. Springer, 2017.
 SI Nipanikar, V Hima Deepthi, and Nikita Kulkarni. A sparse representation based image steganography using particle swarm optimization and wavelet transform. Alexandria engineering journal, 57(4):2343–2356, 2018.
 Sahib Khan and Tiziano Bianchi. Ant colony optimization (aco) based data hiding in image complex region. International Journal of Electrical & Computer Engineering (2088-8708), 8(1), 2018.
 Anan Banharnsakun. Artificial bee colony approach for enhancing lsb based image steganography. Multimedia Tools and Applications, 77(20):27491–27504, 2018.
 Chun-Hsien Chou and Yun-Chin Li. A perceptually tuned subband image coder based on the measure of just-noticeable-distortion profile. IEEE Transactions on circuits and systems for video technology, 5(6):467–476, 1995.
 Tom´aˇs Pevny, Patrick Bas, and Jessica Fridrich. Steganalysis by subtractive pixel adjacency matrix. IEEE Transactions on information Forensics and Security, 5(2):215–224, 2010.