Evidence map›Paper›PMID 35978898›Full record

ArticleComputational intelligence and neuroscience2022

Pigeon Inspired Optimization with Encryption Based Secure Medical Image Management System.

B T Geetha, Prakash Mohan, A V R Mayuri, T Jackulin, J L Aldo Stalin, Varagantham Anitha

Abstract read
In one paragraph

Article in Computational intelligence and neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

B T GeethaDepartment of ECE, Saveetha School of Engineering, SIMATS, Saveetha University, Chennai, India.
Prakash MohanDepartment of Computer Science and Engineering, Karpagam College of Engineering, Coimbatore, India.
A V R MayuriSCSE, VIT Bhopal University, Bhopal, India.
T JackulinDepartment of CSE, Panimalar Engineering College, Chennai, India.
J L Aldo StalinDepartment of Information Technology, Sona College of Technology, Salem, India.
Varagantham AnithaDepartment of Computer Science, Institute of Technology, Hawassa University, Hawassa, Ethiopia.ORCID https://orcid.org/0000-0002-7408-5938

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Presently, technological advancements in the healthcare sector pose a challenging problem relevant to the security and privacy of health-related applications. Medical images can be considered significant and sensitive data in the medical informatics system. In order to transmit medical images in an open medium, the design of secure encryption algorithms becomes essential. Encryption can be considered one of the effective solutions for accomplishing security. Although numerous models have existed in the literature, they could not adaptable to the rising number of medicinal images in the health sector. At the same time, the optimal key generation process acts as a vital part in defining the performance of the encryption techniques. Therefore, this article presents a Pigeon Inspired Optimization with Encryption-based Secure Medical Image Management (PIOE-SMIM) technique. The proposed PIOE-SMIM approach majorly concentrates on the development of secret share creation (SSC) and the encryption process. At the initial stage, the medical images are converted into a collection of 12 shares using the SSC approach. In addition, an elliptic curve cryptography (ECC) scheme is employed for the encryption process. In order to optimum key creation procedure in the ECC model, the PIO technique is exploited with the aim of maximizing PSNR. Finally, on the receiver side, the decryption and share reconstruction processes are performed to construct the original images. The PIOE-SMIM model displayed an enhanced PSNR of 59.37 dB in image 1. Improved PSNR of 59.53 dB is given for image 5 using the PIOE-SMIM model. For demonstrating an enhanced performance of the PIOE-SMIM method, a widespread experimental study is made and the results highlighted the supremacy of the PIOE-SMIM model over other techniques.

Indexed as

Computer SecurityPrivacyAlgorithms

Identifiers

PMID35978898
PMCPMC9377849

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.