Enhancing Secure Medical Data Communication Through Integration of LSB and DCT for Robust Analysis in Image Steganography
Steganography enhances data security by embedding information seamlessly within digital channels. While hospital systems focus on text and visuals in medical images, audio integration remains an overlooked area with untapped potential. This research addresses the security gap by exploring the embedd...
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IEEE
2025-01-01
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| Online Access: | https://ieeexplore.ieee.org/document/10816414/ |
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| author | Ramyashree P. S. Venugopala S. Raghavendra Vijay S. Kubihal |
| author_facet | Ramyashree P. S. Venugopala S. Raghavendra Vijay S. Kubihal |
| author_sort | Ramyashree |
| collection | DOAJ |
| description | Steganography enhances data security by embedding information seamlessly within digital channels. While hospital systems focus on text and visuals in medical images, audio integration remains an overlooked area with untapped potential. This research addresses the security gap by exploring the embedding of audio data in medical images to enhance patient record protection and information integrity. The Proposed work introduced an innovative Steganography approach for medical image data by embedding Audio files aiming to addresses this research gap. This method integrate audio data into medical images, specifically DICOM-standard images without compromising their visual integrity. It also preserves the integrity of DICOM metadata, ensuring compliance with medical imaging standards. The Least Significant Bit (LSB) and Discrete Cosine Transform (DCT) steganography techniques are used to embed audio file data into medical images. The study illustrates the effectiveness of LSB and DCT techniques on a computed tomography(CT) Images. The LSB method is renowned for its simplicity and its ability to extract data without introducing errors. Additionally, the method offers efficient insertion and extraction time during the watermark embedding and retrieval process, making it highly practical for real-time applications. An algorithm employs DCT technique for Audio integration within DICOM images are more robust and imperceptible. Both techniques have been proven to be highly precise and supported by empirical evidence such as PSNR, SSIM, and MSE analysis. Robustness analysis was conducted on various image quality variation scenarios that includes compression level, resolution and noise tolerance. The proposed DCT approach achieves a PSNR of 57.89 dB, SSIM of 0.9997, and MSE of 0.013, demonstrating minimal distortion and superior structural integrity. Robustness analysis shows that DCT outperforms the LSB method, consistently maintaining PSNR above 47 dB, MSE approximately zero, and SSIM at 0.99 across varying compression levels, image resolutions, and noise conditions. After conducting an experiment, the DCT technique is the most suitable approach for secure communication of medical data with capacity of 2.03 bits per pixel (bpp). The overall analysis of proposed work significantly improves result in terms of the security and robustness under various attacks. |
| format | Article |
| id | doaj-art-337856df8de446c7be57860100f0d53b |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-337856df8de446c7be57860100f0d53b2025-01-07T00:01:29ZengIEEEIEEE Access2169-35362025-01-01131566158010.1109/ACCESS.2024.352295710816414Enhancing Secure Medical Data Communication Through Integration of LSB and DCT for Robust Analysis in Image Steganography Ramyashree0https://orcid.org/0000-0002-0237-2444P. S. Venugopala1S. Raghavendra2https://orcid.org/0000-0003-2733-3916Vijay S. Kubihal3https://orcid.org/0000-0001-9927-8544Department of Information and Communication Technology, Manipal Academy of Higher Education, Manipal Institute of Technology, Manipal, IndiaDepartment of Artificial Intelligence and Data Science, NMAM Institute of Technology, NITTE (Deemed to be University), Nitte, Karnataka, IndiaDepartment of Information and Communication Technology, Manipal Academy of Higher Education, Manipal Institute of Technology, Manipal, IndiaDepartment of Radiodiagnosis, K. S. Hegde Medical Academy, NITTE (Deemed to be University), Deralakatte, Karnataka, IndiaSteganography enhances data security by embedding information seamlessly within digital channels. While hospital systems focus on text and visuals in medical images, audio integration remains an overlooked area with untapped potential. This research addresses the security gap by exploring the embedding of audio data in medical images to enhance patient record protection and information integrity. The Proposed work introduced an innovative Steganography approach for medical image data by embedding Audio files aiming to addresses this research gap. This method integrate audio data into medical images, specifically DICOM-standard images without compromising their visual integrity. It also preserves the integrity of DICOM metadata, ensuring compliance with medical imaging standards. The Least Significant Bit (LSB) and Discrete Cosine Transform (DCT) steganography techniques are used to embed audio file data into medical images. The study illustrates the effectiveness of LSB and DCT techniques on a computed tomography(CT) Images. The LSB method is renowned for its simplicity and its ability to extract data without introducing errors. Additionally, the method offers efficient insertion and extraction time during the watermark embedding and retrieval process, making it highly practical for real-time applications. An algorithm employs DCT technique for Audio integration within DICOM images are more robust and imperceptible. Both techniques have been proven to be highly precise and supported by empirical evidence such as PSNR, SSIM, and MSE analysis. Robustness analysis was conducted on various image quality variation scenarios that includes compression level, resolution and noise tolerance. The proposed DCT approach achieves a PSNR of 57.89 dB, SSIM of 0.9997, and MSE of 0.013, demonstrating minimal distortion and superior structural integrity. Robustness analysis shows that DCT outperforms the LSB method, consistently maintaining PSNR above 47 dB, MSE approximately zero, and SSIM at 0.99 across varying compression levels, image resolutions, and noise conditions. After conducting an experiment, the DCT technique is the most suitable approach for secure communication of medical data with capacity of 2.03 bits per pixel (bpp). The overall analysis of proposed work significantly improves result in terms of the security and robustness under various attacks.https://ieeexplore.ieee.org/document/10816414/Discrete Cosine Transformleast significant bitsteganographyhealthcaremean squared errorpeak signal-to-noise ratio |
| spellingShingle | Ramyashree P. S. Venugopala S. Raghavendra Vijay S. Kubihal Enhancing Secure Medical Data Communication Through Integration of LSB and DCT for Robust Analysis in Image Steganography IEEE Access Discrete Cosine Transform least significant bit steganography healthcare mean squared error peak signal-to-noise ratio |
| title | Enhancing Secure Medical Data Communication Through Integration of LSB and DCT for Robust Analysis in Image Steganography |
| title_full | Enhancing Secure Medical Data Communication Through Integration of LSB and DCT for Robust Analysis in Image Steganography |
| title_fullStr | Enhancing Secure Medical Data Communication Through Integration of LSB and DCT for Robust Analysis in Image Steganography |
| title_full_unstemmed | Enhancing Secure Medical Data Communication Through Integration of LSB and DCT for Robust Analysis in Image Steganography |
| title_short | Enhancing Secure Medical Data Communication Through Integration of LSB and DCT for Robust Analysis in Image Steganography |
| title_sort | enhancing secure medical data communication through integration of lsb and dct for robust analysis in image steganography |
| topic | Discrete Cosine Transform least significant bit steganography healthcare mean squared error peak signal-to-noise ratio |
| url | https://ieeexplore.ieee.org/document/10816414/ |
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