Assessment of the complexity of input data preprocessing procedures for implementing steganographic transformations

An assessment of the complexity of input data preprocessing procedures has been carried out, which ensures the necessary preparation and processing of data for the implementation of content (image) encapsulation procedures within the modeling of the first stage of a hybrid steganographic algorithm. The results obtained confirm that optimized smoothing of low-information areas significantly improves computational efficiency and information hiding quality. Balanced parameter settings allow to achieve a balance between image quality, container capacity, and resistance to unauthorized detection. The adaptive approach ensures the scalability of the method for different types of images and its efficiency on devices with limited resources. The results obtained emphasize the importance of the correct selection of parameters to optimize computations and increase the reliability of steganographic transformations.

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Publication Details

Journal
InterConf
Published
2025-06-20
DOI
https://doi.org/10.51582/interconf.19-20.06.2025.030
Primary Topic
Climate Change and Environmental Impact
Type
article
Field-Weighted Citation Impact
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article

Assessment of the complexity of input data preprocessing procedures for implementing steganographic transformations

InterConf
Climate Change and Environmental Impact
article

Assessment of the complexity of input data preprocessing procedures for implementing steganographic transformations

article en

Abstract

An assessment of the complexity of input data preprocessing procedures has been carried out, which ensures the necessary preparation and processing of data for the implementation of content (image) encapsulation procedures within the modeling of the first stage of a hybrid steganographic algorithm. The results obtained confirm that optimized smoothing of low-information areas significantly improves computational efficiency and information hiding quality. Balanced parameter settings allow to achieve a balance between image quality, container capacity, and resistance to unauthorized detection. The adaptive approach ensures the scalability of the method for different types of images and its efficiency on devices with limited resources. The results obtained emphasize the importance of the correct selection of parameters to optimize computations and increase the reliability of steganographic transformations.

InterConf(58(252))
V. N. Karazin Kharkiv National University (UA)
Openalex Percentile: Top 47%
Climate Change and Environmental Impact
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