A framework for sharing images with limited regions of sensitive information

This paper introduces a novel framework that integrates image encryption and secret sharing to facilitate the secure sharing of confidential images, such as identification documents, financial records, medical images, and traffic violation images, which often contain limited regions of highly sensitive information. Existing secret image sharing schemes generally provide a single level of access, allowing any authorized set of participants to reconstruct and view the entire image, even when specific regions are highly confidential and require an additional level of access control. To address this limitation, the proposed framework provides a layered access structure in which general authorized participants can view the document, while access to the sensitive regions is restricted to participants with elevated privileges. More specifically, the sensitive regions of the document are encrypted in place, before sharing using a threshold secret image sharing scheme among the general participants. Furthermore, the decryption key for the sensitive regions is shared among the essential participants (those with elevated privileges) using a threshold secret sharing scheme. As a result, the sensitive parts of the document are revealed only upon presentation of a sufficient number of essential shares. While any threshold secret image sharing scheme may be used within the proposed framework, as a proof-of-concept, this work introduces a secret image sharing scheme that exploits the characteristics of Cauchy matrices to facilitate secure and efficient generation of shadow images. Simulation results demonstrate the efficiency of the proposed framework in terms of the randomness properties of the generated shadow images and its robustness against various common image degradations, such as cropping and salt-and-pepper noise.

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Publication Details

Journal
Multimedia Tools and Applications
Published
2026-08-03
DOI
https://doi.org/10.1007/s11042-026-21835-0
Primary Topic
Image Retrieval and Classification Techniques
Type
article
Field-Weighted Citation Impact
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article

A framework for sharing images with limited regions of sensitive information

Ali Kanso, M. Ghebleh
Multimedia Tools and Applications
Image Retrieval and Classification Techniques
article

A framework for sharing images with limited regions of sensitive information

Ali Kanso, M. Ghebleh
article en

Abstract

This paper introduces a novel framework that integrates image encryption and secret sharing to facilitate the secure sharing of confidential images, such as identification documents, financial records, medical images, and traffic violation images, which often contain limited regions of highly sensitive information. Existing secret image sharing schemes generally provide a single level of access, allowing any authorized set of participants to reconstruct and view the entire image, even when specific regions are highly confidential and require an additional level of access control. To address this limitation, the proposed framework provides a layered access structure in which general authorized participants can view the document, while access to the sensitive regions is restricted to participants with elevated privileges. More specifically, the sensitive regions of the document are encrypted in place, before sharing using a threshold secret image sharing scheme among the general participants. Furthermore, the decryption key for the sensitive regions is shared among the essential participants (those with elevated privileges) using a threshold secret sharing scheme. As a result, the sensitive parts of the document are revealed only upon presentation of a sufficient number of essential shares. While any threshold secret image sharing scheme may be used within the proposed framework, as a proof-of-concept, this work introduces a secret image sharing scheme that exploits the characteristics of Cauchy matrices to facilitate secure and efficient generation of shadow images. Simulation results demonstrate the efficiency of the proposed framework in terms of the randomness properties of the generated shadow images and its robustness against various common image degradations, such as cropping and salt-and-pepper noise.

Multimedia Tools and ApplicationsVol. 85(8)
Kuwait University (KW)
Openalex Percentile: Top 10%
Image Retrieval and Classification Techniques
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