Exploiting the Block Space Adjustment Strategy for Gradable Color Thumbnail-Preserving Encryption in Industrial IoT

To alleviate the contradiction between image privacy in Internet of Things (IoT) cloud storage platforms and the convenience of platform functionality, a class of visual image privacy preservation schemes, Thumbnail Preserving Encryption (TPE), is proposed. These schemes achieve a balance between preserving image privacy and usability by altering the size of the thumbnail block, which makes the encrypted image well compatible with the convenient features of the IoT cloud storage platform. However, these schemes are flawed in that the color vividness of the encrypted image remains constant regardless of circumstances. These schemes may not be suitable for various applications in different Industrial IoT scenarios since the intensity of color can directly influence individuals’ understanding and assessment of image semantics. To this end, a TPE scheme with gradable color vividness is proposed, which achieves the gradual change of color vividness of encrypted images from dull or distorted to bright or real under any thumbnail block size. In this scheme, the highest bit plane of the image is isolated for block space adjustment, while the remaining 7-bit planes are encrypted using substitution-permutation encryption. By adjusting the sum of the elemental values in the block space to gradually approximate the sum of the elemental values in the original block pixels, the encrypted image and its thumbnail create the effect of a gradual change in color vividness. Furthermore, the vibrancy of the color intensifies as the adjustment ratio is increased. The experimental results show that the scheme does not significantly affect the privacy of the encrypted images, despite the gradual change in color vividness.

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Publication Details

Journal
IEEE Internet of Things Journal
Published
2025-05-19
DOI
https://doi.org/10.1109/jiot.2025.3571286
Citations
2
Primary Topic
Biometric Identification and Security
Type
article
Field-Weighted Citation Impact
2.97
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article

Exploiting the Block Space Adjustment Strategy for Gradable Color Thumbnail-Preserving Encryption in Industrial IoT

Ruoyu Zhao, Dezhi An, Dawei Hao, Yushu Zhang et al.
2 citations
IEEE Internet of Things Journal
Biometric Identification and Security
2.97
article

Exploiting the Block Space Adjustment Strategy for Gradable Color Thumbnail-Preserving Encryption in Industrial IoT

Ruoyu Zhao, Dezhi An, Dawei Hao, Yushu Zhang, Yongming Zhang
article en
2 citations

Abstract

To alleviate the contradiction between image privacy in Internet of Things (IoT) cloud storage platforms and the convenience of platform functionality, a class of visual image privacy preservation schemes, Thumbnail Preserving Encryption (TPE), is proposed. These schemes achieve a balance between preserving image privacy and usability by altering the size of the thumbnail block, which makes the encrypted image well compatible with the convenient features of the IoT cloud storage platform. However, these schemes are flawed in that the color vividness of the encrypted image remains constant regardless of circumstances. These schemes may not be suitable for various applications in different Industrial IoT scenarios since the intensity of color can directly influence individuals’ understanding and assessment of image semantics. To this end, a TPE scheme with gradable color vividness is proposed, which achieves the gradual change of color vividness of encrypted images from dull or distorted to bright or real under any thumbnail block size. In this scheme, the highest bit plane of the image is isolated for block space adjustment, while the remaining 7-bit planes are encrypted using substitution-permutation encryption. By adjusting the sum of the elemental values in the block space to gradually approximate the sum of the elemental values in the original block pixels, the encrypted image and its thumbnail create the effect of a gradual change in color vividness. Furthermore, the vibrancy of the color intensifies as the adjustment ratio is increased. The experimental results show that the scheme does not significantly affect the privacy of the encrypted images, despite the gradual change in color vividness.

IEEE Internet of Things JournalVol. 12(15)
Gansu Institute of Political Science and Law (CN), Jiangxi University of Finance and Economics (CN), Nanjing University of Aeronautics and Astronautics (CN)
Industry, innovation and infrastructure
Openalex Percentile: Top 10%
Biometric Identification and Security
2.97
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