Optimized Cover Selection for Audio Steganography Using Multi-Objective Evolutionary Algorithm
DOI:
https://doi.org/10.32890/jict2023.22.2.5Keywords:
Audio Steganography, Cover Audio Selection, trade-off, Multiobjective Optimisation ProblemAbstract
Existing embedding techniques depend on cover audio selected by users. Unknowingly, users may make a poor cover audio selection
that is not optimised in its capacity or imperceptibility features, which could reduce the effectiveness of any embedding technique. As a trade-off exists between capacity and imperceptibility, producing a method focused on optimising both features is crucial. One of
the search methods commonly used to find solutions for the trade-off problem in various fields is the Multi-Objective Evolutionary Algorithm (MOEA). Therefore, this research proposed a new method for optimising cover audio selection for audio steganography using the Non-dominated Sorting Genetic Algorithm-II (NSGA-II), which falls under the MOEA Pareto dominance paradigm. The proposed method provided suggestions for cover audio to users based on imperceptibility and capacity features. The sample difference calculation was initially formulated to determine the maximum capacity for each cover audio defined in the cover audio database. Next, NSGA-II was implemented to determine the optimised solutions based on the parameters provided by each chromosome. The experimental results demonstrated the effectiveness of the proposed method as it managed to dominate the
solutions from the previous method selected based on one criterion only. In addition, the proposed method considered that the trade-off managed to select the solution as the highest priority compared to the previous method, which put the same solution as low as 71 in the priority ranking. In conclusion, the method optimised the cover audio selected, thus, improving the effectiveness of the audio steganography used. It can be a response to help people whose computers and mobile devices continue to be unfamiliar with audio steganography in an age where information security is crucial.
References
Abdul Sattar, I., & Talib Gaata, M. (2017, March). Image steganography technique based on adaptive random key generator with suitable cover selection. In Annual Conference on New Trends in Information & Communications Technology Applications (NTICT’2017) (pp. 208–212). IEEE.
Ahani, S., Ghaemmaghami, S., & Wang, Z. J. (2015). A sparse representation based wavelet domain speech steganography method. IEEE/ACM Transactions on Audio Speech and Language Processing, 23(1), 80–91. https://doi.org/10.1109/ TASLP.2014.2372313
Ali, A. H., Mokhtar, M. R., & George, L. E. (2017). Enhancing the hiding capacity of audio steganography based on block mapping. Journal of Theoretical and Applied Information Technology, 95(7), 1441–1448.
Alsabhany, Ahmed A., Ridzuan, F., & Azni, A. H. (2020). The progressive multilevel embedding method for audio steganography. Journal of Physics: Conference Series, 1551(1). https://doi.org/10.1088/1742-6596/1551/1/012011
Alsabhany, Ahmed Abduljabbar, Ridzuan, F., & Azni, A. H. (2019). The adaptive multi-level phase coding method in audio steganography. IEEE Access, 7, 129291–129306. https://doi.org/10.1109/ACCESS.2019.2940640
Amirtharajan, R., & Rayappan, J. B. B. (2013). Steganography - Time to time: A review. Research Journal of Information Technology, 5(2), 53–66.
Ballesteros, D. M. L., & Moreno, J. M. A. (2012). Highly transparent steganography model of speech signals using efficient wavelet masking. Expert Systems with Applications, 39(10), 9141–9149. https://doi.org/10.1016/j.eswa.2012.02.066
Bazyar, M., & Sudirman, R. (2015). A new method to increase the capacity of audio steganography based on the LSB algorithm. Jurnal Teknologi, 6, 49–53.
Bender, W., & Gruhl, D. (1996). Techniques for data hiding. IBM Systems Journal, 35.3.4(1996), 313–336. https://doi.org/10.1147/sj.353.0313 Journal of ICT, 22, No. 2 (April) 2023, pp: 255–
Chiandussi, G., Codegone, M., Ferrero, S., & Varesio, F. E. (2012). Comparison of multi-objective optimization methodologies for engineering applications. Computers and Mathematics with Applications, 63(5), 912–942. https://doi.org/10.1016/j. camwa.2011.11.057
Cvejic, N., & Seppänen, T. (2002, October). A wavelet domain LSB insertion algorithm for high capacity audio steganography. In Proceedings of 2002 IEEE 10th Digital Signal Processing Workshop, 2002 and the 2nd Signal Processing Education Workshop (pp. 53–55). IEEE. https://doi.org/10.1109/ DSPWS.2002.1231075
Deb, K, Pratap, A., Agarwal, S., & Meyarivan, T. (2002). A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation, 6(2), 182–197.
Deb, Kalyanmoy. (2000). Multi-objective optimization using evolutionary algorithms: An introduction. Multi-Objective Evolutionary Optimisation for Product Design and Manufacturing, 6(3), 1–24. https://doi.org/2011003
Djebbar, F., Ayad, B., Meraim, K. A., & Hamam, H. (2012). Comparative study of digital audio steganography techniques. EURASIP Journal on Audio, Speech, and Music Processing, 2012(25), 1–16. https://doi.org/10.1186/1687-4722-2012-25
Durafe, A., & Patidar, V. (2022). Development and analysis of IWT-SVD and DWT-SVD steganography using fractal cover. Journal of King Saud University - Computer and Information Sciences, 34(7), 4483–4498. https://doi.org/10.1016/j.jksuci.2020.10.008
Dutta, H., Das, R. K., Nandi, S., & Prasanna, S. R. M. (2019). An overview of digital audio steganography. IETE Technical Review (Institution of Electronics and Telecommunication Engineers, India), 37(6), 1–19. https://doi.org/10.1080/02564 602.2019.1699454
Gopalan, K., & Shi, Q. (2010, August). Audio steganography using bit modification – A Tradeoff on perceptibility and data robustness for large payload audio embedding. In 2010 Proceedings of 19th International Conference on Computer Communications and Networks (pp. 1–6). IEEE.
Hajduk, V., & Levický, D. (2018, April). Cover selection steganography with intra-image scanning. In 2018 28th International Conference Radioelektronika (RADIOELEKTRONIKA) (pp. 1–4). IEEE. Journal of ICT, 22, No. 2 (April) 2023, pp: 255–
Hameed, M. A., Hassaballah, M., Aly, S., & Awad, A. I. (2019). An adaptive image steganography method based on histogram of oriented gradient and PVD-LSB techniques. IEEE Access, 7, 185189–185204. https://doi.org/10.1109/ ACCESS.2019.2960254
Indrayani, R. (2020, November). Modified LSB on audio steganography using WAV format. In 2020 3rd International Conference on Information and Communications Technology (ICOIACT 2020) (pp. 466–470). IEEE. https://doi.org/10.1109/ ICOIACT50329.2020.9332132
Jayapandiyan, J. R., Kavitha, C., & Sakthivel, K. (2020). Enhanced least significant bit replacement algorithm in spatial domain of steganography using character sequence optimization. IEEE Access, 8, 136537–136545. https://doi.org/10.1109/ ACCESS.2020.3009234
Deb, K. (2001). Multi-objective optimization using evolutionary algorithms. Wiley.
Kaur, A., Dutta, M. K., Soni, K. M., & Taneja, N. (2017). Localized & self adaptive audio watermarking algorithm in the wavelet domain. Journal of Information Security and Applications, 33, 1–15. https://doi.org/10.1016/j.jisa.2016.12.003
Khairullah, M. (2019). A novel steganography method using transliteration of Bengali text. Journal of King Saud University - Computer and Information Sciences, 31(3), 348–366. https://doi.org/10.1016/j.jksuci.2018.01.008
Kunkle, D. (2005). A summary and comparison of MOEA algorithms. Northeastern University, Boston, Massachusetts.
Li, B., Li, J., Tang, K. E., & Yao, X. I. N. (2015). Many-objective evolutionary algorithms: A survey. ACM Computing Surveys (CSUR), 48(1), 1–37.
Mashwani, W. K., Salhi, A., Jan, M. A., Sulaiman, M., Adeeb Khanum, R., & Algarni, A. (2016). Evolutionary algorithms based on decomposition and indicator functions: State-of-the-art survey. International Journal of Advanced Computer Science and Applications (IJACSA), 7(2), 583–593.
Nursalman, M., Rachman, J. R., & Sidik, F. (2018, October). Implementation of low bit coding algorithm and cipher block with electronic code book mode for data legality in audio steganographic streaming. In 2018 International Conference on Information Technology Systems and Innovation (ICITSI 2018) (pp. 330–335). IEEE. https://doi.org/10.1109/ ICITSI.2018.8695921 Journal of ICT, 22, No. 2 (April) 2023, pp: 255–
Rashid, R. D. (2020). Cover image selection for embedding based on different criteria. In Mobile Multimedia/Image Processing, Security, and Applications 2020, vol. 11399, pp. 179–188. SPIE, 2020. https://doi.org/10.1117/12.2560720
Rustad, S., Setiadi, D. R. I. M., Syukur, A., & Andono, P. N. (2022). Inverted LSB image steganography using adaptive pattern to improve imperceptibility. Journal of King Saud University - Computer and Information Sciences, 34(6), 3559–3568. https://doi.org/10.1016/j.jksuci.2020.12.017
Sahu, A. K., & Swain, G. (2022). High fidelity based reversible data hiding using modified LSB matching and pixel difference. Journal of King Saud University - Computer and Information Sciences, 34(4), 1395–1409. https://doi.org/10.1016/j. jksuci.2019.07.004
Sajedi, H., & Jamzad, M. (2008, July). Cover selection steganography method based on similarity of image blocks. In Proceedings - 8th IEEE International Conference on Computer and Information Technology Workshops (CIT Workshops 2008) (pp. 379–384). IEEE. https://doi.org/10.1109/CIT.2008.Workshops.34
Setiadi, D. R. I. M. (2022). Improved payload capacity in LSB image steganography uses dilated hybrid edge detection. Journal of King Saud University - Computer and Information Sciences, 34(2), 104–114. https://doi.org/10.1016/j.jksuci.2019.12.007
Shah, P. D., & Bichkar, R. S. (2020, June). Genetic algorithm based approach to select suitable cover image for image steganography. In 2020 International Conference for Emerging Technology (INCET 2020) (pp. 1–5). https://doi.org/10.1109/ INCET49848.2020.9154032
Siinivas, N., & Deb, K. (1994). Multiobjective optimization using nondominated sorting in genetic algorithms. Evolutionary Computation, 2(3), 221–248.
Singh, K. U. (2014). A survey on audio steganography approaches. International Journal of Computer Applications, 95(14), 7–14.
Solak, S. (2020). High embedding capacity data hiding technique based on EMSD and LSB substitution algorithms. IEEE Access, 8, 166513–166524. https://doi.org/10.1109/ ACCESS.2020.3023197
Somani, H., & Madhu, K. M. (2015). A survey on digital audio steganography techniques used for secure transmission of data. International Journal of Engineering Development and Research, 3(4), 236–239. Journal of ICT, 22, No. 2 (April) 2023, pp: 255–
Srivastava, M., & Rafiq, M. Q. (2012). A novel approach to secure communication using audio steganography. Advanced Materials Research, 408, 963–969.
Tabares-Soto, R., Raúl, R. P., & Gustavo, I. (2019). Deep learning applied to steganalysis of digital images: A systematic review. IEEE Access, 7, 68970–68990. https://doi.org/10.1109/ ACCESS.2019.2918086
Vimal, J. (2014). Literature review on audio steganographic techniques. International Journal of Engineering Trends and Technology, 11(5), 246–248. http://www.ijettjournal.org
Wakiyama, M., Hidaka, Y., & Nozaki, K. (2010, October). An audio steganography by a low-bit coding method with wave files. In 2010 6th International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIHMSP 2010) (pp. 530–533). IEEE.
Wang, J., Jia, X., Kang, X., & Shi, Y. Q. (2019). A cover selection hevc video steganography based on intra prediction mode. IEEE Access, 7, 119393–119402. https://doi.org/10.1109/ ACCESS.2019.2936614
Wang, Z., & Zhang, X. (2019). Secure cover selection for steganography. IEEE Access, 7, 57857–57867. https://doi.org/10.1109/ACCESS.2019.2914226
Wang, Z., Zhang, X., & Qian, Z. (2020). Practical cover selection for steganography. IEEE Signal Processing Letters, 27(c), 71–75. https://doi.org/10.1109/LSP.2019.2956416
Xin, L., & Jiaojiao, Y. (2018, April). Two embedding strategies for payload distribution in multiple images steganography. In 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), (pp. 1982–1986). IEEE.
Yasear, S. A., & Ku-Mahamud, K. R. (2021). Review of multi-objective swarm intelligence optimization algorithms. Journal of Information and Communication Technology, 20(2), 171–211. https://doi.org/10.32890/jict2021.20.2.3
Ye, D., Jiang, S., & Huang, J. (2019). Heard more than heard: An audio steganography method based on GAN. ArXiv Preprint ArXiv:1907.04986., 1–13. http://arxiv.org/abs/1907.04986
Zhou, A., Qu, B., Li, H., Zhao, S., & Nagaratnam, P. (2011). Multiobjective evolutionary algorithms: A survey of the state of the art. Swarm and Evolutionary Computation, 1(1), 32–49. https://doi.org/10.1016/j.swevo.2011.03.001
Zumchak, S. M. (2016). Audio steganography: A comparative study of techniques and tools. [Doctoral dissertation, Utica College].
Published
Issue
Section
License
Copyright (c) 2023 Journal of Information and Communication Technology

This work is licensed under a Creative Commons Attribution 4.0 International License.
How to Cite
Research impact
Harvested 2026-09-06Counts differ between services because each indexes a different body of literature. None of them is the whole picture.
2002 - 2020






















