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Medical image encryption using fractional discrete cosine transform with chaotic function

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Abstract

In this advanced era, where we have high-speed connectivity, it is very imperative to insulate medical data from forgery and fraud. With the regular increment in the number of internet users, it is challenging to transmit the beefy medical data. This (medical data) is always reused for different diagnosis purposes, so the information of the medical images need to be protected. This paper introduces a new scheme to ensure the safety of the medical data, which includes the use of a chaotic map on the fractional discrete cosine transform (FrDCT) coefficients of the medical data/images. The imperative FrDCT provides a high degree of freedom for the encryption of the medical images. The algorithm consists of two significant steps, i.e., application of FrDCT on an image and after that chaotic map on FrDCT coefficients. The proposed algorithm discusses the benefits of FrDCT over fractional Fourier transform (FRFT) concerning fractional order α. The key sensitivity and space of the proposed algorithm for different medical images inspire us to make a platform for other researchers to work in this area. Experiments are conducted to study different parameters and challenges. The proposed method has been compared with state-of-the-art techniques. The results suggest that our technique outperforms many other state-of-the-art techniques.

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Acknowledgments

The authors are grateful to the anonymous referees for their insightful comments to make this paper more qualitative for other researchers working in the same area.

Funding

We thank the Ministry of Electronics & Information Technology, Government of India (Digital India Corporation (Grant No.U72900MH2001NPL133410)) for granting fund to this prestigious project in the Signal & Image Processing Laboratory at Indian Institute of Technology Patna, India.

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Correspondence to Sumit Kumar.

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Kumar, S., Panna, B. & Jha, R.K. Medical image encryption using fractional discrete cosine transform with chaotic function. Med Biol Eng Comput 57, 2517–2533 (2019). https://doi.org/10.1007/s11517-019-02037-3

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