Abstract
Healthcare information management has received an enormous deal of attention in recent times due to enormous potential for delivering more precise and cost-effective patient care. The Blockchain network could be used in the healthcare to exchange user data among hospitals, diagnostic laboratories, and pharmaceutical enterprises. Nowadays securing images is a big provocation to maintain confidentiality and integrity. The developed technology in the health industry might be misused by the public network and give chance to unauthorized access. The Blockchain network could be used in the healthcare to exchange user data among hospitals, diagnostic laboratories, and pharmaceutical enterprises. To put it another way, blockchain provides a public record of peer-to-peer transactions so that everyone can view them. This technology helps medical organizations in obtaining insight and enhancing the analysis of medical records. Blockchain technology provides a robust and secure framework for storing and sharing data throughout the healthcare business. In the health sector, the image-based diagnostic is an essential process. This proposed research in blockchain technology allows sharing of patient records in a secured way for telemedicine applications. These images will be shared geographically because these medical images will be passed through public networks, so the security issues like integrity and authentication may occur. These images will be encrypted using cover image and final steganography image is created. Steganography is used as major tool to improve the security of one’s data. This proposed system will have two layers in medical security by using LSB (Least Significant Bit) method with encryption. The medical image should be inserted into a cover image by LSB this is also known as the Stego image. Encryption will be provided in integrity which is a piece of cryptography. The medical image will be secured in the steganography process. The entire process can be executed by using MATLAB 2021 version. The simulation results show that the medical images are secured from various attacks. The extracted image shows minimum mean square error of 0.5.
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References
Lu, W., Xue, Y., Yeung, Y., Liu, H., Huang, J., Shi, Y.-Q.: Secure halftone image steganography based on pixel density transition. IEEE Trans. Dependable Secure Comput. 18(3), 1137–1149 (2020)
Sarmah, D.K., Bajpal, N.: Proposed system for data hiding using cryptography and steganography. J. Comput. Appl. 8(9), 7–10 (2010)
Hassaballah, M., Hameed, M.A., Awad, A.I., Muhammad, K.: A novel image steganography method for industrial Internet of Things security. IEEE Trans. Ind. Inform. 17(11), 7743–7751 (2021)
Singh, A.K., Singh, J., Singh, H.V.: Steganagraphy in images using LSB technique. Int. J. Latest Trends Eng. Technol. 5(1), 426–430 (2015)
Vinothkanna, R.: A secure steganography creation algorithm for multiple file formats. J. Innov. Image Process. 1(01), 20–30 (2019)
Hamid, N., Yahya, A., Ahmad, R.B., Al-Qershi, O.M.: Image steganography techniques. Int. J. Comput. Sci. Secur. (IJCSS) 6(3), 168–187 (2019)
Lu, W., Huang, F., Huang, l.: Edge adaptive image steganography based on LSB matching revisited. IEEE Trans. Inf. Forensics Secur. 5(2), 201–214 (2010)
Saravanan, M., Priya, A.: An algorithm for security enhancement in image transmission using steganography. J. Inst. Electron. Comput. 1(1), 1–8 (2019)
Feng, B., Lu, W., Sun, W.: Secure binary image steganography based on minimizing the distortion on the texture. IEEE Trans. Inf. Forensics Secur. 10(2), 243–255 (2015)
Anderson, R.J., Petitcolas, F.A.P.: On the limits of steganography. IEEE J. Sel. Area Commun. 16(4), 474–481 (1998)
Sedighi, V., Cogranne, R., Fridrich, J.: Steganography by minimizing statistical detectability. IEEE Trans. Inf. Forensics Secur. 11(2), 221–234 (2016). https://doi.org/10.1109/TIFS.2015.2486744
Mohsin, A.H., et al.: PSO–blockchain-based image steganography: towards a new method to secure updating and sharing COVID-19 data in decentralised hospitals intelligence architecture. Multimed. Tools Appl. 80(9), 14137–14161 (2021). https://doi.org/10.1007/s11042-020-10284-y
Pustokhina, I.V., Pustokhin, D.A., Shankar, K.: Blockchain-based secure data sharing scheme using image steganography and encryption techniques for telemedicine applications. In: Wearable Telemedicine Technology for the Healthcare Industry, pp. 97–108. Academic Press (2022). ISBN: 9780323858540. https://doi.org/10.1016/B978-0-323-85854-0.00009-5
Jassbi, S.J., Agha, A.E.A.: A new method for image encryption using chaotic permutation. Int. J. Image Graph. Sig. Process. (IJIGSP) 12(2), 42–49 (2020). https://doi.org/10.5815/ijigsp.2020.02.05
Isinkaye, F.O., Aluko, A.G., Jongbo, O.A.: Segmentation of medical X-ray bone image using different image processing techniques. Int. J. Image Graph. Sig. Process. (IJIGSP) 13(5), 27–40 (2021). https://doi.org/10.5815/ijigsp.2021.05.03
Tiwari, C.S., Jha, V.K.: Enhancing security of medical image data in the cloud using machine learning technique. Int. J. Image Graph. Sig. Process. (IJIGSP) 14(4), 13–31 (2022). https://doi.org/10.5815/ijigsp.2022.04.02
Agrawal, S., Kumar, S.: MLSMBQS: design of a machine learning based split & merge blockchain model for QoS-aware secure IoT deployments. Int. J. Image Graph. Sig. Process. (IJIGSP) 14(5), 58–71 (2022). https://doi.org/10.5815/ijigsp.2022.05.05
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Kandasamy, L., Ajay, A. (2023). Implementation of Blockchain Technology for Secure Image Sharing Using Double Layer Steganography. In: Hu, Z., Wang, Y., He, M. (eds) Advances in Intelligent Systems, Computer Science and Digital Economics IV. CSDEIS 2022. Lecture Notes on Data Engineering and Communications Technologies, vol 158. Springer, Cham. https://doi.org/10.1007/978-3-031-24475-9_16
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