Hiding Information in Digital Images Using Ant Algorithms
Stenographic methods are closely related to the security and confidentiality of communications, which have always been essential domains of human life. Steganography itself is a science dedicated to the process of hiding information in public communication channels. Its main idea is to use digital f...
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-06-01
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| Series: | Entropy |
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| Online Access: | https://www.mdpi.com/1099-4300/25/7/963 |
| _version_ | 1797589448193474560 |
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| author | Mariusz Boryczka Grzegorz Kazana |
| author_facet | Mariusz Boryczka Grzegorz Kazana |
| author_sort | Mariusz Boryczka |
| collection | DOAJ |
| description | Stenographic methods are closely related to the security and confidentiality of communications, which have always been essential domains of human life. Steganography itself is a science dedicated to the process of hiding information in public communication channels. Its main idea is to use digital files or even communication protocols as a medium inside which data are hidden. The present research aims to investigate the applicability of ant algorithms in steganography and evaluate the effectiveness of this approach. Ant systems could be employed both in spatial and frequency-based image steganography. The combination of frequency domain and optimization method to increase robustness is used, and an integer wavelet transform is performed on the host image. ACO optimization is used to find the optimal coefficients describing where to hide the data. The other method utilizes ACO to determine the optimal pixel locations for embedding secret data in the cover image. ACO is also used to detect complex regions of the cover image. Afterward, the least-significant-bits (LSB) substitution is used to hide secret information in the detected complex regions’ pixels. Our study focuses on optimizing two mutually exclusive features of steganograms—high capacity and low distortion. An attempt was made to use ant systems to select areas of digital images that allow the greatest amount of information to be hidden with the least loss of image quality. The effect of variants of the ant system and its parameters on the quality of the results obtained was also investigated, and the final effectiveness of the proposed method was evaluated. The results of the experiments were compared with those published in related articles. The proposed procedures proved to be effective and allowed the embedding of large amounts of data with relatively little impact on image quality. |
| first_indexed | 2024-03-11T01:06:50Z |
| format | Article |
| id | doaj.art-797dd67910dc41f69fa0dfbd309bb273 |
| institution | Directory Open Access Journal |
| issn | 1099-4300 |
| language | English |
| last_indexed | 2024-03-11T01:06:50Z |
| publishDate | 2023-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj.art-797dd67910dc41f69fa0dfbd309bb2732023-11-18T19:12:39ZengMDPI AGEntropy1099-43002023-06-0125796310.3390/e25070963Hiding Information in Digital Images Using Ant AlgorithmsMariusz Boryczka0Grzegorz Kazana1Institute of Computer Science, University of Silesia in Katowice, Bedzińska 39, 41-200 Sosnowiec, PolandSkyGate, Chris Parjaszewski, Rynek 6, 44-100 Gliwice, PolandStenographic methods are closely related to the security and confidentiality of communications, which have always been essential domains of human life. Steganography itself is a science dedicated to the process of hiding information in public communication channels. Its main idea is to use digital files or even communication protocols as a medium inside which data are hidden. The present research aims to investigate the applicability of ant algorithms in steganography and evaluate the effectiveness of this approach. Ant systems could be employed both in spatial and frequency-based image steganography. The combination of frequency domain and optimization method to increase robustness is used, and an integer wavelet transform is performed on the host image. ACO optimization is used to find the optimal coefficients describing where to hide the data. The other method utilizes ACO to determine the optimal pixel locations for embedding secret data in the cover image. ACO is also used to detect complex regions of the cover image. Afterward, the least-significant-bits (LSB) substitution is used to hide secret information in the detected complex regions’ pixels. Our study focuses on optimizing two mutually exclusive features of steganograms—high capacity and low distortion. An attempt was made to use ant systems to select areas of digital images that allow the greatest amount of information to be hidden with the least loss of image quality. The effect of variants of the ant system and its parameters on the quality of the results obtained was also investigated, and the final effectiveness of the proposed method was evaluated. The results of the experiments were compared with those published in related articles. The proposed procedures proved to be effective and allowed the embedding of large amounts of data with relatively little impact on image quality.https://www.mdpi.com/1099-4300/25/7/963steganographydigital imageant algorithmshigh capacitylow distortion |
| spellingShingle | Mariusz Boryczka Grzegorz Kazana Hiding Information in Digital Images Using Ant Algorithms Entropy steganography digital image ant algorithms high capacity low distortion |
| title | Hiding Information in Digital Images Using Ant Algorithms |
| title_full | Hiding Information in Digital Images Using Ant Algorithms |
| title_fullStr | Hiding Information in Digital Images Using Ant Algorithms |
| title_full_unstemmed | Hiding Information in Digital Images Using Ant Algorithms |
| title_short | Hiding Information in Digital Images Using Ant Algorithms |
| title_sort | hiding information in digital images using ant algorithms |
| topic | steganography digital image ant algorithms high capacity low distortion |
| url | https://www.mdpi.com/1099-4300/25/7/963 |
| work_keys_str_mv | AT mariuszboryczka hidinginformationindigitalimagesusingantalgorithms AT grzegorzkazana hidinginformationindigitalimagesusingantalgorithms |