Securing the COVID Patients’ Medical Records Using Encrypted Image Steganography

Durafe, Asha; Patidar, Vinod

doi:10.1007/978-981-16-5987-4_43

Cited by 3 publications

(2 citation statements)

References 27 publications

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“…", It is crucial yet difficult to update and share such vast volumes of healthcare data in an efficient and safe manner. Potential authors claim that these problems have not been fully examined [6]. More COVID-19 patients' private health information is being gathered and shared across hospitals and clinical labs, which presents further issues.…”

Section: Introductionmentioning

confidence: 99%

“…The imperceptibility of a steganography system signifies the carrier media quality that can be used for hiding the secret message following the algorithm embedment. The security of a steganography system [6] refers to its robustness against various statistical attacks such as the chi-square, human visual system (HVS), and histogram analysis. In this perception, the present research intends to resolve various issues related to the existing steganography system and improve its robustness in terms of high security, high payload capacity, and imperceptibility.…”

Section: Introductionmentioning

confidence: 99%

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A crypto-steganography healthcare management: towards a secure communication channel for data COVID-19 updating

Jabbar¹,

Issa²

2023

IJEECS

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<span lang="EN-US">Nowadays, secure transmission massive volumes of medical data (such as COVID-19 data) are crucial but yet difficult in communication between hospitals. The confidentiality and integrity are two concerning challenges must be addressing to healthcare data. Also, the data availability challenge that related to network fail which may reason concerns to the arrival the COVID-19 data. The second challenge solved with the different tools such as virtual privet network (VPN) or blockchain technology. Towards overcoming the aforementioned for first challenges, a new scheme based on crypto steganography is proposed to secure updating (COVID-19) data. Three main contributions have been consisted within this study. The first contribution is responsible to encrypt the COVID-19 data prior to the embedding process, called hybrid cryptography (HC). The second contribution is related with the security in random blocks and pixels selection in hosting image. Three iterations of the Hénon Map function used with this contribution. The last contribution called inversing method which used with embedding process. <span>Three important measurements were used the peak signal-to-noise ratio (PSNR), the Histogram analysis and structural similarity index measure (SSIM). Based on the findings, the present scheme gives evidence to increase capacity, imperceptibility, and security to ovoid the existing methods problem.</span></span>

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%