Image Encryption and Compression for Medical Image Security

Patient medical information in all forms is crucial to keep private and secure, particularly when medical data communication occurs through insecure channels. Therefore, there is a bad need for protecting and securing the color medical images against impostors and invaders. In this paper, an optical medical image security approach is introduced. It is based on the optical bit-plane Jigsaw Transform (JT) and Fractional Fourier Transform (FFT). Different kernels with a lone lens and a single arbitrary phase code are exploited in this security approach. A preceding bit-plane scrambling process is conducted on the input color medical images prior to the JT and FFT processes to accomplish a tremendous level of robustness and security. To confirm the efficiency of the suggested security approach for secure color medical image communication, various assessments on different color medical images are examined based on different statistical security metrics. Furthermore, a comparative analysis is introduced between the suggested security approach and other conventional cryptography protocols. The simulation outcomes acquired for performance assessment demonstrate that the suggested security approach is highly secure. It has excellent encryption/decryption performance and superior security results compared to conventional cryptography approaches with achieving recommended values of average entropy and correlation coefficient of 7.63 and 0.0103 for encrypted images.

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“…In [29], the authors developed various medical image cryptosystems. These cryptosystems can be employed for any form of multimedia data.…”

Section: Related Workmentioning

confidence: 99%

A Fractional Fourier Based Medical Image Authentication Approach

Alqahtani¹,

Amoon²,

El‐Shafai³

2022

Computers, Materials &Amp; Continua

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“…Step 2 Generating a prediction error histogram for each image block then calling pixel points with a prediction error of [− 2, 2] for embedding points. Next, translation resolves embedded space and embedded secret information [24,25], the formula of this translation is as follows:…”

Section: Prediction Error Expansionmentioning

confidence: 99%

“…Step 3 The prediction error [24,25] histogram is generated. Excepting that the value within the selected error range remains unchanged, the other values are shifted to the left and right sides to leave a certain space then the error within the selected error range is moved according to the embedded information.…”

Section: Prediction Error Expansionmentioning

confidence: 99%

A partial encryption algorithm for medical images based on quick response code and reversible data hiding technology

Zhang

et al. 2020

BMC Med Inform Decis Mak

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Background Medical image data, like most patient information, have a strong requirement for privacy and confidentiality. This makes transmitting medical image data, within an open network, problematic, due to the aforementioned issues, along with the dangers of data/information leakage. Possible solutions in the past have included the utilization of information-hiding and image-encryption technologies; however, these methods can cause difficulties when attempting to recover the original images. Methods In this work, we developed an algorithm for protecting medical image key regions. Coefficient of variation is first employed to identify key regions, a.k.a. image lesion areas; then additional areas are processed as blocks and texture complexity is analyzed. Next, our novel reversible data-hiding algorithm embeds lesion area contents into a high-texture area, after which an Arnold transformation is utilized to protect the original lesion information. After this, we use image basic information ciphertext and decryption parameters to generate a quick response (QR) code used in place of original key regions. Results The approach presented here allows for the storage (and sending) of medical image data within open network environments, while ensuring only authorized personnel are able to recover sensitive patient information (both image and meta-data) without information loss. Discussion Peak signal to noise ratio and the Structural Similarity Index measures show that the algorithm presented in this work can encrypt and restore original images without information loss. Moreover, by adjusting the threshold and the Mean Squared Error, we can control the overall quality of the image: the higher the threshold, the better the quality and vice versa. This allows the encryptor to control the amount of degradation as, at appropriate amounts, degradation aids in the protection of the image. Conclusions As shown in the experimental results, the proposed method allows for (a) the safe transmission and storage of medical image data, (b) the full recovery (no information loss) of sensitive regions within the medical image following encryption, and (c) meta-data about the patient and image to be stored within and recovered from the public image.

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“…This verification step essentially solves the false positive detection problem that arises in SVD based watermarking. The experimental results of proposed scheme shows that it is imperceptible and robust against different kinds of attacks [8][9]. For improved security using image compression, watermarking using DCT technique is used which has been combined with image compression technique by using improved adaptive Huffman encoding.…”

Section: Literature Surveymentioning

confidence: 99%

“…For example, in the medical field the necessity of safe identification and rapid diagnosis is crucial. Visual data transmission is considered as the routine work and therefore the necessity for finding out the proper way of transmission of data in different networks [9].…”

Section: Introductionmentioning

confidence: 99%

Image Water-Marking/De-Watermarking using Spatial Domain Technique

Honade,

Ingole

2019

IJEAT

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There are various existing techniques for cryptography and watermarking. The multimedia data security can be achieved by means of encryption and decryption i.e. cryptography. While watermarking is employed for hiding multimedia data using images. The proposed work focuses on the new method combining these strategies for producing effective solution to improve security of secrete multimedia data. In the proposed dissertation work the images will be used as multimedia data. The proposed method involves the encryption of data to be hid. The cover image is then used as the media for hiding encrypted data. The encrypted data combined with cover image is treated as embedded image. The embedded image then compressed using wavelet transforms compression.

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Image Encryption and Compression for Medical Image Security

Abstract: This tutorial presents the problem of protecting the transmission of medical images. The presented algorithms will be applied to images, videos and 3D objects. The main keywords are compression, encryption, watermarking and data hiding.

Cited by 20 publications

References 2 publications

A Fractional Fourier Based Medical Image Authentication Approach

A Fractional Fourier Based Medical Image Authentication Approach

A partial encryption algorithm for medical images based on quick response code and reversible data hiding technology

Image Water-Marking/De-Watermarking using Spatial Domain Technique

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