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A reversible and secure patient information hiding system for IoT driven e-health

Author

Listed:
  • Kaw, Javaid A.
  • Loan, Nazir A.
  • Parah, Shabir A.
  • Muhammad, K.
  • Sheikh, Javaid A.
  • Bhat, G.M.

Abstract

Internet of things (IoT) coupled with mobile cloud computing has made a paradigm shift in the service sector. IoT-assisted mobile cloud based e-healthcare services are making giant strides and are likely to change the conventional ways of healthcare service delivery. Though numerous approaches for preventing unauthorized access to information exchanged between a mobile phone and cloud platform do exist, but there is no security mechanism to prevent unauthorized access by the cloud administrators. With an aim to ensure security of client data such as Electronic Patient Records (EPR), we propose a novel high-capacity and reversible data hiding approach for securely embedding EPR within the medical images using Optimal Pixel Repetition (OPR). OPR converts every pixel of the input image to a 2 × 2 block to facilitate reversibility by ensuring all the pixels in a 2 × 2 block to have different values. Since a 2 × 2 block is comprised of 4-pixel elements, which could be arranged in sixteen possible ways; we generate a lookup table corresponding to sixteen possible positions of pixels. EPR hiding in each block is achieved by permuting the pixels of a block according to the four-bit word of secret data, resulting in a histogram invariant stego image. The histogram invariance improves the robustness of the proposed scheme to statistical attacks. A stego image is said to hide embedded data securely, when it provides better imperceptivity for an appreciably high payload. Thus, while using information embedding approach for securing client data on a mobile-cloud platform, high imperceptivity is a desirable feature. Experimental results show that average PSNR obtained is 42 dB for payload 1.25 bpp by our scheme, showing its effectiveness for preventing unauthorized access to client’s sensitive data.

Suggested Citation

  • Kaw, Javaid A. & Loan, Nazir A. & Parah, Shabir A. & Muhammad, K. & Sheikh, Javaid A. & Bhat, G.M., 2019. "A reversible and secure patient information hiding system for IoT driven e-health," International Journal of Information Management, Elsevier, vol. 45(C), pages 262-275.
  • Handle: RePEc:eee:ininma:v:45:y:2019:i:c:p:262-275
    DOI: 10.1016/j.ijinfomgt.2018.09.008
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    References listed on IDEAS

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    1. Ogiela, Marek R. & Ogiela, Urszula, 2012. "DNA-like linguistic secret sharing for strategic information systems," International Journal of Information Management, Elsevier, vol. 32(2), pages 175-181.
    2. Williams, Faustine & Boren, Suzanne Austin, 2008. "The role of electronic medical record in care delivery in developing countries," International Journal of Information Management, Elsevier, vol. 28(6), pages 503-507.
    3. Sultan, Nabil, 2014. "Making use of cloud computing for healthcare provision: Opportunities and challenges," International Journal of Information Management, Elsevier, vol. 34(2), pages 177-184.
    4. Lozupone, Vincent, 2017. "Disaster recovery plan for medical records company," International Journal of Information Management, Elsevier, vol. 37(6), pages 622-626.
    5. Gardiyawasam Pussewalage, Harsha S. & Oleshchuk, Vladimir A., 2016. "Privacy preserving mechanisms for enforcing security and privacy requirements in E-health solutions," International Journal of Information Management, Elsevier, vol. 36(6), pages 1161-1173.
    6. Soomro, Zahoor Ahmed & Shah, Mahmood Hussain & Ahmed, Javed, 2016. "Information security management needs more holistic approach: A literature review," International Journal of Information Management, Elsevier, vol. 36(2), pages 215-225.
    7. Gupta, Shivam & Kar, Arpan Kumar & Baabdullah, Abdullah & Al-Khowaiter, Wassan A.A., 2018. "Big data with cognitive computing: A review for the future," International Journal of Information Management, Elsevier, vol. 42(C), pages 78-89.
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    Cited by:

    1. Singha, Sumanta & Arha, Himanshu & Kar, Arpan Kumar, 2023. "Healthcare analytics: A techno-functional perspective," Technological Forecasting and Social Change, Elsevier, vol. 197(C).

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