phat 19(18): e1

Research Article

Hybrid Robust Image Steganography approach for the secure transmission of biomedical images in Cloud

Download57 downloads
  • @ARTICLE{10.4108/eai.13-7-2018.162401,
        author={Arunkumar S and Subramaniyaswamy V and Logesh R},
        title={Hybrid Robust Image Steganography approach for the secure transmission of biomedical images in Cloud},
        journal={EAI Endorsed Transactions on Pervasive Health and Technology},
        volume={5},
        number={18},
        publisher={EAI},
        journal_a={PHAT},
        year={2019},
        month={5},
        keywords={Image Steganography, biomedical images, secure transmission, Cloud, QR Decomposition},
        doi={10.4108/eai.13-7-2018.162401}
    }
    
  • Arunkumar S
    Subramaniyaswamy V
    Logesh R
    Year: 2019
    Hybrid Robust Image Steganography approach for the secure transmission of biomedical images in Cloud
    PHAT
    EAI
    DOI: 10.4108/eai.13-7-2018.162401
Arunkumar S1, Subramaniyaswamy V1,*, Logesh R2
  • 1: School of Computing, SASTRA Deemed University, Thanjavur, Tamilnadu, India
  • 2: Sri Ramachandra Faculty of Engineering and Technology, Sri Ramachandra Institute of Higher Education and Research, Chennai, India
*Contact email: vsubramaniyaswamy@gmail.com

Abstract

INTRODUCTION: A rich patient may reside in their home and may prefer to take treatment with all the medical appliances inside the premise. A patient may take treatment in the less specialized hospital, which may be taking a suggestion from a specialist working in a specialized center. In such a scenario, bio-medical images need to be transmitted over the public network. Bio-medical images sent in plain form suffer from confidentiality and integrity problem.

OBJECTIVES: To overcome the above problem, medical records are always hidden in the cover image so that others do not know what is being sent.

METHODS: In our proposed scheme, the chosen cover image gets divided into the following three planes, namely: R plane, G plane, and B plane. The co-occurrence matrix is computed for each plane by dividing it into 16 x 16 pixels block and then the embedding map is generated from it. The biomedical image is also divided into 8 x 8 pixels block and is hidden into the chosen cover image block using the embedding map. Both cover image blocks and secret image blocks are transformed by RIWT. R matrix of QR decomposition of the cover image and secret image blocks are used in embedding At the end of the embedding phase. These three planes are merged into an RGB image to produce a stego image.

RESULTS: To assess the performance of our scheme, parameters like imperceptibility, robustness, and security are considered. With respect to imperceptibility, PSNR values of the stego images are over 50. With respect to robustness, average NCC values between the original secret and the attacked secret is 0.94. With respect to security, stego image cannot be detected easily if it has any secret.

CONCLUSION: From the experimental results, our scheme is proved to be better with respect to these three selected parameters.