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Adaptive invisible steganography for securing medical images leveraging entropy-based image encryption with the mimic octopus adaptive framework (MOAF)

Crossref DOI link: https://doi.org/10.1007/s10791-025-09719-7

Published Online: 2025-10-07

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Judy, S.

Khilar, Rashmita
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Text and Data Mining valid from 2025-10-07

Version of Record valid from 2025-10-07
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Article History

Received: 25 March 2025

Accepted: 4 September 2025

First Online: 7 October 2025

Declarations

:

: The dataset used in this study comprises de-identified medical ultrasound images and was obtained from a publicly available source on Kaggle: . No administrative permissions were required to access or use the dataset. As this study did not involve direct interaction with human participants or the collection of new human data, approval from an institutional ethics committee was not required. According to the information provided by the original dataset creators, all experimental protocols were approved by the relevant institutional review board, and informed consent was obtained from all participants, including from parents or legally authorized representatives for subjects under the age of 16. All data usage adhered to relevant ethical guidelines and regulations, including those outlined in the Declaration of Helsinki.

: Not applicable for this section

: Not applicable for this section

: The authors declare no competing interests.

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