High Security and Robustness Image Steganography Based On Ant Colony Optimization Algorithms and Discrete Cosine Transform

Authors

  • Department of Basic Sciences, College of Nursing, University of Baghdad, IRAQ
  • Department of Computer Systems, Technical Institute- Suwaira, Middle Technical University, IRAQ

DOI:

https://doi.org/10.32792/jeps.v13i4.370

Abstract

Abstract
Steganography, which is the science of delivering a message between parties in a way that an
eavesdropper will not be aware that the message exists, is one of the key disciplines that have a considerable interest in fields. The suggested method seeks to conceal a smaller color image within a larger color image. It utilizes the transform domain throughout the steganography process to increase its resistance to changes and treatments made to the cover image. In order to achieve both complexity security and robustness, the project seeks to implement and utilize two techniques: ant colony optimization and transformation domain approach. The technologies under consideration suggest a Steganography method for digital photographs. It employs Discrete Cosine Transform (DCT) to achieve the same aims in terms of security, transparency and robustness. Additionally, it makes use of Once an Ant Colony Optimization (ACO) to increase robustness against signal processing attacks and imperceptibility in accordance with the human visual system. This work implements ACO for the cover to find the embedding locations on the graph path, and then finds locations to hide information based on threshold method, when looking for places to hide information blocks, DCT uses an intelligent block matching technique between the embedded image and the cover image, and both systems were tested against each other to compare their performance. Six stages make up the proposed secret key steganography system: test, transform, key creation and substitution, ant colony optimization, matching, inverse transform, and key encryption and concealing.

References

. Reddy, G. D., Kiran, Y. V. U., Singh, P., Singh, S. V., Shaw, S., & Singh, J. (2022, October). A Proficient and secure way of Transmission using Cryptography and Steganography. In 2022 2nd International Conference on Technological Advancements in Computational Sciences (ICTACS) (pp. 582-586). IEEE.

. Al-Nofaie, S., Gutub, A., & Al-Ghamdi, M. (2021). Enhancing Arabic text steganography for personal usage utilizing pseudo-spaces. Journal of King Saud University-Computer and Information Sciences, 33(8), 963-974.

. Fateh, M., Rezvani, M., & Irani, Y. (2021). A new method of coding for steganography based on LSB matching revisited. Security and Communication Networks, 2021, 1-15.

. Zhang, Y., Lu, H., & Abbas, H. (2018). Mobile Intelligence Assisted by Data Analytics and Cognitive Computing. Wireless Communications and Mobile Computing, 2018, 1-2.

. Hamano, G., Imaizumi, S., & Kiya, H. (2023). Effects of JPEG Compression on Vision Transformer Image Classification for Encryption-then-Compression Images. Sensors, 23(7), 3400.

. Zhang, Y., Luo, X., Wang, J., Guo, Y., & Liu, F. (2021). Image robust adaptive steganography adapted to lossy channels in open social networks. Information Sciences, 564, 306-326.

. Tao, H., Chongmin, L., Zain, J. M., & Abdalla, A. N. (2014). Robust image watermarking theories and techniques: A review. Journal of applied research and technology, 12(1), 122-138.

. Zhang, Y., Wang, C., Wang, X., & Wang, M. (2017). Feature-based image watermarking algorithm using SVD and APBT for copyright protection. future internet, 9(2), 13.

. Makhdoom, I., Abolhasan, M., & Lipman, J. (2022). A comprehensive survey of covert communication techniques, limitations and future challenges. Computers & Security, 120, 102784.

. Kaur, H., & Rani, J. (2016). A Survey on different techniques of steganography. In MATEC web of conferences (Vol. 57, p. 02003). EDP Sciences.

. Boryczka, M., & Kazana, G. (2023). Hiding Information in Digital Images Using Ant Algorithms. Entropy, 25(7), 963.

. Gnanalakshmi, V., & Indumathi, G. (2023). A review on image steganographic techniques based on optimization algorithms for secret communication. MULTIMEDIA TOOLS AND APPLICATIONS.

. Saini, K. (2017). A review on video steganography techniques in spatial domain. 2017 Recent Developments in Control, Automation & Power Engineering (RDCAPE), 366-371.

. Priya, A. (2018). High capacity and optimized image steganography technique based on ant colony optimization algorithm. International Journal of Emerging Technology and Innovative Engineering, 4(6).

. Bajracharya, R., Shrestha, R., Hassan, S. A., Jung, H., & Shin, H. (2023). 5G and Beyond Private Military Communication: Trend, Requirements, Challenges and Enablers. IEEE Access.

. Subramanian, N., Elharrouss, O., Al-Maadeed, S., & Bouridane, A. (2021). Image steganography: A review of the recent advances. IEEE access, 9, 23409-23423.

. Li, H., & Guo, X. (2018). Embedding and extracting digital watermark based on DCT algorithm. Journal of Computer and Communications, 6(11), 287-298.

. Sharma, V., & Mir, R. N. (2022). An enhanced time efficient technique for image watermarking using ant colony optimization and light gradient boosting algorithm. Journal of King Saud University-Computer and Information Sciences, 34(3), 615-626.

. Ali, M., Wook Ahn, C., Pant, M., Kumar, S., Singh, M. K., & Saini, D. (2020). An optimized digital watermarking scheme based on invariant DC coefficients in spatial domain. Electronics, 9(9), 1428.

. Liu, C., & Ding, Q. (2020). A color image encryption scheme based on a novel 3d chaotic mapping. Complexity, 2020, 1-20.

. Lu, W., Zhang, J., Zhao, X., Zhang, W., & Huang, J. (2020). Secure robust JPEG steganography based on autoencoder with adaptive BCH encoding. IEEE Transactions on Circuits and Systems for Video Technology, 31(7), 2909-2922.

. Pan, P., Wu, Z., Yang, C., & Zhao, B. (2022). Double-matrix decomposition image steganography scheme based on wavelet transform with multi-region coverage. Entropy, 24(2), 246.

. Zhang, Y. Q., Zhong, K., & Wang, X. Y. (2022). High-Capacity Image Steganography Based on Discrete Hadamard Transform. IEEE Access, 10, 65141-65155.

. Gaertner, D., & Clark, K. L. (2005, June). On Optimal Parameters for Ant Colony Optimization Algorithms. In IC-AI (pp. 83-89).

. Zebari, D. A., Zeebaree, D. Q., Saeed, J. N., Zebari, N. A., & Adel, A. Z. (2020). Image steganography based on swarm intelligence algorithms: A survey. people, 7(8), 9.

. Thakkar, F., & Srivastava, V. K. (2017). A particle swarm optimization and block-SVD-based watermarking for digital images. Turkish Journal of Electrical Engineering and Computer Sciences, 25(4), 3273-3288.

. Singhal, V., Shukla, Y. K., & Praksash, N. (2020). Image steganography embedded with advance encryption standard (AES) securing with SHA-256. International Journal of Innovative Technology and Exploring Engineering (IJITEE), 9(8).

. Riabko, A. V., Zaika, O. V., Kukharchuk, R. P., Vakaliuk, T. A., & Hordiienko, I. V. (2022, June). Algorithm of ant colony optimization (ACO) for 3D variation traveling salesman problem. In Journal of Physics: Conference Series (Vol. 2288, No. 1, p. 012001). IOP Publishing.

. Nayyar, A., & Singh, R. (2016, March). Ant colony optimization—computational swarm intelligence technique. In 2016 3rd International conference on computing for sustainable global development (INDIACom) (pp. 1493-1499). IEEE.

. Khan, S., & Bianchi, T. (2018). Ant Colony Optimization (ACO) based Data Hiding in Image Complex Region. International Journal of Electrical & Computer Engineering (2088-8708), 8(1).

. Ning, J., Zhang, Q., Zhang, C., & Zhang, B. (2018). A best-path-updating information-guided ant colony optimization algorithm. Information Sciences, 433, 142-162.

. Ignatious, N., & Ali, S. (2019, November). Identifying A Regression Test Prioritization Technique and Proposing A Tool for Automation for Trade me Website. In CS & IT Conference Proceedings (Vol. 9, No. 14). CS & IT Conference Proceedings.

. Alomoush, W., Khashan, O. A., Alrosan, A., Attar, H. H., Almomani, A., Alhosban, F., & Makhadmeh, S. N. (2023). Digital image watermarking using discrete cosine transformation based linear modulation. Journal of Cloud Computing, 12(1), 1-17.

. Shawahna, A., Haque, M. E., & Amin, A. (2019). JPEG image compression using the discrete cosine transform: an overview, applications, and hardware implementation. arXiv preprint arXiv:1912.10789.

. Raid, A. M., Khedr, W. M., El-Dosuky, M. A., & Ahmed, W. (2014). Jpeg image compression using discrete cosine transform-A survey. arXiv preprint arXiv:1405.6147.

. Abdulrazzaq, S. T., Rasheed, M. H., & Siddeq, M. M. (2023). The multi-quantization process with matrix size reduction is applied to compress images with strip structure light that is commonly used in 3D reconstructions.

. Nikoukhah, T., Colom, M., Morel, J. M., & von Gioi, R. G. (2022). A Reliable JPEG Quantization Table Estimator. Image Processing On Line, 12, 173-197.

. Senthooran, V., & Ranathunga, L. (2014, August). DCT coefficient dependent quantization table modification steganographic algorithm. In 2014 First International Conference on Networks & Soft Computing (ICNSC2014) (pp. 432-436). IEEE.

. Ghosh, D., Chattopadhyay, A. K., Chanda, K., & Nag, A. (2020). A Secure Steganography Scheme Using LFSR. In Emerging Technology in Modelling and Graphics: Proceedings of IEM Graph 2018 (pp. 713-720). Springer Singapore.

. Siahaan, A. P. U., Ikhwan, A., & Aryza, S. (2018). A novelty of data mining for promoting education based on FP-growth algorithm.

. Kollin, F., & Bavey, A. (2017). Ant colony optimization algorithms: pheromone techniques for TSP

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Published

2023-12-03