Reversible watermarking for image integrity verification in hierarchical PACS

Fontani, Marco; Rosa, Alessia De; Caldelli, Roberto; Filippini, F.; Piva, Alessandro; Consalvo, M; Cappellini, V.

doi:10.1145/1854229.1854259

Cited by 11 publications

(12 citation statements)

References 13 publications

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“…The process of integrating the proposed watermarking technique into medical environments is then clarified and validated. Two studies have been found; one related to manipulation of medical images within PACS database [5] and another study related to tampering with medical images during transmission [13]. In addition, two potential security issues have also been identified in this research.…”

Section: Validation Of the Proposed Medical Imaging Workflowmentioning

confidence: 86%

“…These threats need to be identified first to provide a secure platform for medical imaging workflow that can address these threats. To achieve this, a research paper has been considered as a case study to identify security risks that may face medical images stored in the PACS database [5]. This aids in analyzing the PACS workflow and understanding the security requirements derived from the medical side to determine a suitable approach for integrating the proposed watermarking technique into medical domains.…”

Section: Scenario Four (S4) -Archiving Phasementioning

confidence: 99%

“…The images are then transferred to a hierarchically upper PACS until they arrive the top-PACS to be collected and permanently archived in tapes, physical drives or optical disks. This process is defined as consolidation [5]. For security reasons, the authorized archive is conducted offline, while accessible images are saved on the top-PACS discs.…”

mentioning

confidence: 99%

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Integration of Digital Watermarking Technique into Medical Imaging Systems

Qasim

Aspin

Meziane

2019

2019 10th International Conference on Dependable Systems, Services and Technologies (DESSERT)

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This paper presents the process of integrating digital watermarking technique into medical imaging workflow to evaluate, validate and verify its applicability and appropriateness to medical domains. This is significant to ensure the ability of the proposed approach to tackle security threats that may face medical images during routine medical practices. This work considers two key objectives within the aim of defining a secure and practical digital medical imaging system: current medical digital workflows are deeply analyzed to define security limitations in Picture Archiving and Communication Systems (PACS) of medical imaging; the proposed watermarking approach is then theoretically tested and validated in its ability to operate in a real-world scenario (e.g. PACS). These have been undertaken through identified case studies related to manipulations of medical images within PACS workflow during acquisition, viewing, exchanging and archiving. This work assures the achievement of the identified particular requirements of digital watermarking when applied to digital medical images and also provides robust controls within medical imaging pipelines to detect modifications that may be applied to medical images during viewing, storing and transmitting.

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Section: Validation Of the Proposed Medical Imaging Workflowmentioning

confidence: 86%

Section: Scenario Four (S4) -Archiving Phasementioning

confidence: 99%

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Integration of Digital Watermarking Technique into Medical Imaging Systems

Qasim

Aspin

Meziane

2019

2019 10th International Conference on Dependable Systems, Services and Technologies (DESSERT)

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“…We now briefly describe the AO-PEE embedding procedure as follows. First, for a cover pixel x i , if its complexity measurement n i < T , the prediction-error e i is modified according to (6) to get e i . Then, x i is modified to x i = x i + e i to get the marked pixel.…”

Section: Ao-peementioning

confidence: 99%

Efficient Reversible Data Hiding Based on Multiple Histograms Modification

Zhang

Gui

et al. 2015

IEEE Trans.Inform.Forensic Secur.

278

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Prediction-error expansion (PEE) is the most successful reversible data hiding (RDH) technique, and existing PEE-based RDH methods are mainly based on the modification of one-or two-dimensional prediction-error histogram (PEH). The two-dimensional PEH-based methods perform generally better than those based on onedimensional PEH; however, their performance is still unsatisfactory since the PEH modification manner is fixed and independent of image content. In this paper, we propose a new RDH method based on PEE for multiple histograms. Unlike the previous methods, we consider in this paper a sequence of histograms and devise a new embedding mechanism based on multiple histograms modification (MHM). A complexity measurement is computed for each pixel according to its context, and the pixels with a given complexity are collected together to generate a PEH. By varying the complexity to cover the whole image, a sequence of histograms can be generated. Then, two expansion bins are selected in each generated histogram and data embedding is realized based on MHM. Here, the expansion bins are adaptively selected considering the image content such that the embedding distortion is minimized. With such selected expansion bins, the proposed MHM-based RDH method works well. Experimental results show that the proposed method outperforms the conventional PEE and its miscellaneous extensions including both one-or two-dimensional PEH-based ones.Index Terms-Reversible data hiding, prediction-error expansion, multiple histograms modification, adaptive embedding.

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“…Images captured in a hospital are inserted into the Picture Archiving and Communication Systems (PACS) and then transferred to the hierarchically upper PACS systems until they reach the top-PACS. In the top-PACS, the data is permanently archived in tapes, physical drives, or optical supports to become available for the diagnostic workflow services through drawdown within the PACS system [2].…”

Section: Introductionmentioning

confidence: 99%

Assessment of perceptual distortion boundary through applying reversible watermarking to brain MR images

Qasim

Aspin

Meziane

et al. 2019

Signal Processing: Image Communication

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The digital medical workflow faces many circumstances in which the images can be manipulated during viewing, extracting and exchanging. Reversible and imperceptible watermarking approaches have the potential to enhance trust within the medical imaging pipeline through ensuring the authenticity and integrity of the images to confirm that the changes can be detected and tracked. This study concentrates on the imperceptibility issue. Unlike reversibility, for which an objective assessment can be easily made, imperceptibility is a factor of human cognition that needs to be evaluated within the human context. By defining a perceptual boundary of detecting the modification, this study enables the formation of objective guidelines for the method of data encoding and level of image/pixel modification that translates to a specific watermark magnitude. This study implements a relative Visual Grading Analysis (VGA) evaluation of 117 brain MR images (8 original and 109 watermarked), modified by varying techniques and magnitude of image/pixel modification to determine where this perceptual boundary exists and relate the point at which change becomes noticeable to the objective measures of the image fidelity evaluation. The outcomes of the visual assessment were linked to the images Peak Signal to Noise Ratio (PSNR) values, thereby identifying the visual degradation threshold. The results suggest that, for watermarking applications, if a watermark is applied to the 512x512 pixel (16 bpp grayscale) images used in the study, a subsequent assessment of PSNR=82dB or greater would mean that there would be no reason to suspect that the watermark would be visually detectable.

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Reversible watermarking for image integrity verification in hierarchical PACS

Cited by 11 publications

References 13 publications

Integration of Digital Watermarking Technique into Medical Imaging Systems

Integration of Digital Watermarking Technique into Medical Imaging Systems

Efficient Reversible Data Hiding Based on Multiple Histograms Modification

Assessment of perceptual distortion boundary through applying reversible watermarking to brain MR images

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